Volume 17 - Nondestructive Evaluation and Quality Control Part 13 docx

Fundamentals of Acoustic Microscopy Methods As a general comparison between the methods, the scanning laser acoustic microscope is primarily a transmission mode instrument that creates

suited to specific applications The vidicons offer the highest frame rates in formats of 1024 and more, the line scanners have excellent resolution at moderate prices, and the micro-densitometers are the most precise with regard to photometric and geometric quantities Most microdensitometers will digitize to 12 bits, which limits their dynamic range to about 3.6

in film density As noted in Table 2, the standard scanning microdensitometer (row one) will take longer (up to several hours) to scan film if the film density is over 2 The laser scanners are faster (depending on the make) because of the more intense laser light source and the fact that one axis is scanned with the light beam rather than mechanically

Table 2 Typical characteristics of image digitization devices

Acquisition time per

1024 2 by 8-bit image

Interscene dynamic range

Image area, mm

× mm (in × in.)

(a) Aperture

(b) 776 × 512

Linear CCD or photodiode arrays are good choices for film digitization and can have even better dynamic ranges than those listed in Table 2 When these devices are cooled, each 7 °C (13 °F) reduction in temperature reduces the root mean square noise by a factor of two The charge-coupled device and charge injection device are capable of good dynamic range and fair resolution, but have certain artifacts (Ref 12) Again, if the devices are cooled, the noise floor is reduced, and they can be integrated for long periods to enhance the dynamic range and sensitivity Cooled CCDs are available that rival the low light sensitivity of silicon-intensified targets (SITs), but not the frame speed

In general, the frame rate, dynamic range, and resolution are all interrelated The interscene dynamic range is listed as the maximum achievable for the microdensitometers and as the dynamic range that can be achieved at the given frame rate for the other devices The faceplate illumination given for the tubes and the solid-state detectors assumes mid-level illumination (halfway between saturation and preamplifier noise) (Ref 13) This may vary among tubes and generic types

by a factor of three to four (Ref 14) The interscene dynamic range will also vary greatly, but can be maximized by the proper selection of a tube such that a dynamic range of 200 can be achieved at 33 ms/field with a high resolution (>1000 lines)

The quoted resolution for the tubes is at a modulation transfer function (MFT) of 5%, which means that the contrast between a black line and a white line is only 5% at the stated resolution This, of course, is measured at optimum illumination and at the center of the tube image field Under other conditions, the resolution will be less For comparison,

a 10242 CCD camera may have an MTF of 5% at 750 lines The lags quoted for the tubes are typical for the particular type at 3 TV fields or 50 ms Tube cameras are primarily used in radiation environments or in specialized applications, such as high-resolution real-time radiography, in which the frame rate is higher than that achievable by current CCD designs Charge-coupled device camera design is rapidly evolving for high-resolution scientific use and can be expected

to improve with regard to real-time frame rates (Ref 12, 15)

It should be noted that a 355 × 432 mm (14 × 17 in.) film digitized at a resolution of 50 m (0.002 in.) with 12-bit accuracy will consume a 92-Mbyte file Just writing or reading this file to or from a hard disk could take up to 8 min (optical disks take even longer) Even with high-density optical disks and data compression, the digital storing of high-resolution radiographs represents a formidable problem

References cited in this section

3 R.C Gonzalez and P Wintz, Digital Image Processing, Addison-Wesley, 1977

12 J.R Janesick, T Elliott, S Collins, M.M Blouke, and J Freeman, Scientific Charge Coupled Devices, Opt Eng., Vol 26 (No 8), 1987, p 692-714

13 I.P Csorba, Image Tubes, Howard W Sams & Co., 1985

14 G.I Yates, S.A Jaramillo, V.H Holmes, and J.P Black, "Characterization of New FPS Vidicons for Scientific Imaging Applications," LA-11035-MS, US-37, Los Alamos National Laboratory, 1988

15 L.E Rovich, Imaging Processes and Materials, Van Nostrand Reinhold, 1989

Digital Image Enhancement

T.N Claytor and M.H Jones, Los Alamos National Laboratory

Image Processing

Prior to image processing, it may be necessary to perform some type of preprocessing on the data Most often, an image file will need to be converted into the workstation standard from some other type of format; for example, the files may be 8-, 16-, or 24-bit uncompressed format with a variable-length header and need to be converted to 8-bit format with no header Typically, a problem arises when a file must be read that is in an unknown size, a compressed format, or has a limited color or nonstandard palette

Other preprocessing functions operate on the raw data in some manner before inputting it for image processing For example, the system should have the capability to average, filter, and acquire full frames and control the scanning parameters on the digitizer so that the noise level can be minimized In other cases, more complicated operations are called for, such as tomographic reconstruction, synthetic aperture operations, or an FFT Shown in Fig 1(a) and (b) in the article "Use of Color for NDE" in this Volume are tomographs taken before and after oversampling by a factor of four and Wiener filtering of the input data set to correct for the point spread function (Ref 16) The preprocessing operation greatly increases the smoothness of the lines and reduces the artifacts

Reference cited in this section

16 K Thompson, private communication, Sandia National Laboratories, 1988

Digital Image Enhancement

T.N Claytor and M.H Jones, Los Alamos National Laboratory

Image Enhancement

There are three major scientific applications for image processing:

• Enhancement of an image to facilitate viewing

• Manipulation and restoration of an image

• Measurement and separation of features

These functions are listed in Table 3 Many of the functions have a dual purpose and, as will be shown, are usually combined to form other functions

Table 3 Image-processing software algorithms useful for NDE applications

Image enhancement Image

operations

Information extraction

Contrast stretching Scaling Image statistics

Histogram equalization Translation Point, line, angle perimeter, area, measurement

Contouring Rotating FFT transformation, one and two dimensional

Thresholding Registration Correlation

Composite image building Warping Edge detection

Palette operations Combining Deblurring

Color model selection Filtering Motion restoration

True color representation Thickening, thinning

Noise cleaning Trend removal

where r is the original pixel value and s is the transformed pixel value

Fig 3 Concept of histogram stretching and equalization (a) Histogram is stretched with a linear

transformation (b) Histogram is equalized such that the probability density is constant

The linear stretch and offset method is the most commonly applied, while transforms of the nonlinear type can be used to convert film density to integrated dose or to linearize the film transfer function to account for base density Although the manual contrast stretch is often used, a more automated contrast stretch is available with an operation known as histogram equalization The general form is:

(Eq 2)

A simple linear equalization example is shown in Fig 3(b) Occasionally, it may be desirable to use the cubic or logarithmic equalization The cubic emphasizes the lower values, making the image darker, while the exponential makes the image much brighter Other types of transfer functions are often used to remove nonlinear response in the imaging or camera system For isolated defects, a manual stretch usually gives good results On textured materials, however, histogram equalization often works well An example of a linear histogram equalization of a low-contrast ultrasonic image of a bond line in an explosively bonded steel-to-aluminum plate is shown in Fig 2 in the article "Use of Color for NDE" in this Volume

Contouring and Thresholding. Contouring and thresholding are often combined with palette operations to show gradations in intensity or to highlight defects Color should be used to detect gradients in intensity because the eye is sensitive to many more colors (approximately 104 shades) than gray levels Thresholding can be done with a binary picture (black and white), a color scale, or a combination of gray and color The concept of thresholding has particular application in the generation of a mask for future image-processing operations or the removal of the background Contouring is used to change only those values between two pixel levels to a certain value It can also be used in outlining high-definition features before further processing

Composite Image Building. The ability to display composite images is useful in comparing the difference between images produced by different modalities, such as a radiograph and an ultrasonic or NMR image Because image quality suffers greatly when displayed at resolutions of less than 5122 it is imperative to have at least a 10242 display or to use two monitors if detailed comparisons are to be made Figure 4 illustrates how x-ray radiographs and neutron radiographs can be displayed together and combined to enhance voids in a composite material As shown in Fig 4(c), the images have simply been added to enhance the detection of voids The absorption of neutrons in the epoxy is higher than in the alumina and the reverse is true for the absorption of x-rays However, the voids do not absorb in either case, and the contrast is therefore improved if the images are added

Fig 4 Voids detected in three 60 × 60 × 10 mm (2.4 × 2.4 × 1 in.) alumina-filled epoxy tiles using three

different imaging techniques (a) Conventional radiography (b) Neutron radiography (c) Combined x-ray and neutron radiographic image Building a composite image of both modalities indicates that there are voids in the sample The addition of the two images enhances the voids because of the differential absorption in the matrix between the x-ray and neutron images

Palette Control. Color can be displayed as a true color map or as a pseudocolor representation In a pseudocolor representation, the digital data values are mapped to any color that can be produced by the combination of the red, green, and blue (RGB) values specified by a look-up table (LUT) A typical 8-bit pseudocolor system is shown in Fig 5(a) With only an 8-bit-deep pixel as shown in Fig 2, a type of true color is possible; however, each color is represented only by eight or fewer color levels (Fig 5b) With 8-bits per color (as in Fig 5c), the colors can be shaded continuously and are suitable for three-dimensional displays in which depth cueing is indicated by decreasing the luminance Eight-bit pixels with 24-bit LUTs can produce good color scenes by adjusting the LUT to include only those colors that appear in a scene However, the palette is then image specific

Fig 5 Concept of a look-up table for three types of color displays (a) bit pseudocolor representation (b)

8-bit true color map (c) 24-8-bit true color map The LUT is controlled by the palette, which specifies what color composition (R,G,B) will be assigned to one of 256 levels, as in (a) The digital-to-analog converter (DAC) converts the digital signal to RGB for input to the monitor Shown in (b) is a way to display true color with an 8- bit pixel Better true color can be obtained by using a 24-bit pixel, with each byte (8 bits) assigned to a specific primary color, as in (c)

Several types of pseudocolor and linear gray-scale palettes are shown in Fig 4 in the article "Use of Color for NDE" in this Volume The spectrum palette (or inverse spectrum) is preferred for range of color, but is not suitable for displaying rapid changes in pixel level Other palettes, such as the complementary palettes shown in Fig 4(d) and (e), can be used with good results on figures that have gradual changes in gray level A typical threshold palette is shown in Fig 4(b) All values below 192 will appear as a gray scale, while those equal to or above 192 will appear as red The gray scale is still used to display lower-intensity data so that the operator can still detect unusual, yet not rejectable, anomalies In contrast stretching, when further work on the image is anticipated, the palette (that is, LUT values) is altered, leaving the pixel values intact

Color Models and the Use of Color. There are two main color models: the red, green, blue (RGB) model and the hue, saturation, luminance (HSL) model High-resolution imaging systems use the RGB model, while the National Television Systems Committee has adopted the HSL model for broadcast television The colors in the RGB model are simply an additive mixture of the Commission Internationale de l'Éclairage monochromatic primary colors (red = 700 nm,

or 7000 Å; green = 546.1 nm, or 5461 Å; and blue = 435.8 nm, or 4358 Å) When equal intensities of these colors are combined, a nearly white light results In the HSL model, the primaries are transformed such that the hue value represents the color (0 to 360°; red = 0, 360; green = 120; and blue = 240), the saturation is the color intensity (values 0 to 1), and

the luminance is the amount of brightness (0 to 1) If the saturation is 0 and the luminance is 1, the color will be white The advantage of the HSL model is that a single hue can be manipulated in intensity more easily than with the RGB model

Although both color and black-and-white images contain the same information, there are features that are much more obvious in color plots than in corresponding black-and-white plots, and vice versa In particular, a black-and-white representation is appropriate when there is a high spatial frequency inherent in the image; in such a case, the mind-eye combination interprets this as a texture On the other hand, color is preferred when there are a few isolated objects or low spatial frequency This makes it easier for the image interpreter to discern small changes in image density through the use

of contrast enhancement Black-and-white images are shown in Fig 6 and 7, and the color versions are shown in Fig 6(c) and (d) in the article "Use of Color for NDE" in this Volume

Fig 6 Ultrasonic image of a hot isostatic pressed tungsten plate prepared from powder (99% dense) The

black-and-white image shows small changes in density that are not easily discernible The density changes are enhanced by the use of color, as shown in Fig 6(c) of the article "Use of Color for NDE" in this Volume The ring

is caused by a transition from one thickness to another (the outer thickness was about 50% of the inner circle)

Fig 7 Tungsten plate similar to the one shown in Fig 6, except that this part was fabricated from a plate that

was rolled rather than hot isostatic pressed The black-and-white image shows a texture imparted to the material due to the inclusion of 2% porosity The color version of the plate, Fig 6(d) in the article "Use of Color for NDE" in this Volume, shows how difficult the texture is to interpret in a color representation using a spectrum palette

Digital Image Enhancement

T.N Claytor and M.H Jones, Los Alamos National Laboratory

duplication of pixels In the case of integer scaling (×2, ×3), the pixels are replicated in the x and y by the integer For

noninteger scaling (such as magnification by 1.5), every other pixel is replicated Image interpolation and noninteger scaling should be avoided unless the image is subsequently filtered or unless interpolation and scaling are the last steps in

a processing chain before printing The printer will often perform interpolation and dithering (adding a small random number to the value) to obtain an image with a smoother appearance:

(Eq 3)

Warping is a nonlinear scaling process The equation for a sixth-order warp is:

u = a1 + a2x + a3y + a4xy + a5x2 + a6y2

v = b1 + b2x + b3y + b4xy + b5x2 + b6y2 (Eq 4)

This transform can be of use if an object is at an angle to the viewing plane and it is necessary to measure a feature of interest or to correct the image for the viewing angle

Image registration can be performed by trial and error with the rotation, translation, and scaling functions The goodness of fit can be calculated with the correlation function or by subtraction Registration is usually a prior step to image combination

Image Combination. Image combination operations generally include the following: AND, NAND, OR, NOR, XOR, difference, subtract, add, multiply, divide, and average All these operations require two operands One will be the data in the primary image, the other can be either a constant or data in a secondary image The image combination operations are used to mask certain areas of images, to outline features, to eliminate backgrounds, to search for commonality, and/or to combine images For example, a video of a part can be taken, edge enhanced, boosted, ANDed with 128 added to 127 and scaled and registered with a radiograph or other image, and then added to the other image

Filtering. There are many types of spatial filters The most useful are low pass, high pass, edge, noise, and morphological, as listed in Table 4

Table 4 Commonly used image filters

Convolution filters Other filters

High pass Median

Low pass Erosion

Horizontal edge Dilation

Vertical edge Unsharp mask

Laplacian Roberts

Sobel or Prewitt

Compass

Wiener

Many filters are classified as convolution filters The convolution filter uses the discrete form of the two-dimensional

convolution integral to compute new pixel values In Eq 5, the image matrix is defined as f(x,y), and the filter is a small 3

× 3 or (in general, m × n) matrix called a kernel, K In practice, the kernel is limited to a size of less than 20 × 20 because

the FFT filtering procedure becomes faster than direct convolution for large kernels The discrete form of the convolution integral is:

Fig 8 Various convolution kernels and their use

Other filters that are useful in image processing are the median, erosion, dilation, and unsharp mask filters The median filter selects the median value in an image neighborhood (usually 3 × 3) and replaces the center pixel with the median value This filter can be very effective in removing isolated pixel noise without blurring the image as severely as the low-pass filter The effect of a low-pass and a median filter is shown on a noisy ultrasonic image of a hot-rolled plate in Fig 3(a), (b), and (c) in the article "Use of Color for NDE" in this Volume The erosion and dilation filters work by replacing the center pixel value in a neighborhood with the smallest or largest index in the neighborhood, respectively They can be used to thicken or to thin boundaries The unsharp mask filter algorithm is:

g(x,y) = 2 · f(x,y) - L P F (f)xy (Eq 7)

where LPF is the low-pass filter The new image is the difference between the original image multiplied by a factor and the low-pass filtered image This operation tends to enhance the contrast and to sharpen the edges slightly

The Roberts and Sobel filters are similar types of edge detectors The Roberts filter algorithm is:

g(x,y) = {[f(x,y) - f(x + 1, y + 1)]2 + [(f(x,y + 1)

This algorithm operates on a 2 × 2 neighborhood and will enhance high frequencies, while the Sobel filter operates with a

3 × 3 kernel and will produce good (but thick) outlines of images The Sobel filter algorithm is:

g(x,y) = ({[(f(x + 1, y - 1) + 2 · f(x + 1, y) + f(x + 1, y + 1)] - [(f(x - 1, y - 1) + 2 · f(x - 1, y) + f(x - 1, y + 1)]}2+ {[f(x - 1, y - 1) + 2 · f(x, y - 1) + f(x + 1, y - 1)] - [f(x - 1, y + 1) + 2 · f(x, y + 1) + f(x + 1, y + 1)]}2)1/2

(Eq 8b)

A summary of the effect of various filters and edge detectors is shown in Fig 9

Fig 9 Ultrasonic image of an adhesive bond (250 m, or 0.01 in., thick) between two opaque plastic parts (a)

Unfiltered (b) Filtered with numerous filter types (vertical edge, high pass, Laplacian, Roberts, and Sobel)

There is a class of filters that restore image quality by considering a priori knowledge of the noise or the degradation

mechanism An example is the inverse filter In this case, the image has been degraded and is reestimated by the use of

the inverted degrading transfer function and a noise model to minimize the least square error This type of filter can be useful if a transfer function model is derived for the imaging chain

For noise cleaning, the filters listed in Table 4 and the median filter can be used Fast Fourier transform techniques are particularly effective for the removal of periodic noise, especially filtering in the frequency domain

Trend removal, or field flattening, is an important processing function to perform before contrast enhancement In most cases, an x-ray film will not have a uniform density even if the part is uniform In addition, variations in density may occur when the part is digitized with a camera When the technique of contrast enhancement is attempted, parts of the image will saturate, and defects will be difficult to detect, as in the ceramic disk shown in Fig 6(a) of the article "Use of Color for NDE" in this Volume Listed below are techniques used to reduce the effect:

1 High-pass filter using an FFT

2 Low-pass filter using a large kernel or FFT, and subtracted from the original image

3 Polynominal fitted to image line and fitted curve subtracted from original

Most of these algorithms produce artifacts and are not entirely satisfactory, especially if there is a high spatial frequency superimposed on a low-frequency trend Figure 6(b) of the article "Use of Color for NDE" in this Volume shows the results of using technique 2 (similar to unsharp masking) on a noisy image with a top-to-bottom trend

Digital Image Enhancement

T.N Claytor and M.H Jones, Los Alamos National Laboratory

Simple measurement functions that are often used are:

• Determination of the pixel value at a particular point (such as on a defect)

• Conversion of the pixel value to film density or part density

• The distance from one pixel to another in terms of pixel units or engineering units

• The angle of one line with respect to another

It is very desirable to be able to measure both the perimeter and the area of a defect In many cases, such as a part with many voids, it may be desirable to obtain the total area of all defects above (or below) a threshold and their radius in terms of pixel values or engineering units and then to produce a histogram of the defect radii This type of quantitative analysis is useful for material evaluation as a function of processing variables

Fast Fourier Transform. The FFT algorithm is central to many filtering and information extraction schemes The dimensional FFT is analogous to the one-dimensional FFT in that the function extracts frequency-dependent information from the waveform or image A discrete form of the two-dimensional FFT algorithm is:

two-(Eq 9)

Specific methods for calculating Eq 9 are given in Ref 6 and 17

The most direct uses of the FFT and inverse FFT are as filters to eliminate periodic noise from an image The noise may

be a periodic pattern, as in the case of the filament-wound vessel shown in Fig 10(a), or it could be 60-cycle noise The general filter procedure is shown in Fig 10 The image is simply transformed, edited, and inverse transformed In Fig 10(a), the original radiograph shows a section of a filament-wound vessel with a cut in the windings After the transform, the signal from the filament-wound structure is seen to radiate from the center at 45° (Fig 10b) The filament-wound structure is removed from the image by removing the frequency components of the structure as shown in Fig 10(c) As shown in Fig 10(c) the zero frequency component (center pixel) is left intact to restore the average gray-level value The image is then inverse transformed to recreate the original image minus the 45° filament pattern Figure 10(d) shows the pattern after the inverse transform; the cut section is readily apparent

Fig 10 General procedure used to filter an image with the FFT (a) Original image (b) Image transformed to

the frequency domain (c) Image edited (d) Image inverse transformed into the filtered image

A correlation function can be used directly to detect objects or features of an image that are of interest or to align images for combination If two images that are generated from different modalities are to be combined and a registration mark is not present, the two images can be correlated over a region of interest and moved until the correlation coefficient peaks This is best accomplished in images having edges or texture, such as those shown in Fig 4 and 7

The edge detection filters described in the section "Image Operations" in this article are often used to detect or outline images; in particular, the Sobel filter works well on high-definition or noisy edges In radiographs having noisy, fuzzy, and low-contrast edges, the Laplacian, Roberts, Sobel, and simple convolution filters will usually not produce good

results Edge followers, Hough transforms, and other ad hoc algorithms that depend on knowledge of the rough shape of

the curve (template matching) to be outlined work satisfactorily in most cases These algorithms, although of some use, are usually not part of a processing package because of their specialized applications

Advanced Functions. General formulations of image restoration functions such as motion restoration, deblurring, maximum entropy, and pattern recognition are not commonly found in general image-processing software packages, probably because of the computation required and the limited demand for these applications These algorithms are discussed in Ref 3 (motion restoration), Ref 1 and 3 (deblurring), Ref 9 (maximum entropy), and Ref 1 and 10 (pattern recognition) The algorithms are of use in the restoration of flash radiographs or high-speed video as well as the correction of point-spread function in tomography or ultrasonics Maximum entropy methods may be of use in the enhancement of NMR signals and other low signal-to-noise data, while pattern recognition can be of use in automating the detection of flawed, incomplete, or misassembled parts

References cited in this section

1 W.K Pratt, Digital Image Processing, John Wiley & Sons, 1978

3 R.C Gonzalez and P Wintz, Digital Image Processing, Addison-Wesley, 1977

6 H.K Huang, Element of Digital Radiology: A Professional Handbook and Guide, Prentice-Hall, 1987

9 B.R Frieden, Image Enhancement and Restoration, in Picture Processing and Digital Filtering, Vol 6, Topics in Applied Physics, T.S Huang, Ed., Springer-Verlag, 1979, p 177

10 D.H Janney and R.P Kruger, Digital Image Analysis Applied to Industrial Nondestructive Evaluation and

Automated Parts Assembly, Int Adv Nondestr Test., Vol 6, 1979, p 39-93

17 C.S Burrus and T.W Parks, DFT/FFT and Convolution Algorithms: Theory and Implementation, John

Wiley & Sons, 1985

Digital Image Enhancement

T.N Claytor and M.H Jones, Los Alamos National Laboratory

Image Display

A wide variety of devices and techniques are available for the display and output of the processed data

CRT Displays. The CRT display is the standard means of output for all imaging applications because the range of colors, brightness, and dynamic range cannot be matched by any other display technology Black-and-white monitors can have resolutions of up to 2000 × 1500 pixels, bandwidths of the order of 200 MHz, and a brightness of 515 cd/m2 (150 ft-L) at a dynamic range in excess of 256 Color monitors may have 1280 × 1024 pixels and bandwidths of 250 MHz High-resolution color monitors have a brightness of 85 cd/m2 (25 ft-L) or more, with a dynamic range of 256 when viewed in dim light

Recent advances in tube design have darkened the shadow mask by a factor of four to allow increased room illumination with no degradation in dynamic range The only other major advance in CRT technology is the recent introduction of flat-screen tubes with resolutions up to 640 × 480 pixels

The standards for video output are the RS-170, which specifies 525 lines of interlaced video at a frame rate of 30 Hz, and RS-343-A, which specifies 1023 interlaced lines also at a 30-Hz frame rate Most modern monitors have special circuitry that enables the monitor to sync to various standards with either the sync superimposed on the green signal or as a separate input Most high-resolution (1280 × 1024) imaging systems use a 483 mm (19 in.) tube operating in a noninterlaced mode at 60 to 64 Hz for the primary display

Printers. Various color and black-and-white printers are available for hard copy A simple method of hard copy for color and black-and-white is to photograph the CRT screen or a small (80 mm, or 3 in.) very flat screen directly with

an 8 × 11 in or smaller Polaroid-type camera The disadvantages of this method are the cost of the instant film in the large format and the small size of the image in the 4 × 5 in format However, the color quality of the image is excellent

The two other types of color printers for small-system color output are ink-jet printers and thermal-transfer printers The ink-jet printers are very inexpensive and produce vivid colors at 180 dpi on paper, but have poor contrast on transparency material The thermal copiers are more expensive but produce high-resolution copies (300 dpi) by transferring color from

a Mylar sheet onto paper or film with very good color and color density The Polaroid cameras can reproduce all the colors seen on the screen, while the ink-jet and thermal-transfer printers will produce at least 162 colors at 150 or 90 dpi, with 2 × 2 pixel enlargement

Table 5 lists the possible color and black-and-white hard copy output devices suitable for printing images Impact printers and plotters are not listed, because of the limited number of colors and poor resolution Also not listed in Table 5 are the color printers based on the Xerox process

Table 5 Typical characteristics of color and black-and-white hard copy output devices

Camera Excellent Very good

Thermal transfer 300 Very good Very good

Ink-jet 180 Good Fair

Black and white

Camera Excellent Very good

Laser film 300 Very good Very good

Thermal paper 300 Good

Thermal transfer 300 Fair Fair

Laser printer 300 Poor Poor

Ink-jet 180 Poor Very poor

There are many more black-and-white printers available than color; however, the high-quality printers are restricted to the camera type and the laser film printer The laser film printer writes with a modulated laser directly on a special dry silver paper or film that is then developed with heat These printers are capable of producing 64 shades of gray on paper and 128 shades on film at 300 dpi with very dense blacks The other devices listed in Table 5 have poor resolution or low contrast

The other black-and-white printers produce poor plots because they are binary printers (a pixel may be black or white) at

300 dpi

To achieve a gray scale, the printer must use a 2 × 2, 3 × 3 or other super pixel size, and this decreases the effective resolution If a 2 × 2 pixel is used, the printer can print only five shades of gray at 150 dpi; if 3 × 3 pixels are used (100 dpi), ten shades are possible The printers can actually produce many more shades by programming the device driver for a super pixel dithering In this case, the program looks at a large super pixel of 5 × 5, determines whether or not the pixel should be smaller, and adjusts the dot density with a dither so that, effectively, about 26 or more shades of gray are perceived with a resolution of about 100 dpi

Videotape and Videodisk. A common use of videotape is to input TV frames from a dynamic test to the processing system For example, a high-speed video can be made of a pressure vessel as it bursts Later, the sequential frames are captured and enhanced to determine the shape of the initiation crack or the speed of crack growth Conversely, radiographs can be made periodically during the slow evolution of a part under the influence of some external variable (for example, void coalescence in ceramics as a function of temperature) The radiographs are then digitized and interpolated to form a time-compressed video

image-Videodisks can be made in a write once read many format with relatively inexpensive machines image-Videodisks offer better resolution and more convenient frame access than videotape Another alternative for the display of dynamic data is to use the hard disk in the imaging workstation Hard disk transfer rates (300 kbytes/s) allow small (200 × 200) movies to be shown on a workstation screen for tens of seconds (depends on disk size) at seven frames per second Ultimately, it will

be possible to expand compressed data quickly enough so that it can be read off a hard disk or a removable digital optical disk in near real time for significant durations

The processing of tape can be tedious because of the amount of data required for a few seconds of video and also because

of the limited resolution However, the techniques of video data display are a very powerful enhancement tool because of the attraction of the eye to changing features

Pseudo Three-Dimensional Images. All discussion of output data display has been in terms of a flat dimensional representation This is the display of preference for processing because the algorithms are available or easily coded However, depending on the data and the method of acquisition, other types of displays may be more appropriate Shown in Fig 10(a) and (b) in the article "Use of Color for NDE" in this Volume are two ways to present two-dimensional data in three dimensions In Fig 10(a), a two-dimensional ultrasonic microscopy image of a circuit board is shown with two defective metallic conductor pads (Ref 18) The image lines are drawn, as in the terrain-mapping method, with high values elevated with respect to low values and with a hidden line algorithm Another way to present two-dimensional image data is shown in Fig 10(b) In this case, the two-dimensional ultrasonic data were taken from a C-scan

two-of a filament-wound sphere with Teflon shims imbedded in the matrix (Ref 19) Presenting the two-dimensional data in this manner results in a realistic display and facilitates interpretation

Tomographic, ultrasonic, and NMR data sets may consist of many two-dimensional images that can be stacked to yield a picture of a true three-dimensional object There are two ways to represent this three-dimensional data In the first method, the data are modeled as a geometric solid or surface; in the second method, the data are displayed as raw data, or voxels (volume elements) The first method is used in solids-modeling workstations for design engineering It can also be used to image NDE data, especially if the number of modeled elements is very large (105 or more) or has many surfaces Figure 11 shows a three-dimensional reconstruction of a bundle of bent fuel rods after a reactor accident test The image was constructed of 250 individual 128 × 128 pixel tomograms A type of surface modeling that treats surfaces as polygons was used to model the rods An inspection of the original tomograms shows that it is impossible to quickly grasp the shape of the bent rods from simple two-dimensional plots (Ref 20) Another three-dimensional reconstruction of this failed assembly can be found in Fig 9 in the article "Use of Color for NDE" in this Volume

Fig 11 Three-dimensional perspective plot representation of a bundle of failed, bent fuel rods The

representation was reconstructed from three-dimensional data sets obtained from a series of 250 individual 128

× 128 pixel tomographic slices of the rod bundle

Figure 8 in the article "Use of Color for NDE" shows a tomogram of a turbine blade that was displayed in terms of voxel imaging (also known as volume rendering), rather than modeling the surfaces by polygons or other shapes Volume elements are created from the raw data, and these voxels are then projected to a view surface to produce an image The raw data are not actually displayed Figure 8 also demonstrates how the surfaces can be made transparent and the lighting model adjusted for a realistic effect Graphics accelerators are available so that the images shown in Fig 8 can be rotated, lighting sources adjusted, and textures added in almost real time (see Fig 7 of the article "Use of Color for NDE" in this Volume) Three-dimensional image processing is in its infancy, but many medical and NDE applications are envisioned (Ref 21)

References cited in this section

18 J Gieske, private communication, Sandia National Laboratories, 1988

19 W.D Brosey, Ultrasonic Analysis of Spherical Composite Test Specimens, Compos Sci Technol., Vol 24,

1985, p 161-178; private communication, Sandia National Laboratories, 1988

20 C Little, private communication, Sandia National Laboratories, 1988

21 A.R Smith, Geometry and Imaging: Two Distinct Kinds of Graphics, to be published 1989; private

communication

Digital Image Enhancement

T.N Claytor and M.H Jones, Los Alamos National Laboratory

References

1 W.K Pratt, Digital Image Processing, John Wiley & Sons, 1978

2 M.H Jacoby, Image Data Analysis, in Radiography & Radiation Testing, Vol 3, 2nd ed., Nondestructive Testing Handbook, American Society for Nondestructive Testing, 1985

3 R.C Gonzalez and P Wintz, Digital Image Processing, Addison-Wesley, 1977

4 G.A Baxes, Digital Image Processing: A Practical Primer, Prentice-Hall, 1984

5 W B Green, Digital Image Processing: A Systems Approach, Van Nostrand Reinhold, 1983

6 H.K Huang, Element of Digital Radiology: A Professional Handbook and Guide, Prentice-Hall, 1987

7 A Rosenfeld and A.A Kak, Digital Picture Processing, Academic Press, 1982

8 K.R Castleman, Digital Image Processing, Prentice-Hall, 1979

9 B.R Frieden, Image Enhancement and Restoration, in Picture Processing and Digital Filtering, Vol 6, Topics in Applied Physics, T.S Huang, Ed., Springer-Verlag, 1979, p 177

10 D.H Janney and R.P Kruger, Digital Image Analysis Applied to Industrial Nondestructive Evaluation and

Automated Parts Assembly, Int Adv Nondestr Test., Vol 6, 1979, p 39-93

11 J.J Dongarra, "Performance of Various Computers Using Standard Linear Equations Software in a Fortran Environment," Technical Memorandum 23, Argonne National Laboratory, 1989

12 J.R Janesick, T Elliott, S Collins, M.M Blouke, and J Freeman, Scientific Charge Coupled Devices,

Opt Eng., Vol 26 (No 8), 1987, p 692-714

13 I.P Csorba, Image Tubes, Howard W Sams & Co., 1985

14 G.I Yates, S.A Jaramillo, V.H Holmes, and J.P Black, "Characterization of New FPS Vidicons for Scientific Imaging Applications," LA-11035-MS, US-37, Los Alamos National Laboratory, 1988

15 L.E Rovich, Imaging Processes and Materials, Van Nostrand Reinhold, 1989

16 K Thompson, private communication, Sandia National Laboratories, 1988

17 C.S Burrus and T.W Parks, DFT/FFT and Convolution Algorithms: Theory and Implementation, John

Wiley & Sons, 1985

18 J Gieske, private communication, Sandia National Laboratories, 1988

19 W.D Brosey, Ultrasonic Analysis of Spherical Composite Test Specimens, Compos Sci Technol., Vol 24,

1985, p 161-178; private communication, Sandia National Laboratories, 1988

20 C Little, private communication, Sandia National Laboratories, 1988

21 A.R Smith, Geometry and Imaging: Two Distinct Kinds of Graphics, to be published 1989; private

it was envisioned that the highest frequencies would dominate the applications However, because of the high-attenuation properties of materials, the lower frequency range of 10 to 100 MHz is extensively used Acoustic microscopy is recognized as a valuable tool for nondestructive inspection and materials characterization Acoustic microscopy comprises three different methods:

• Scanning laser acoustic microscopy (SLAM), which was first discussed in the literature in 1970 (Ref 1)

• C-mode scanning acoustic microscopy (C-SAM), which is the improved version of the C-scan instrumentation (Ref 2)

• Scanning acoustic microscopy (SAM), which was first discussed in the literature in 1974 (Ref 3)

Each of these methods has a specific range of utility, and most often the methods are noncompetitive with regard to applications That is, only one method will be best suited to a particular inspection problem

Acoustic microscopes are practical tools that have emerged from the laboratory to find useful applications within industry They can be applied to a broad range of problems that previously had no solutions, and they have been especially useful in solving problems with new high-technology materials and components not previously available The three acoustic microscope types can be as different from each other as are microradiography and electron microscopy This discussion should provide the potential user with an awareness of the techniques and their distinctions in order to maximize the opportunities for the successful use of acoustic microscopy

References

1 A Korpel, L.W Kessler, and P.R Palermo, Acoustic Microscope Operating at 100 MHz, Nature, Vol 232

(No 5306), 1970, p 110-111

2 Product Bulletin, Sonoscan, Inc

3 R.A Lemons and C.F Quate, Acoustic Microscope Scanning Version, Appl Phys Lett., Vol 24 (No 4),

1974, p 163-165

Acoustic Microscopy

Lawrence W Kessler, Sonoscan, Inc

Fundamentals of Acoustic Microscopy Methods

As a general comparison between the methods, the scanning laser acoustic microscope is primarily a transmission mode instrument that creates true real-time images of a sample throughout its entire thickness (reflection mode is sometimes employed) In operation, ultrasound is introduced to the bottom surface of the sample by a piezoelectric transducer, and the transmitted wave is detected on the top side by a rapidly scanning laser beam

The other two types of microscopes are primarily reflection mode instruments that use a transducer with an acoustic lens

to focus the wave at or below the sample surface The transducer is mechanically translated (scanned) across the sample

in a raster fashion to create the image The C-mode scanning acoustic microscope can image several millimeters or more into most samples and is ideal for analyzing at a specific depth Because of a very large top surface reflection from the sample, this type of microscope is not effective in the zone immediately below the surface unless the Rayleigh-wave mode to scan near-surface regions is used along with wide-aperture transducers The scanning acoustic microscope uses this Rayleigh wave mode and is designed for very high resolution images of the surface and near-surface regions of a sample Penetration depth is intrinsically limited, however, to only one wavelength of sound because of the geometry of the lens For example, at 1 GHz, the penetration limit is about 1 m (40 in.) The C-mode scanning acoustic microscope

is designed for moderate penetration into a sample, and transmission mode imaging is sometimes employed This instrument uses a pulse-echo transducer, and the specific depth of view can be electronically gated More detailed discussions of each acoustic microscopy technique follow

SLAM Operating Principles

A collimated plane wave of continuous-wave (CW) ultrasound at frequencies up to several hundred megahertz is produced by a piezoelectric transducer located beneath the sample, as illustrated in Fig 1 Because this ultrasound cannot travel through air (making it an excellent tool for crack, void, and disbond detection), a fluid couplant is used to bring the ultrasound to the sample Distilled water, spectrophotometric-grade alcohol, or other more inert fluids can be used, depending on user concerns for sample contamination When the ultrasound travels through the sample, the wave is affected by the homogeneity of the material Wherever there are anomalies, the ultrasound is differentially attenuated, and the resulting image reveals characteristic light and dark features, which correspond to the localized acoustic properties of the sample Multiple views can be made to determine the specific depth of a defect, as is performed by stereoscopy (Ref 4)

Fig 1 Simplified view of the methods for producing through transmission and noncollinear reflection mode

acoustic images with the scanning laser acoustic microscope

A laser beam is used as an ultrasound detector by means of sensing the infinitesimal displacements (rippling) at the surface of the part created by the ultrasound In typical samples that do not have polished, optically reflective surfaces, a mirrored plastic block, or coverslip, is placed in close proximity to the surface and is acoustically coupled with fluid The laser is focused onto the bottom surface of the coverslip, which has an acoustic pattern that corresponds to the sample surface By rapid sweeping of the laser beam, the scanning laser acoustic microscope images are produced in real time (that is, 30 pictures per second) and are displayed on a high-resolution video monitor In contrast to other less accurate uses of the term real time in industry today, the scanning laser acoustic microscope can be used to observe events as they occur for example, a crack propagating under an applied stress The images produced by SLAM are shadowgraph mode images of structure throughout the thickness of the sample This provides the distinct advantage of simultaneous viewing

of the entire thickness of the sample, as in x-ray radiography In situations where it is necessary to focus on one specific plane, holographic reconstruction of the SLAM data can be employed (Ref 5, 6)

Figure 2 shows a system block diagram for the scanning laser acoustic microscope In addition to an acoustic image on a CRT, an optical image is produced by means of the direct scanned laser illumination of the sample surface For this mode, the reflective coating on the coverslip is made semi-transparent The optical image serves as a reference view of the sample for the operator to consult for landmark information, artifacts, and positioning of the sample to known areas The SLAM acoustic images also provide useful and easily interpreted quantitative data about the sample For example, the brightness of the image corresponds to the acoustic transmission level By removing the sample and restoring the image brightness level with a calibrated electrical attenuator placed between the transducer and its electrical driver, precise insertion loss data can be obtained (Ref 7, 8) With the acoustic interference mode, the velocity of sound can be measured

in each area of the sample (Ref 9, 10) When these data are used to determine regionally localized acoustic attenuation loss, modulus of elasticity, and so on, the elastic microstructure can be well characterized

Fig 2 Schematic showing principal components of a scanning laser acoustic microscope The unit employs a

plane wave piezoelectric transducer to generate the ultrasound and a focused laser beam as a point source detector of the ultrasonic signal Acoustic images are produced at a rate of 30 images per second

The simplest geometries for SLAM imaging are flat plates or disks However, with proper fixturing, complex shapes and large samples can also be accommodated For example, tiny hybrid electronic components, large (254 × 254 mm, or 10 ×

10 in.) metal plates, aircraft turbine blades and ceramic engine cylinder liner tubes have been routinely examined by SLAM

C-SAM Operating Principles

The C-mode scanning acoustic microscope is primarily a pulse-echo (reflection-type) microscope that generates images

by mechanically scanning a transducer in a raster pattern over the sample A focused spot of ultrasound is generated by an acoustic lens assembly at frequencies typically ranging from 10 to 100 MHz A schematic diagram is shown in Fig 3

Fig 3 Schematic of the C-mode scanning acoustic microscope This instrument incorporates a reflection,

pulse-echo technique that employs a focused transducer lens to generate and receive the ultrasound signals beneath the surface of the sample

The ultrasound is brought to the sample by a coupling medium, usually water or an inert fluid The angle of the rays from the lens is generally kept small so that the incident ultrasound does not exceed the critical angle of refraction between the fluid coupling and the solid sample Note that the focal distance into the sample is shortened considerably by the liquid-solid refraction The transducer alternately acts as sender and receiver, being electronically switched between the transmit and receive modes A very short acoustic pulse enters the sample, and return echoes are produced at the sample surface and at specific interfaces within the part The return times are a function of the distance from the interface to the transducer An oscilloscope display of the echo pattern, known as an A-scan, clearly shows these levels and their time-distance relationships from the sample surface, as illustrated in Fig 4 This provides a basis for investigating anomalies at specific levels within a part An electronic gate selects information from a specific level to be imaged while it excludes all other echoes The gated echo brightness modulates a CRT that is synchronized with the transducer position

Fig 4 Signal/source interfaces and A-scan displays for typical sample (a) Simplified diagram showing pulses of

ultrasound being reflected at three interfaces: front surface, A; material interface, B; and rear interface, C Main bang is the background electrical noise produced by transducer excitation (b) Plot of amplitude versus time as transducer is switched between transmit and receive modes at each interface during a time span of under 1 s (c) Signal at interface B gated for a duration of 30 ns

Compared to older conventional C-scan instruments, which produce a black/white output on thermal paper when a signal exceeds an operator-selected threshold, the output of the C-mode scanning acoustic microscope is displayed in full gray scale, in which the gray level is proportional to the amplitude of the interface signal (gray-scale digitization is discussed

in the article "Machine Vision and Robotic Evaluation" in this Volume) The gray scale can be converted into false color, and as shown in Fig 5, the images can also be color coded with echo polarity information (Ref 11) That is, positive echoes, which arise from reflection from a higher-impedance interface, are displayed in a gray scale having one color scheme, while negative echoes, from reflections off of lower-impedance interfaces are displayed in a different color scheme This allows quantitative determination of the nature of the interface within the sample For example, the echo amplitude from a plastic-ceramic boundary is very similar to that from a plastic-airgap boundary, except that the echoes are 180° out of phase Thus, to determine whether or not an epoxy is bonded to a ceramic, echo amplitude analysis alone

is not sufficient The color-coded enhanced C-mode scanning acoustic microscope is further differentiated from conventional C-scan equipment by the speed of the scan Here, the transducer is positioned by a very fast mechanical

scanner that produces images in tens of seconds instead of tens of minutes for typical scan areas to cover the size of an integrated circuit

Fig 5 Schematic and block diagram of the C-mode scanning acoustic microscope The instrument employs a

very high speed mechanical scanner and an acoustic impedance polarity detector to produce high-resolution scan images

C-With regard to the depth zone within a sample that is accessible by C-SAM techniques, it is well known that the large echo from a liquid/solid interface (the top surface of the sample) masks the small echoes that may occur near the surface within the solid material This characteristic is known as the dead zone, and its size is usually of the order of a few wavelengths of sound or more Far below the surface, the maximum depth of penetration is determined by the attenuation losses in the sample and by the geometric refraction of the acoustic rays, which shorten the lens focus by the solid material Therefore, depending on the depth of interest within a sample, a proper transducer and lens must be used for optimum results

SAM Operating Principles

The scanning acoustic microscope is primarily a reflection-type microscope that generates very high resolution images of surface and near-surface features of a sample by mechanically scanning a transducer in a raster pattern over the sample

(Fig 6 and 7) In the normal mode, an image is generated from echo amplitude data over an x,y scanned field-of-view As

with SLAM, a transmission interference mode can be configured for velocity of sound measurements In contrast to SAM, a more highly focused spot of ultrasound is generated by a very wide angle acoustic lens assembly at frequencies typically ranging from 100 to 2000 MHz The angle of the sound rays is well beyond the critical cutoff angle, so that there

C-is essentially no wave propagation into the material There C-is a Rayleigh (surface) wave at the interface and an evanescent wave that reaches to about one wavelength depth below the surface As in the other techniques, the ultrasound is brought

to the sample by a coupling medium, usually water or an inert fluid The transducer alternately acts as sender and receiver, being electronically switched between the transmit and receive modes However, instead of a short pulse of acoustic energy, a long pulse of gated radio-frequency (RF) energy is used No range gating is possible, as in C-SAM, because of the basic design concept of the SAM system The returned acoustic signal level is determined by the elastic properties of the material at the near-surface zone The returned signal level modulates a CRT, which is synchronized with the transducer position In this way, images are produced in a raster scan on the CRT As with C-SAM, complete images are produced in about 10 s

Fig 6 Schematic of the scanning acoustic microscope lens used for interrogating the surface zone of a sample

Fig 7 Block diagram of a reflective-type SAM system that uses mechanical scanning of a highly focused

transducer to investigate the surface zone of a sample at high magnification

With the SAM technique operating at very high frequencies, it is possible to achieve resolution approaching that of a conventional optical microscope This technique is employed in much the same way as an optical microscope, with the important exception that the information obtained relates to the elastic properties of the material Even higher resolution than an optical microscope can be obtained by lowering the temperature of operation to near 0 K and using liquid helium

as a coupling fluid The wavelength in the liquid helium is very short compared to that of water, and submicron resolution can be obtained (Ref 12)

The SAM technique has also been found to be useful for characterizing the elastic properties of a sample over a microscopic-size area, which is determined by the focal-spot size of the transducer In this method, the reflected signal level is plotted as a function of the distance between the sample and the lens Because of the leaky surface waves generated by mode conversion at the liquid/solid interface as the sample is defocused toward the lens, an interference signal is produced between the mode converted waves and the direct interface reflection The curve obtained is known as

the V(z) curve; by analyzing the periodicity of the curve, the surface wave velocity can be determined Furthermore,

defocusing the lens enhances the contrast of surface features that do not otherwise appear in the acoustic image (Ref 13, 14) In addition, by using a cylindrical lens instead of a spherical lens, the anisotropy of materials can be uniquely characterized (Ref 15)

Comparison of Methods to Optimize Use of Techniques

Figure 8 illustrates the zones of application for all three types of acoustic microscopy techniques The differences are substantial with regard to the potential for visualizing features within a sample, and they should be carefully weighed before a particular method is selected Table 1 lists some of the major advantages and benefits of the techniques However, generalizations are sometimes difficult to make Proposed or laboratory-demonstrated solutions to some of the limitations of each technique may already exist Table 1 was prepared on the basis of instrumentation and techniques that are commercially available and therefore should be used only as a general guide

Table 1 Comparison of industrial acoustic microscopy techniques

General

description

Utilizes CW, plane wave ultrasonic illumination of sample and scanning focused laser beam detection of ultrasound;

simultaneous optical images and acoustic images are produced

SLAM produces images in real time, which is the fastest of all acoustic microscopy techniques

High-resolution focused-beam C-scan(a) Utilizes pulse-echo mode and has full gray-scale image output Images are produced by mechanically scanning the transducer over the sample area

Utilizes very highly focused acoustic lenses to image exterior surfaces by means of surface acoustic wave generation Images are produced by mechanically scanning the

transducer over the sample area SAM produces the highest resolution

of all acoustic microscopy techniques

Primary use Nondestructive testing and

Resolution Resolution limited to the

wavelength of ultrasound within the sample material

Resolution limited to the wavelength of ultrasound within the sample material, multiplied by a factor, typically 2-10, due

to the lens design

Resolution limited to the wavelength

of ultrasound within the coupling fluid at the surface of the sample

Imaging mode Through transmission

(primarily); off-axis reflection;

orthoscopic view of sample

Reflection (primarily); orthoscopic view

Image is produced at any selected depth within the sample, but is affected by wave propagation through all the levels prior to the focus location

Image is produced only at the sample surface, and the depth of the information extends into the material a distance of one

wavelength of sound

Ultrasound

mode

Continuous-wave and frequency-modulated ultrasound waves

Short pulses of ultrasound, less than a few cycles of RF in duration

Gated RF (or tone burst) containing many cycles (10-100) of RF at frequency selected

Ultrasound

signal timing

Not applicable due to CW Echoes are spread out in time, and one is

selected and electronically gated for desired image depth within sample

Gated at the surface of the sample where virtually all the ultrasound is reflected There are no subsurface echoes to select

Transducer

type

Plane wave transducer for sample illumination and focused laser beam for detection

Focused transducer used for transmit and receive mode The angle of the rays is less than the critical angles between the coupling fluid and the sample This is known as a low-numerical-aperture transducer

Focused transducer in which the geometric angle of the rays is much greater than the critical angles in order to excite surface modes This

is known as a aperture transducer

high-numerical-Image outputs Amplitude mode: Records level

of ultrasound transmission at

each x,y coordinate of the scan

Interference mode: Records velocity of sound variations within sample over the field-of- view at each frequency Frequency scan mode: Similar to amplitude mode except that the insonification frequency is swept over a range to eliminate speckle and other artifacts of coherent imaging

Optical mode: Laser scanned optical image produced in synchrony with the acoustic images

C-mode: Records echo amplitudes at each x,y coordinate of the scan; image output on CRT

A-scan: Oscilloscope display of the echo pattern as a function of time (distance

into sample) at each x,y coordinate This

can be used to measure the depth of a feature or the velocity of sound in the material The A-scan is used to determine the setting of the echo gate, which is critical to the composition and interpretation of the images

Normal mode: Records reflected

energy from surface at each x,y

position Image output on CRT

V(z), or acoustic material signature

graph, records the change in

reflected signal level at any x,y coordinate as the z position is varied

(Ref 12, 13, 14) This will characterize the material by means

of its surface acoustic wave velocity Interference mode: Records velocity

of sound variations within sample over the field-of-view at each frequency

Depth of

penetration

Penetration is limited by acoustic attenuation characteristic of sample

In addition to attenuation by the sample, penetration is limited by focal length of lens and geometric refraction of the rays, which causes shortening of the focus position below the surface There is also

a dead zone just under the surface due to the large-amplitude front-surface echo, which masks smaller signals occurring immediately thereafter This can be rectified with a high-numerical-aperture transducer

Limited to a distance of one wavelength of sound below the surface There is essentially no wave propagation into the sample

Imaging speed True real-time imaging: 30

frames/s; fastest of all acoustic microscopes

10 s to 30 min per frame; varies greatly among manufacturers

10 to 20 s/frame

New

developments

Holographic reconstruction of each plane through the depth

of the sample (Ref 5, 6)

Acoustic impedance polarity detector

to characterize the physical properties

of the echo producing interfaces (Ref 11)

Low-temperature liquid helium stages for extremely high resolution images (Ref 15)

(a) C-scan produces ultrasonic images by mechanically translating a pulsed transducer in an x,y plane above a sample while recording the echo

amplitude within a preset electronic time gate The transducer may be planar or focused The frequencies of operation are typically 1-10 MHz, and the data are usually displayed as a binary brightness level on a hard copy output unit, such as thermal paper A threshold level selected by the operator determines the transition between what amplitude of echo is displayed as a bright or dark image print

Fig 8 Simplified comparison of three acoustic microscopy techniques, particularly their zones of application

(crosshatched area) within a sample (a) SLAM (b) SAM (c) C-SAM

References cited in this section

4 L.W Kessler and D.E Yuhas, Acoustic Microscopy 1979, Proc of IEEE, Vol 67 (No 4), April 1979, p

526-536

5 Z.C Lin, H Lee, G Wade, M.G Oravecz, and L.W Kessler, Holographic Image Reconstruction in

Scanning Laser Acoustic Microscopy, Trans IEEE, Vol UFFC-34 (No 3), May 1987, p 293-300

6 B.Y Yu, M.G Oravecz, and L.W Kessler, "Multimedia Holographic Image Reconstruction in a Scanning Laser Acoustic Microscope," Paper presented at the 16th International Symposium on Acoustical Imaging

(Chicago, IL), Sonoscan, Inc., June 1987; L.W Kessler, Ed., Acoustical Imaging, Vol 16, Plenum Press,

1988, p 535-542

7 L.W Kessler, VHF Ultrasonic Attenuation in Mammalian Tissue, Acoust Soc Am., Vol 53 (No 6), 1973, p

1759-1760

8 M.G Oravecz, Quantitative Scanning Laser Acoustic Microscopy: Attenuation, J Phys (Orsay), Vol 46,

Conf C10, Supplement 12, Dec 1985, p 751-754

9 S.A Goss and W.D O'Brien, Jr., Direct Ultrasonic Velocity Measurements of Mammalian Collagen

Threads, Acoust Soc Am., Vol 65 (No 2), 1979, p 507-511

10 M.G Oravecz and S Lees, Acoustic Spectral Interferometry: A New Method for Sonic Velocity

Determination, in Acoustical Imaging, Vol 13, M Kaveh, R.K Mueller, and T.F Greenleaf, Ed., Plenum

Press, 1984, p 397-408

11 F.J Cichanski, Method and System for Dual Phase Scanning Acoustic Microscopy, Patent Pending

12 J.S Foster and D Rugar, Low-Temperature Acoustic Microscopy, Trans IEEE, Vol SU-32, 1985, p

139-151

13 K.K Liang, G.S Kino, and B.T Khuri-Yakub, Material Characterization by the Inversion of V(z), Trans IEEE, Vol SU-32, 1985, p 213-224

14 R.D Weglein, Acoustic Micro-Metrology, Trans IEEE, Vol SU-32, 1985, p 225-234

15 J Kushibiki and N Chubachi, Material Characterization by Line-Focus-Beam Acoustic Microscope, Trans IEEE, Vol SU-32, 1985, p 189-212

Acoustic Microscopy

Lawrence W Kessler, Sonoscan, Inc

It is difficult to document concisely the very broad range of applications for acoustic microscopy, but a few generalizations can be made that follow the examples of conventional ultrasonic nondestructive testing (see the articles

"Ultrasonic Inspection" and "Adhesive-Bonded Joints" in this Volume) Acoustic microscopy is compatible with most metals, ceramics, glasses, polymers, and composites (made from combinations of the above materials) The compatibility

of a material is ultimately limited by ultrasound attenuation caused by scattering, absorption, or internal reflection In metals, the grain structure causes scattering losses; and in ceramics, the porosity may cause losses The magnitude of these effects generally increases with ultrasound frequency, and the dependence is monotonic

Figure 9 shows a general guide to acoustic microscopy applications with respect to imaging The quantitative aspects have not yet found widespread industrial acceptance, although they are extremely important and form the basis for materials characterization The techniques of SLAM, C-SAM, and SAM all produce quantitative data in addition to images Acoustic microscopy methods are compared below with a typical C-scan ultrasound method in terms of frequency employed:

Method Frequency range, MHz

Fig 9 Comparison of acoustic microscopy applications with C-scan applications, based on transducer frequency

and wavelength

The most popular application of SLAM and C-SAM is the nondestructive evaluation of bonding, delamination, and cracks in materials These instruments are often used for process and quality control, although a significant percentage of the devices are placed in analytical and failure analysis laboratories The most popular application of SAM utilizes its very high magnification mode and is employed as a counterpart to conventional optical and electron microscopy, that is,

to see fine detail at and near surfaces The scanning acoustic microscope, like the other acoustic microscopy methods, produces image contrast, which is a function of the elastic properties of a material, where other nonacoustic techniques may not

Composite Materials

Composite materials represent an exciting challenge for the materials scientist and for nondestructive testing With the combination of materials having different properties and with manufactured anisotropy, acoustic microscopy can clearly define the relevant property distribution of materials at the microscopic level The examples shown in this section are polymer materials reinforced with fibers Metal-matrix composites and ceramic-matrix composites can be similarly studied

In general, the combinations of materials having different mechanical properties result in interfaces that cause scattering

of ultrasound and differential attenuation within the field-of-view This can be important in determining the population density shifts of fibers within a sample

SLAM Images. Acoustic microscopy can be used to differentiate fibers that are bonded well to the matrix from fibers that are separated from the matrix Excessive stress, for example, would cause such a separation As an example of this, Fig 10 shows two nominally identical tensile-test bars made of carbon fiber reinforced plastic (CFRP) One of the bars has been stressed to a level that produced a 1.5% strain The other sample has not been stressed Figures 11(a) and 11(b) compare SLAM images of these samples at 100 MHz The lighter image, Fig 11(a), shows texturing that follows the fiber direction Figure 11(b) shows the much darker, attenuating characteristics of the stressed sample The excess attenuation

is due to the separation of the fiber from the matrix

Fig 10 Photograph of two CFRP tensile-test bars one unstressed and one stressed The stressed bar was

subjected to a force that yielded a 1.5% strain

Fig 11 100-MHz SLAM acoustic micrographs of the tensile bar samples shown in Fig 10 (a) In the unstressed

bar, the texture corresponds to fiber population shifts and small areas of disbond (b) In the stressed bar that was pulled to a 1.5% strain level, there is no visible evidence of fracture Field of view: both 3 × 2.25 mm However, the increased acoustic attenuation (dark zones) present in (b) indicates stress damage to the

material

Figure 11 in the article "Use of Color for NDE" in this Volume shows a 30-MHz transmission SLAM image of a Kevlar fiber-reinforced plastic that has been cut perpendicular to the fibers, thus producing extensive delamination (red) and cracks along the axis of the sample Defects anywhere throughout the thickness will block the ultrasound transmission

Figure 12 in this article shows a curved CFRP component This sample is more difficult to image than the tensile-test bars because it has a complex shape; in addition, it has fibers oriented in a variety of different directions for directional strength

Fig 12 Complex-shaped CFRP component The fibers are arranged to impart directional strength to certain

critical areas of the sample

In Fig 13, a 30-MHz SLAM transmission image, a transition is seen between different fiber orientations in the sample; Fig 14 in the article "Use of Color for NDE" in this Volume shows a large anomaly that is located in the middle of the curved portion Scanning laser acoustic microscopy can be used to image complex-shape samples even though the curvature may cause some restriction of the field-of-view due to critical angle effects and lenslike action by the sample

Fig 13 30-MHz SLAM acoustic micrograph of the sample shown in Fig 12 The left portion of the micrograph

shows a more complex fiber network than the area on the right A color image of the curved CFRP component is

shown in Fig 14 in the article "Use of Color for NDE" in this Volume Field of view: 14 × 10.5 mm

C-SAM Image. Figure 14 shows a 50-MHz reflection image in the C-SAM image of a CFRP tensile-test bar similar to that shown in Fig 10 The acoustic lens is focused near the surface of the sample, and the electronic gate was set to receive a portion of the backscattered signal Because the sample is constructed with fibers distributed throughout the volume, acoustic energy is scattered from all depths, and distinct, time-separated echoes were not generated When the transducer was focused deep into the sample, there was less definition of the fibers in the acoustic image, similar to what

is seen in the SLAM image

Fig 14 50-MHz C-SAM reflection mode micrograph of a CFRP test sample The ultrasound was focused near the

top surface of the sample Field of view: 19 × 14 mm

Ceramic Materials

Ceramic materials are used in a variety of applications Some are used in the electronics industry as substrates for delicate hybrid circuits In structural applications, ceramics are used where high temperature and light weight are important Silicon nitride, silicon carbide, and zirconia are receiving much attention for future engine applications However, because of the inherent brittleness of ceramic materials, small defects are very critical to the structural integrity of the materials The successful use of these materials necessitates careful nondestructive screening of the samples

Aluminum Oxide. Figure 15 shows an optical picture of an aluminum oxide panel with laser-machined holes This sample is an electronics-grade material that is 99.5% pure and has very low porosity When the ceramic powder is first compressed in the green state, opportunities arise for segregated low-density areas to occur After the sintering operation, these areas are usually found to be very porous If one of these areas happens to coincide with the site of laser machining, the stresses that occur can cause the material to crack Upon visual examination, it may be very difficult to detect fine cracks, even if they come to the surface Dye penetrants can be used to increase the visual contrast Unfortunately, in many applications, dyes are considered to be contaminants and therefore cannot be used for nondestructive testing Because of the discontinuity in material property, a crack will reflect acoustic waves and produce high-contrast images

Fig 15 Aluminum oxide panel having laser-machined holes and slots with fine cracks around the perimeter and

the circumference of the openings

Figure 16 shows a 100-MHz SLAM acoustic micrograph of a ceramic sample with a crack that can be seen as a dark line originating from one of the holes Surrounding the area of the crack are several small, dark patches, which arise from localized increases in porosity In the acoustic image, the pores may not be visible individually if they are smaller than the wavelength of sound In this case, the pores are only a few microns in size, and the wavelength is about 25 m (0.001 in.) The porous areas are detectable by virtue of excess ultrasound scattering, which causes the differential attenuation Correlative analyses have shown that pores in the 1 m (40 in.) size range cause detectable attenuation increases (Fig 16) However, the presence of a single 1 m (40 in.) pore would be difficult to detect unless the frequency of the ultrasound was increased to 1 GHz or more

Fig 16 100-MHz SLAM acoustic micrograph of an alumina panel section that contains a hole showing a crack

with very high contrast A digitally enhanced image of this alumina panel is also shown in Fig 15 in the article

"Use of Color for NDE" in this Volume Field of view: 3 × 2.25 mm

It is significant to note that attenuation changes in ceramics correlate well with variations in strength (Ref 16) Fig 15 in the article "Use of Color for NDE" in this Volume shows a digitally enhanced pseudocolor image of a ceramic sample that is useful for quantitative analysis of the gray scale and for identifying precisely the acoustic signal levels without relying on operator interpretation of the gray scale on the CRT screen

Example 1: Use of C-SAM to Detect Internal Porosity Defects in an Alumina Ceramic Disk

Acoustic microscopy is a powerful tool for nondestructively evaluating ceramic materials and displaying internal defects and density gradients such as porosity An acoustic microscope scanning at 50 MHz with an f/1 lens on the transducer was used to evaluate a 6.4 mm (0.25 in.) thick aluminum oxide ceramic disk No surface preparation of the sample was required prior to scanning

The acoustic microscope, with a 25 m (0.001 in.) acoustic resolution, scanned a 12.7 × 12.7 mm (0.50 × 0.50 in.) area of the ceramic disk A pulse-echo technique (C-SAM) displayed internal reflections The black areas (arrows, Fig 17), which were detected as having the highest-amplitude reflection, indicate areas of porosity of the order of 10 to 20 m (400 to 800 in.) in diameter

Fig 17 A portion of the 160 mm2 (0.25 in 2 ) area of an alumina ceramic disk scanned by an acoustic microscope showing the presence of porosity in the disk (arrows) Courtesy of G.H Thomas, Sandia National Laboratories

Example 2: Analysis of Alumina Ceramic Disks Supplied by a Variety of Manufacturers and Subjected to SLAM, C-SAM, and SAM Evaluation

Disks of alumina were obtained from various manufacturers as part of a study on the effects of sintering temperature changes on mechanical strength and ultrasonic properties The disks were approximately 25 mm (1 in.) diameter and 6

mm ( in.) thick Figure 18 shows a through-transmission 10-MHz SLAM image of an alumina disk Higher SLAM frequencies could not be used, because of excessive attenuation This is unusual for ceramic materials unless they are very porous or otherwise defective Most of the area of this sample is nontransmissive (dark), which indicates a large internal defect A subsequent cross section of this part, shown in Fig 19, reveals a large crack that correlated to the indication in the SLAM image The crack is not parallel to the surface; this was not known prior to cross sectioning

Fig 18 Low-frequency 10-MHz SLAM image of a 25 mm (1 in.) diam alumina test disk The disk is very

attenuating to ultrasound because of internal defects that cover about 75% of the area (dark zones) Field of view: 35 × 26 mm

Fig 19 Cross sectioning of the alumina test disk shown in Fig 18 reveals a large crack that correlates with the

area of low acoustic transmission This confirms the presence of an internal defect

Figures 16(a) and 16(b) in the article "Use of Color for NDE" in this Volume are 15-MHz reflection C-SAM images of the same part focused to different depths The radical changes in echo pattern at different depth locations in the disk result

in widely different images This is due to the nonparallel nature of the crack In these figures, the darkest features correspond to the greatest echo amplitude The C-mode scanning acoustic microscope clearly shows anomalies in this part, and by sequential scanning at a variety of depths, an overall diagnosis of the part can be assembled

Figure 20 shows a SAM image produced at 180 MHz in which the lens was focused slightly below the surface (20 m, or

800 in., in water) to highlight subsurface information The predominant features in Fig 20 are surface scratches, which may also be associated with near-surface cracks The grain structure and porosity of this sample are finer than can be visualized at 180 MHz

Fig 20 SAM image at 180 MHz of the sample shown in Fig 18 and 19 revealing features of the ceramic at and

near the surface Color images of this disk are shown in Figures 16(a) and 16(b) in the article "Use of Color for NDE" in this Volume Field of view: 1 × 1 mm

Another alumina sample produced under different conditions was found to be much more transparent acoustically Figure

21 shows a 30-MHz SLAM image of a typical area of this disk The higher frequencies are associated with higher magnifications and therefore smaller fields-of-view The ceramic appears fairly homogeneous at this level of magnification Figure 22, a 100-MHz SLAM image of the sample in Fig 21, shows that some textural inhomogeneities are beginning to appear The texture may be due to nonuniform segregation of porosity in the sample and throughout its thickness Figure 23, a 50-MHz C-SAM image of the disk, shows large pores (white) about 1 mm (0.04 in.) below the surface Figure 24 shows a 180-MHz SAM image made under conditions identical to Fig 20 The fine texture at the surface of this sample is due to porosity The differences between the two samples are clearly evident acoustically

Fig 21 SLAM images at 30 MHz of an alumina test disk similar in size to that shown in Fig 18 This sample

was quite transparent to the ultrasound, as evidenced by the bright, relatively uniform appearance of the acoustic image Field of view: 14 × 10.5 mm

Fig 22 SLAM 100-MHz transmission acoustic image of the sample shown in Fig 21 At this higher frequency,

textured variations in the sample are evident that may be due to micro (subresolution) porosity segregations, which cause differential absorption Field of view: 3.5 × 2.6 mm

Fig 23 C-SAM reflection mode image at 50 MHz made by setting the gate and focus to about 1 mm (0.04 in.)

below the surface The white circular spots correspond to individual pores located at this depth Field of view:

30 × 30 mm

Fig 24 SAM surface mode image at 180 MHz made under conditions identical to Fig 20 In this image, the fine

texture corresponds to porosity of the sample Note the sharp contrast between the microstructure of this sample and that of Fig 20 Field of view: 1 × 1 mm

Metals

In typical optical microscopy and metallography, it is necessary to polish and etch a sample to reveal the microstructural pattern With SAM, this may not be necessary, as evidenced by the above As one further illustration of SAM, Fig 25 shows a 400-MHz image, focused 23 m (920 in.) below the surface, of a manganese-zinc ferrite material The different phases of this important material can be visualized without the use of etchants For certain metallic samples, that is, those with smooth, polished surfaces, SAM can be used for nondestructive testing as well as for metallographic analysis

Fig 25 SAM surface mode image at 400 MHz of a manganese-zinc ferrite sample that was polished

metallurgically but not chemically etched The elastic property differences between the various phases of this material are responsible for the contrast shown in this image Courtesy of Honda Electronics Company, Ltd

Figure 26 shows the metallographic structure of low-carbon steel; the specimen was polished but not etched Although the images are similar to optical displays, the acoustic microscope is sensitive to acoustic properties and will generate images

of surface and subsurface structure The low-carbon steel was scanned at 1.3 GHz over an area measuring 100 × 100 m (0.004 × 0.004 in.) A high-resolution scanning acoustic microscope was used to generate this image from variations in the acoustic properties of the steel sample Details of the grain structure, grain boundaries, and impurities in the specimen are visible in Fig 26 The darker areas indicate contaminants trapped in the metal