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Ni Labview 2010 Crack

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Version 1.0.1: Pre-install step added to prevent installation on LabVIEW 2010 or later. For 2010 or later, you can optionally enable VI Scripting by selecting the option in Tools>>Options>>VI Server>>VI Scripting.

Existing eddy current non-destructive testing (NDT) techniques generally do not consider the inclination angle of inclined cracks, which potentially harms a larger region of a tested structure. This work proposes the use of 2D scan images generated by using pulsed eddy current (PEC) non-destructive testing (NDT) technique in the quantification of the inclination and depth of inclined cracks. The image-based feature extraction technique effectively identifies the crack axis, which consequently enables extraction of features from the extracted linear scans. The technique extracts linear scans from the images to allow the extraction of three novel image-based features, namely the length of extracted linear scans (LLS), the linear scan skewness (LSS), and the highest value on linear scan (LSmax). The correlation of the three features to surface crack inclination angles and depths were analysed and found to be highly dependent on the crack depths, while only LLS and LSS are correlated to the crack inclination angles.

As compared to conventional eddy current testing which only applies a single frequency for excitation, pulsed eddy current (PEC) offers the advantage of exciting magnetic field of multiple frequency components in a short period of time. PEC also offers many benefits over the more traditional eddy current NDT techniques, which makes it applicable in various applications as proposed by researchers around the globe. Additionally, PEC imaging techniques potentially serve as an effective tool to provide a more comprehensive understanding of the tested region, by constituting every pixel in 2D scan images with the peak value or other signal features obtained from differential signals at each spatial location. An extensive list of reported works suggested various approaches on crack quantifications and reconstruction through 2D scan technique. For example, He et al. [1] suggested the use of rectangular excitation coil to provide a constant distribution of magnetic field into the sample. Although the amount of magnetic field concentrated into the sample was not optimal, the results demonstrated a better predictive capability of identifying the width and length of the crack. In another work, Arjun et al. [2] studied the use of specially designed probe with a ferrite core in between the excitation and pick up coil to improve the performance of A-scan signals, thus allowing greater accuracy in 2D scan images. Besides defect characterisation, 2D scan images can also be employed for a fast crack profile reconstruction, as studied by Bai et al. [3]. PEC imaging technique was also proven to offer better reliability and defect detectability than flash thermography for crack detection in carbon fibre reinforced plastics (CFRP) [4].

Many simulations and validated experiments were designed to study the effects of crack depths to their corresponding PEC responses using either signals or images; however, little attention has been paid to find the theoretical influence of inclination angles. This is highly important in real life application, as cracks, such as rolling contact fatigue (RCF) in rail track heads, tend to grow at steep angles and can potentially result in an underestimation of the cracks. Since it is highly difficult to manufacture a calibration sample with specific crack geometry, well-defined cracks with different inclination angles are commonly used instead [13]. This research opens up the use of image processing to extract linear scans from 2D scan images. Features extracted from the obtained linear scan were compared with their corresponding inclination angles and depths. The rest of the paper is organized as follows: Section 2 discusses the methodology employed; Section 3 explains the results of the image-processing technique used, and the correlation of extracted features with crack parameters; Sections 4 presents the conclusions of the work.

To create the artificial cracks, slots were cut through the width of the aluminium test pieces, with different inclination angles and depths. Cracks were fabricated using electrical discharge machining (EDM) and separated by 70 mm from each other to avoid the edge effect. Figure 2 illustrates the fabricated cracks.

The scanning was purposely done perpendicularly to the crack axis to collect more data from the 2D scan images, thus allowing greater number of data to be analysed. However, to demonstrate the effectiveness of the proposed image-based feature extraction technique, additional scanning was done on 45 crack of 4 mm depth, in a random scanning direction.

The acquired response signals were filtered using low-pass filter and then normalized. The normalized reference signal from a flawless sample was subtracted from them to yield differential signals. Peak value was the feature used and plotted at each 2D coordinate to produce the 2D scan images. The 2D scan images were 2D-interpolated to improve the image resolution. For positioning reference, the signal with the highest peak value on one of the 2D scan images row was assigned as the 0-mm position. Bearing in mind that the surface crack grows to the right-hand side of the crack opening, the signals that are picked up before reaching the differential signal with the highest peak were assigned as the signals at negative positions.

As the crack extended completely across the width of the test piece, the highest peak values in the 2D scan images contributed to a line across the image, which should be along the direction of the crack axis. To make full use of it, the pixels in each image containing the highest peak values (local maxima) were first detected. It is also important to note that finding local maxima in an image can be troublesome when the image is noisy. Noise typically contributes to single pixel variation, thus making the algorithm to find local maxima to be ineffective. Prior to the steps, median filtering was first applied.

The proposed technique for processing 2D scan images composed of four main routines; image dilation, non-maximum suppression, the Hough transform, and the extraction of pixel value orthogonal to the crack axis, which are discussed below.

The crack axis lines detected were first extrapolated to the edge of the images as the crack was recognized to extend across the 2D scan images. Figures 3(a) and (b) depict the illustration of extracting linear scan from 45, 4 mm crack 2D scan image on one of the points along the crack axis line. From that, the pixel values orthogonal to each point along the detected line were extracted. Using simple geometry, crack direction, Φ, obtained from Hough transform was used to compute the coordinate of x1, x2, y1, and y2 as shown in Eq. (1):

Three novel image-based features were used to effectively quantify surface crack inclination angles and depths, namely length of linear scan (LLS), linear scan skewness (LSS), and linear scan peak (LSmax). The LLS is essentially the length of the linear scan, after 60% thresholding. The feature was opted as eddy current tend to concentrate the eddy current along the crack elongation, making the LLS to increase with the decrease of inclination angle.

The symmetricity of the 2D scan images around the crack axis was observed to differ across distinct inclination angles. Hence, the second image-based feature was introduced, termed as LSS. LSS explains the effect of the crack inclination angles on the field distribution at different probe positions. The elongation of inclined cracks to the positive spatial positions made the linear scan to settle slower than the negative side. The calculation of LSS was adopted from statistical skewness function [18], which can be defined as

The third feature was termed as LSmax, coming from the extraction of maximum value of each linear scan. According to our previous work, the maximum peak value of LLS does not occur exactly above the middle of crack opening, but slightly further to the crack elongation direction [19].

Figures 6(a) and (b) shows the relationship of the LSS and crack parameters. From both figures, the LSS was mostly linearly dependent on both inclination angles and depths. LSS explained the measure of symmetricity of the cracks, with 90 cracks ideally exhibited zero LSS. While this was true, crack depths also influenced LSS because of the high concentration of eddy current for cracks of deeper depths. Inclined deeper cracks also lengthen further, resulting in higher LSS. It was also observed that despite the depths, the LSS for cracks of 90 was almost flat at zero value, explaining the symmetrical effect of magnetic field at both side of the linear scanning. The LSS was also more prone to noise as observed at the standard deviations, since the calculation of the LSS itself considered the peak value at each spatial position.

Interestingly, LSmax correlates strongly with depth, but inclination angle has relatively less effect on LSmax, as illustrated in Figures 7(a) and (b). Although in theory, inclination angle wass believed to provide slight influence on LSmax due to the crack elongation, but practical application proved otherwise due to the limited effect of the inclination angle on the response signals.

Ilham Mukriz Zainal Abidin, a research officer at the Leading Edge Non-Destructive Testing Technology (LENDT) Group, Malaysian Nuclear Agency, received his PhD in 2010 from Newcastle University, U.K. His research area includes active thermography and advanced NDT.

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