Insight Vol 49 No 12 December 2007 1

T Saravanan, S Bagavathiappan, J Philip, T Jayakumar and Baldev RajPaper submitted 28 February 2007

Accepted 1 May 2007

1. Introduction

Radiography is a well-established non-destructive testing (NDT) method for obtaining information about discontinuities throughout the volume of a specimen. It is a versatile technique for determining critical gaps and clearances between the fuel pellets and clad of a fuel pin in nuclear applications[1-3]. The resolution of the X-ray detecting medium is a limiting factor for the estimation of defects[4-8]. The radiography resolution is affected by the X-ray focal spot size, scattering from the object, film graininess/detector

quantum noise and orientation of the defect. These factors exert considerable influence on the quantification and characterisation of the defect geometry. Segal et al[9] have pointed out that the problem of gap width measurements is connected with the problem of edge detection. It has been pointed out that the representation density profile of the gap is incorrect if the width of the gap to be measured is less than image blurring functions such as geometrical unsharpness and film granularity[10]. Hence, estimating the gap width from the full width at half maximum (FWHM) of the intensity profile across the gap can also be incorrect.

Most of the past studies reveal that the X-ray beam angle with respect to the object position is a critical factor that leads to an erroneous measurement of gap width, because the oblique beam angle results in variations in the geometrical enlargement of the specimens. When radiography was carried out on irregular thickness specimens such as castings and particularly those in which the edges of the specimen come within the area of the film/detector, scattered radiation is predominant and makes quantification of defects unreliable[11]. In comparison to a plate geometry, cylindrical rods exhibit poorer flaw sensitivity by a factor of 2-3. If the edge of the specimen is not close to the X-ray film, then undercutting of the resultant image would come into the picture and obscure the edge and the flaws near the edge of the specimen. In Neutron Radiography (NR) experiments, a calibrated fuel pin was used as an image quality indicator (IQI), and the gap between clad and pellets is found to be less than 50 microns[3].

Recently, an image processing approach has been adopted for improved detection of volumetric defects in electrochemical hydrogen sensors[12]. As indicated in the literature[13], measurement of the dimensions of nuclear fuel pins from neutron radiographs consists of measuring the distances between locally occurring maxima or minima in the optical film density on the radiographs.

In mixed uranium-plutonium oxide (MOX) fuel pins, the actual radial gap between pellet and clad tube can vary from 90 to 180 microns depending on the fuel and cladding fabrication conditions. To establish a radiography procedure to measure the radial gap in the above range, a calibration study was carried out with different radial gaps. To create a radial gap of 100 microns, a stainless steel (SS) cylindrical rod of diameter 11.96 ± 0.02 mm was inserted in to an aluminium hollow pipe with an outer diameter (OD) of 25.04 ± 0.02 mm. To mimic the measurement of pellet-to-pellet axial gap (in the range of 100-500 microns) in MOX fuel pins, axial gap measurements with plates of copper (Cu) and SS with known dimensions are placed in contact and at different known gaps. From the radiography images, it is observed that the accurate measurement of radial and axial gaps by grey-level profiling is not possible due to unsharpness factors. Hence, an image processing based approach for axial and radial gap measurements is developed. After applying the image enhancement tools on the radiographic images of calibration samples for precise determination of the radial and axial gaps, this methodology has been successfully adopted for the estimation of dimensional measurements of MOX fuel pins. The results showed that, by using this procedure, it is possible to measure gaps with good accuracy that was not possible before.

RADIOGRAPHY

Improved estimation of radial and axial gap of fuel pins from radiography images using image processing tools

We report a new methodology for the precise estimation of radial gap from radiography images using image sharpening tools. The image sharpening is done by differentiation of pixels over a region, using a gradient approach. The gradient approach assumes relatively large gradient values for prominent edges in an image, small values for smooth regions and zero for regions that have constant grey values. Applying a first-order derivative to an image demarcates the boundaries and enhances the visibility of small steps and other finer details. This new approach facilitates enhanced detectability of radial gaps. Using this approach, radial gaps of 100 microns and above have been measured, which was not possible without employing image enhancement tools. The procedure has been successfully applied to the estimation of pellet-to-clad gap and pellet-to-pellet axial gap in mixed uranium-plutonium oxide ((U, Pu) O2) fuel pins. The minimum radial gap (pellet-to-clad gap) measured using this approach is 64 microns. It has been found that the image processing tools can substantially reduce the unsharpness of the image due to scattering components and detector characteristics. This methodology is considered to be useful for the estimation of internal dimensions with better accuracy in assembled components using X-ray radiography images.

Dr Baldev Raj is the Distinguished Scientist and Director of Indira Gandhi Centre for Atomic Research, Kalpakkam. He is a Hon Member of ICNDT, Hon Fellow of the Indian Society for NDT, Hon Fellow of The British Institute of NDT and Founder Member of the Board of Directors, World Federation of NDE Centres, USA.

Dr T Jayakumar is the Head, Non-Destructive Evaluation Division, Indira Gandhi Centre for Atomic Research, Kalpakkam.

Corresponding author: Dr John Philip is the Head, SMART Section, Non-Destructive Evaluation Division, Inspection Technology Group, Indira Gandhi Centre for Atomic Research, Kalpakkam – 603 102, Tamil Nadu, India. Tel: +91-044-27480232; Fax: +91-044-27480356; E-mail: philip@igcar.gov.in

Dr T Saravanan is a Scientific Officer in the Non-Destructive Evaluation Division, Indira Gandhi Centre for Atomic Research, Kalpakkam.

Shri S Bagavathiappan is a Scientific Assistant in Non-Destructive Evaluation Division, Indira Gandhi Centre for Atomic Research, Kalpakkam.

2 Insight Vol 49 No 12 December 2007

2. Experimental

Conventional film radiography of various specimens was carried out using a 450 kV Balteau constant potential X-ray machine which had a dual focal spot size of 1.2 × 1.2 mm and 3 × 3 mm. Radiography exposure parameters were suitably adjusted for the cylindrical and plate geometry specimens to obtain a radiography density of around 2.0 in the region of interest (ROI). To have a better control on the radiography sensitivity, a low energy, coupled with fine grain, slow-speed Kodak DR5 film, was used. 3 mm lead sheet was used at regions other than the region of interest, for masking to control the scattering. Exposed films were processed manually under standard conditions. Table 1 shows the typical radiography parameters employed for the experiments. All the radiography films were digitised by a Kodak LS 85 laser X-ray film scanner with a scanning resolution of 50 microns with 12-bit pixel depth.

3. Results and discussion

3.1 Estimation of radial gap in assembled components

In order to evolve a suitable methodology for radial gap measurements, various calibration samples have been used in the experiments. Figure 1 (inset) shows the radiography image of a SS cylindrical rod of 11.96 ± 0.02 mm diameter. Due to the optimised

radiography parameters, the required contrast was achieved. Since suitable lead masking was provided to reduce the backscattering effect, the edges of the specimen were seen clearly.

Figure 1 shows the grey-level profile across the SS rod (along the line indicated in the radiography image). For calibration, the length of the cylindrical rod was chosen as a reference. From the change in grey values corresponding to the inner rod portion, the estimated diameter of the rod was 12.05 mm against the actual diameter of 11.96 ± 0.02 mm. The error here was + 110 microns. For diameter measurements, the grey-level profile was taken at five different locations and the average value was taken. The above results suggest that the error in the measurement was less than ± 1%. The higher scanning resolution, contrast and brightness control etc. have facilitated this accuracy.

Figure 2 (right) shows the digitised radiography image of a hollow aluminium (Al) pipe with OD of 25.04 ± 0.02 mm. The hollow portion had a diameter of 12.16 ± 0.02 mm. From the radiography image, the hollow portion of the pipe was seen clearly with good image contrast.

Figure 2 (left) shows the grey-level profile across the Al pipe (along the line on the radiography image). From the profile, the internal diameter of the pipe (hollow region) was estimated as 12.25 mm against the actual dimension of 12.16 ± 0.02 mm. To improve the image contrast for the radiography image, the contrast and brightness values were suitably adjusted. From the profile, the OD of the pipe was measured as 25.10 mm against the actual OD of 25.04 ± 0.02 mm. From this estimation, it is inferred that the error in the measurement was less than ± 1%.

Figure 3 (right) shows the radiography image of a cylindrical SS rod of diameter 11.96 ± 0.02 mm inserted inside a hollow Al pipe of I.D 12.16 ± 0.02mm. It is observed that the image of the outer pipe is blurred and the contrast is poor, due to the higher X-ray scattered photons emanated from the inner SS rod, and also due to the density (ρ) difference between these two materials. From a number of trials, it is observed that higher voltage and exposure (kV, mA min) can result in an optical density higher than 4.0 and hence the image is not discernible. If the material is underexposed,

Table 1. Radiography exposure parameters

Parameters

X-ray unit Balteau NDT 450 kV

Voltage 20-450 kV

Current 30 mA max

Focal spot size(Dual focal spot)

1.2×1.2 mm, 3.0×3.0 mm

Cooling Oil/air

Parameters applied for

Radial gapmeasurement

Axial gapmeasurement

Voltage applied 135/150/160 kV (Outer pipe/inner cylinder/total set-up)

135 kV

Exposure 28/50/50 mA min 64 mA min

Radiography density 2.0-2.5 2.0-2.5

Processing Manual, standard Manual, standard

Detector used Fine grain, slow speed Kodak DR5

Fine grain, slow speed Kodak DR5

Intensifying screen 0.05 mm front and 0.10 mm back Pb screen

0.05 mm front and 0.10 mm back Pb screen

Source-to-film distance (SFD)

1000 mm 1000 mm

Figure 1. Grey-level profile of a cylindrical rod of 11.96 mm diameter and the radiography image (inset)

Figure 2. Grey-level profile of a hollow pipe of diameter 25.04 mm (left) and the radiography image (right)

Figure 3. Grey-level profile of SS rod inside an Al pipe (left) and the radiography image (right)

Insight Vol 49 No 12 December 2007 �

the inner SS rod is not completely penetrated by the X-rays. Figure 3 (right) shows the radiography image under optimum radiography exposure conditions where the image contrast is poor.

In the present experiment, due to the presence of the edges of the inner and outer cylindrical pipes, the effect of undercutting of the X-ray beam is significant and causes image spread at the edges leading to poor detectability of the radial gap between the SS rod and the Al pipe.

Figure 3 (left) shows the grey-level profile for the line drawn across the radiography image (right). No sharp change in intensity value is seen in the profile for the actual radial gap between the SS rod and the Al pipe which is about 100 microns. With the total unsharpness of 125 microns and X-ray scatter from the specimens, detection of the 100 micron radial gap is not possible without image processing.

3.2 Image processing approach to detect the edges of the specimen

Local or neighbourhood operator, ie equalisation of image contrast, produces an increase in local contrast at boundaries. These operators have the effect of making edges easier to view and making the image appear sharper[14]. The approaches used for edge enhancement are less sensitive to the overall brightness level and feature size. A symmetric kernel that does not have exclusively positive values is the 5 × 5 Laplacian operator:

-1 -1 -1 -1 -1

-1 -1 -1 -1 -1

-1 -1 24 -1 -1

-1 -1 -1 -1 -1

-1 -1 -1 -1 -1

This kernel subtracts the brightness values of each of the neighbouring pixels from that of the centre pixel. Hence, in an image that has a uniform brightness or uniform gradient in brightness level, the resultant grey value is reduced to zero. When a discontinuity is present within an image (for example a point, line or edge), the result of the Laplacian transformation is a non-zero value. This value is fixed by the location of the centre point in the mask with respect to the edge.

The Laplacian operator is an approximation to the second-order derivative of the brightness value in the x and y directions, and is defined as:

L f x yf

x

f

y,( ) = ∂

∂+ ∂

∂

2

2

2

2 ...........................(1)

It is invariant to rotation and hence this operation is invariant to the direction of the discontinuity. Figure 4 (right) shows the result of the Laplacian operation on the radiography image of the SS rod inside the Al pipe (Figure 3). From this image, the edge is sharpened locally by enhancing the contrast while retaining the overall grey scale variation in the image. While the Laplacian responded to the edges of the SS rod well, it has not shown the same response to the radial gap. The Laplacian can respond more strongly to detector characteristics, such as noise, than to a step, since the noise is present in the image as points with varying brightness values[14]. These characteristics are represented in the grey-level profile (Figure 4). The Laplacian operator, a second-order differentiation, shows edges as extrema while reducing the signal-to-noise ratio[15]. From the grey-level profile, the detector noise (circled) and the edges of the SS rod (distance between extreme minima in grey-value) are seen clearly. From the distance between the extrema in the profile, the diameter of the SS rod is measured as 12.16 mm against the actual value of 11.96 ± 0.02 mm. From the result, it is clear that the Laplacian gives the edges as a step in the brightness values.

To detect a measurable gap with and without image enhancement, a radial gap of 150 microns was created, which was higher than the total unsharpness (125 microns). Here, a 12 ± 0.02 mm SS rod was inserted into a hollow Al pipe with OD of 24.91 mm. The diameter of the hollow portion was 12.30 ± 0.02 mm. Figure 5 (right) shows the radiography image of the inserted SS rod inside the hollow Al pipe. From this image, it is observed that the outer tube and inner rod are seen with poor image contrast. Here, the 150 microns radial gap was not distinguishable. This is attributed to the effect of the total unsharpness (125 microns), undercutting, and scattering from the SS and Al objects.

Figure 5 (left) shows the grey-level profile for the line drawn on the radiography image. No sharp changes in the intensity values can be seen corresponding to the radial gap regions. After applying the Laplacian kernel, the result was not different from the above. Then, in the above specimen, an EDM notch with dimensions of 1 mm width and 0.1 mm depth was made on one side of the SS rod so as to make a radial gap of 250 microns on one side while the other side retained the 150 micron radial gap with the Al pipe. The radiography image of the specimen with the EDM notch is shown in Figure 6 (right). From the image, the notch is seen clearly (circled) along with the inner rod and outer pipe. Therefore, a radial gap of 250 microns or more could be detected, using the experimental condition employed.

Figure 6 (left) shows the grey-level profile for the line drawn across the notch portion in the image. From the profile, it is seen that this notch portion has not been represented distinctly but with a small hump (circled). The reason for this small hump is that the notch depth is less than 2 pixels in size (100 microns) in the image in comparison to the 12 mm diameter (more than 200 pixels) of the rod. To estimate the notch dimensions accurately, the Laplacian operator was applied over the radiography image (Figure 6).

Figure 7 (right) shows the Laplacian enhanced radiography image of Figure 6 (right), where the edges of the inner rod and the

Figure 4. Grey-level profile of SS rod inside Al pipe after applying Laplacian operator (left) and the radiography image (right)

Figure 5. Grey-level profile of SS rod in an Al pipe (left) and the radiography image for 150 microns radial gap (right)

4 Insight Vol 49 No 12 December 2007

notch portion (circled) are seen very clearly. To estimate the notch depth, the diameter of the inner rod, with and without the notch, was measured from the pixel positions corresponding to grey level changes. From the distance between the extreme minima in grey values, the diameter of the rod in the notch location was measured as 12.10 mm whereas it was 12.19 mm at other locations. A difference of 90 microns was observed that was in good agreement with the actual notch depth of 100 microns. In Figure 7, due to the Laplacian transformation, the artefacts in the radiography image are also clearly seen.

3.3 Role of image sharpening by derivative method for radial gap measurements

Since the above discussed approach did not yield the desired result for the measurement of minimum gap, image sharpening by a derivative-based approach was attempted in order to detect the radial gap with better accuracy. These operators are usually performed on those image regions or ordered image point patterns whose spectrum contains mostly higher spatial frequencies. Unlike low-pass smoothing filters (Gaussian, median), the image sharpening operation can result in steeper grey value transitions than the original image without any smoothing effect[16].

The image sharpening techniques are primarily used as enhancement tools for highlighting the edges in an image[17]. Edge

enhancement operators filter out undesired information, but retain the important morphological features of the radiography image[18]. Unlike the Laplacian filter, the first-order derivative based image sharpening approach demarcates the boundaries and enhances the visibility of small steps and other finer details of the image. Sharpening is made by differentiation of pixels over a region. The most commonly used method of differentiation in the image processing applications is by gradient. For a function f(x, y), the gradient of f at co-ordinates (x, y) is defined as the vector:

G f x y

f

xf

y

,( )

∂∂∂∂

= ...............................(2)

The vector G [f(x, y)] points in the direction of the maximum rate of increase of the function f(x, y) and the magnitude of G [f(x, y)], denoted by G[f(x, y)] is given by:

G f x y mag Gf

x

f

y,( ) = = ∂

∂

+ ∂

∂

2 221

2

..........(3)

which equals the maximum rate of increase of f(x, y) per unit distance in the direction of G:

G f x y f x y f x y f x y f x y, , , , ,( ) = ( ) − + +( ) + +( ) −1 1 1 ++( )1 ..(4)

The gradient assumes relatively large values for prominent edges in an image, small values for regions that are smooth, and zero for regions that have a constant grey value. It is understood that the magnitude of the first derivative can be used to detect the presence of an edge[15]. For a 100 micron radial gap, the image sharpening tool was applied over the image and the sharpened radiograph is shown in Figure 8 (right). Figure 8 (left) shows a sharp intensity change across the radial gap region between the inner and outer pipes. In the grey-level profile, sharp changes in grey values corresponding to the radial gap of 100 microns were observed. From this profile, the radial gap on both sides was measured as 130 microns against the actual gap of 100 microns. This variation could be due to the large size of the pixel (65 microns/pixel).

Figure 9 shows the radiography image after applying the first-order image sharpening operator on Figure 6. From Figure 9, it is observed that both the notch and the radial gap are clearly visible. Figure 10 shows the corresponding grey-level profile across the notch on Figure 9. In the profile, two sharp peaks are observed due to a sharp grey-level change associated with a radial gap of 250 microns on one side and 150 microns on the other side. From the pixel positions corresponding to the changes in grey values, the measured radial gap on the top side was 300 microns against the actual radial gap of 250 microns, whereas on the bottom side, it was 193 microns against 150 microns.

Table 2 shows the results of the radial gap measurements made on calibration samples by the image processing technique. From this Table, it is clear that the image sharpening based approach yields

Figure 6. Grey-level profile across the notch (left) and the radiography image (right). The notch depth is 100 microns

Figure 7. Grey-level profile (left) and Laplacian enhanced radiography image (right). The actual radial gaps on the two sides are 150 and 250 microns

Figure 8. Grey-level profile after image sharpening (left) and the radiography image of an object with 100 micron radial gap (right)

Figure 9. Image sharpened radiography image of a notch of 100 microns depth on a SS rod. The radial gap is 150 microns

Insight Vol 49 No 12 December 2007 �

MONDO, a three-dimensional co-ordinate measuring equipment, radial gap measurements were made on the X-ray film. The MONDO has a positional accuracy of ± 1 micron and measurement accuracy of ± 100 microns (total unsharpness in the film). Due to blurring, MONDO measurements were unreliable for a radial gap below 100 microns.

3.5 Estimation of minimum axial gap between two objects

For estimation of the minimum axial gap between two objects from the X-ray radiography image using image processing methods, a series of experiments was carried out using standard specimens.

better results in the measurement of radial gap by improving the edges and reducing the blurring functions, compared to Laplacian operator. The dimensions of the notch obtained in both cases had a variation of ± 7-10 microns.

3.4 Validation of the developed procedure for estimation of pellet-to-clad gap in MOX fuel pin

Figures 11(a) and (b) show the radiography image, without and with image processing respectively, for a fuel pin loaded with MOX fuel pellets inside the SS clad tube. From Figure 11(a), the pellet-to-clad gap is not seen clearly since the radial gap present was smaller than the total unsharpness of the geometrical set-up. In MOX fuel pins, the expected radial gap between pellet and clad is 90 ± 30 microns, which can be less than or close to total unsharpness (100 microns). Figure 11(b) shows the same radiography image after applying the first-order image sharpening operator over the image. In this image, the pellet-to-clad gap is clearly seen. It is clear that after applying the sharpening operator, the unsharpness is reduced significantly, resulting in a sharp differentiation of the pellet and clad positions. Figure 12 shows the grey-level profile along the line drawn in the images of Figures 11(a) and (b). The intensity profile in Figure 12 shows no observable intensity change for images without the sharpening operation, whereas it shows a sharp change in intensity levels after the sharpening process. From the sharp change in grey values corresponding to the pellet-to-clad gap, the top side radial gap was measured as 192 microns whereas the bottom side gap was 64 microns. The above result showed that the pellet was not placed uniformly inside the clad tube.

Table 3 shows the results of radial gap measurement made on some of the fuel pellets. Using the grey-level profile on raw digitised images, it was not possible to measure the radial gap below 180 microns. Image processing with the sharpening operation enabled measurement of a radial gap of 64 microns and above. The large pixel size in comparison to small radial gap is the limiting factor for achieving better resolution. Using

Table 2. Results for measurement of radial gap on calibration specimens

Trials Actual radial gap(microns)

Measured gap by image processing (microns)

Error(microns)

Case 1 100 130 ± 30

Case 2 150 193 ± 43

Case 3 250 300 ± 50

Figure 10. Grey-level profile for the line drawn across the notch (Figure 9)

Figure 11. Radiography image of a typical MOX fuel pin. (a) Without image processing and (b) after image sharpening

Figure 12. Grey profile for the line drawn across the MOX fuel pin shown in Figures 11(a) and (b)

Table 3. Results on measurements of pellet-to-clad radial gaps by MONDO and image processing

Pellet No Actual radial gap

( ± 30 microns)

Using MONDOmeasurement

Without image processing

With image processing

Top side(microns)

Bottom side (microns)

Top side(microns)

Bottom side(microns)

Top side(microns)

Bottom side(microns)

1.(Insulation

pellet)

180 100 100 N.M N.M 190 190

2. 90 N.M N.M N.M N.M 120 120

3. 90 N.M N.M N.M N.M 130 130

4. 90 N.M N.M N.M N.M 120 120

5. 90 N.M N.M N.M N.M 130 130

6. 90 N.M N.M N.M N.M 120 120

N.M – Not Measurable

� Insight Vol 49 No 12 December 2007

For these studies, 150 × 40 mm (L × B) and 8.11 mm thick copper and SS plates were chosen.

Figures 13(a), (b) and (c) show the digitised radiography images of the plates without any gap, with 75 microns gap and 180 microns gap respectively. From Figures 13(a-c), it is seen that due to the higher material density (ρ) of copper, the optical density is low compared to the SS plate. In all three cases, due to total unsharpness of the geometrical set-up, edge spreading in the axial gap location in the radiography image has been observed. Figure 13(a) shows this geometrical arrangement with a sharp change of contrast between the SS and Cu. For the IQI on the radiography image, ASTM plaque (SS) and wire type (SS) penetrameters were pasted on the source side of the object.

In all three cases, the gap was not seen due to the higher optical density on the SS plate which resulted in merging of the gap at the interface. From these experiments, it is understood that it is possible to quantify this gap only by scanning the grey levels across the image. In Figure 13(a), the ASTM plaque (SS) and ASTM wire type (SS) (1-A) penetrameters placed on the object were not seen due to the higher optical density of the SS plate region. After applying suitable image enhancement tools like contrast stretching and brightness control, the ASTM plaque type penetrameter was seen, with an equivalent penetrameter sensitivity of 2% (160 microns), and ASTM 1-A wire penetrameter with the 30 microns thickness wire.

For a typical source-to-object distance (SOD) of 1000 mm and the object thickness ‘t’ of 8.11 mm, the total unsharpness is

Ut = [(ft/(SOD))2 + Uf2] ½ .............................(5)

where Ut is the total unsharpness, Uf the inherent film unsharpness and f is the focal spot size.

This works out to be 103 μm. Also, from radiography principles, ‘d’ the critical size of the defect that could be detected is:

d = Ut / M = 103 μm ................................(6)where M is the magnification of the geometrical set-up.

From equation (6), it is clear that the minimum size of the flaw that could be detected from a radiograph is greater than 103 microns.

Figure 14 shows the grey-level profiles for the lines drawn across Figures 13(a), (b) and (c). From these profiles, sharp changes in grey levels can be seen at the boundary region in all three cases due to the axial gaps present at the interface of the SS and copper. In case (a), from the pixel positions corresponding to changes in grey values, a 125 micron axial gap is estimated against a true value of zero gap. The difference could be due to edge spreading of the image at the SS and Cu interface[11], and due to the blurred edges of the digital images as a result of sampling[17]. In radiography, for two objects placed in contact, due to edge spreading, undercutting of the X-ray beam (due to the sudden thickness change) and geometrical unsharpness, it is not possible to achieve zero gap detection[11]. In Figure 14, the grey-level profile with a sharp change in grey levels for the line drawn across Figure 13(b) showed 225 microns axial gap against 75 microns actual gap. The width of the peak in case (b) is broader than in case (a). For case (c), the grey-level profile

showed 330 microns gap against the actual gap of 180 microns. It is observed that the intensity and peak width are larger for case (c).

Table 4 summarises the results obtained from the measurement of varying axial gaps by the image processing technique. From this Table it is clear that even for the specimens placed with zero gap, due to the edge spreading at the interface, an axial gap of 125 microns is observed. For the cases (b) and (c), the measurement accuracy was ± 150 microns. Using the above approach, the pellet-to-pellet gap in MOX fuel pins was measured and compared with the results obtained from MONDO and without image processing (Table 5).

4. Conclusion

A new methodology has been developed for the precise estimation of radial and axial gaps from radiography images using image sharpening tools. Compared to a second-order Laplacian operator, a first-order derivative based edge sharpening is found to be a better tool for radial gap measurements. The new approach facilitates the enhanced detectability of radial gaps which are larger than the total unsharpness in a conventional radiography image. Radial gaps of 64 microns and above have been measured, using this approach, which was not possible without image processing tools. The procedure has been successfully applied to the estimation of the pellet-to-clad gap and pellet-to-pellet gap in MOX fuel pins. The image processing tools applied are found to drastically reduce the unsharpness in the images due to scattering components such as internal scatter, side scatter, backscatter and unsharpness due to

Table 4. Results for measurement of axial gap on calibration samples

Trials Actual axial gap (microns)

Measured gap from the images (microns)

Error(microns)

Case 1 0 125 ± 125

Case 2 75 225 ± 150

Case 3 180 330 ± 150

Table 5. Results of pellet-to-pellet axial gap measurement by MONDO and image processing

Pellet No Using MONDOmeasurement

(± 100 microns)

Without image processing

(± 140 microns)

With image processing

(± 70 microns)

1-2 300 400 310

2-3 178 250 190

3-4 279 310 260

4-5 220 250 190

5-6 161 250 190

Figure 14. Grey-level profiles across the Cu-SS plates in close contact, and with 75 microns and 180 microns gap (Figure 13)

Figure 13. Radiography image of Cu and SS plates, (a) without gap, (b) with 75 microns gap and (c) with 180 microns gap

Insight Vol 49 No 12 December 2007 7

the focal spot size and the detector. This methodology has been found to be useful for the estimation of internal dimensions with improved accuracy in assembled components of industrial X-ray radiography images.

Acknowledgement

We thank Dr P R Vasudeva Rao, Director, MMCG and Mr P Kalyanasundaram, Associate Director, ITG group for their support and encouragement.

References

1. A Notea, Y Segal and F Trichter, ‘Gaps dimensions in fuel elements from neutron radiography’, Conf: NDE in the Nuclear Industry, Zurich, American Society for Materials, pp 433-437, 1983.

2. D C Cutforth, ‘Dimensioning reactor fuel specimens from thermal neutron radiographs’, Nucl Technol, Vol 18, pp 67-70, 1983.

3. I Ruyter and M Leeflang, ‘Dimensional measurement of the pattern calibration pin’, Proc First World Conf in Neutron Radiography, San Diego, CA, USA, pp 867-885, 1981.

4. D Ingman and A Notea, ‘Derivative method for edge enhancement in radiography testing’, Nucl Technol, Vol 72, pp 99-106, 1986.

5. E Segal, A Notea and Y Segal, ‘Dimensional information through industrial computerized tomography’, Mater Eval, Vol 40, pp 1268-1279, 1982.

6. Y Bushlin, D Ingman and Y Segal, ‘The influence of noise on edge determination in radiography’, Nucl Technol, Vol 75, pp 23-33, 1986.

7. A Fishman, S Wajnberg, A Notea and Y Segal, ‘Extraction of dimensions from radiographs’, Mater Eval, Vol 39, pp 744-747, 1981.

8. F Trichter, ‘Dimensional measurements by means of radiography in the sub-millimetric range’, D.Sc Thesis, Department of Nuclear Engineering, Technion, Haifa, Israel, 1986.

9. Y Segal and F Trichter, ‘Limitations in gap width measurements by X-ray radiography’, NDT International, Vol 21, pp 11-16, 1988.

10. A A Harms, M Heindler and D M Lowe, ‘The physical basis for dimensional measurements in neutron radiography’, Mater Eval, Vol 36, pp 49-56, 1978.

11. R Halmshaw, ‘Scattered radiation in industrial radiography’, Brit J NDT, Vol 35, pp 111-118, 1993.

12. S Bagavathiappan, T Saravanan, J Philip, B Venkatraman, T Jayakumar and Baldev Raj, ‘X-ray radiography for development of defect-free electrochemical hydrogen meter for sodium systems’, Insight, Vol 48, No 10, pp 597-602, Oct 2006.

13. J C Domanus, ‘Practical methods of measuring dimensions from neutron radiographs of nuclear reactor fuel’, Nucl Tech, Vol 92, pp 389-395, Dec 1990.

14. J C Russ, The Image Processing Handbook, 3rd ed, 1999.15. U Zscherpel, U Ewert and Y Onel, ‘Digital industrial

radiography for corrosion inspection of pipelines, J NDE (India), Vol 20, No 3, pp 73-79, 2000.

16. R Klette and P Zamperoni, Handbook of image processing operators, 1996.

17. R C Gonzalez and R E Woods, Digital Image Processing, 2nd ed, 2002.

18. S Das, P R Vaidya and B K Shah, ‘Image processing techniques for digital radiographic images’, Mater Eval, pp 498-501, May 2006.