Showing papers on "Time-of-flight diffraction ultrasonics published in 1996"

Automatic detection of defects in industrial ultrasound images using a neural network

Abstract: Time-of-flight diffraction (TOFD) is a relatively new method of ultrasonic inspection and is well suited to semi- automation using methods such as robotic scanning, computer conditioned data acquisition and signal and image enhancement. However very little work has been documented on the full computer understanding of such scans. Instead, most work has been directed at aiding the manual interpretation process to determine defect characteristics. This paper describes the application of image processing and neural networks (ANNs) to the task of completely automating the decision making process involved in the interpretation of TOFD scans. Local area analysis is used to derive a feature vector which contains 2D information on defect/component and non-defect areas. These vectors are then classified using an ANN trained with the backpropagation algorithm. The labelled image is then further segmented using binary shape analysis to discriminate between component echoes, or defect signals. Time-of-flight correction techniques may be then used in order to determine the location of defects within a scanned weld.

Estimates of the probability of detection of flaws in TOFD data with varying levels of noise

Abstract: Artificially generated B-scan data have been produced which has allowed useful trials of flaw detection by the TOFD technique to be carried out. The results obtained give an indication of the limits of operation of the technique under various circumstances and the cost of these trials is probably less than 5% of that of carrying out equivalent practical investigations. At typical and moderate levels of background noise, the PoD achieved was 100%, while the PFI was zero at typical noise levels and less than 3% at moderate noise levels. The PoD fell and the PFI rose as the noise levels increased further. The precisions achieved in flaw location and flaw sizing well exceeded those normally quoted for TOFD. The results from the trials have been compared with the predictions of a model that is used to predict the probability of detection (PoD) associated with TOFD. This comparison shows that the model predictions are quite pessimistic in some important areas and may be used to justify some changes in the model. At the present level of development, the use of artificial B-scans should not be considered as a replacement for practical trials, but they provide a useful test-bed to establish general levels of detectability and to compare operators and procedures.

An evaluation of the performance of the TOFD technique as a means of sizing flaws, with particular reference to flaws with curved profiles

Abstract: Simulated TOFD data have been employed as a means of evaluating the ability of the TOFD technique to size flaws in both the through-thickness and length dimensions. The interest in the evaluation arose as a result of an earlier study which suggested that the fundamental precision ofthe technique may be greater than is currently assumed. The current assumptions are based on the results of blind trials and it may be that the difference between the expected and achieved precisions is simply a reflection of the wide natural variability of flaws. On the other hand it may be that the procedures currently employed to estimate the flaw size are insufficient or that the trials themselves incorporate other sources of error. These possibilities were of sufficient interest to warrant a preliminary study of the sizing potential of the technique. The results of the study indicate that the potential of the technique for determining the through-thickness extent of flaws is greater than has been assumed. The results from this trial are consistent with a precision of 0.25% of the specimen thickness, whereas the current assumption is a precision in the region of 2% of specimen thickness. An allowance must be made for the use of simulations rather than real data, but it is difficult to envisage this bridging the gap between these figures. An alternative explanation that should be considered is whether the confirmatory (destructive or other NDT) examinations associated with blind trials are contributing to the apparent errors. Ideally, these should not be producing errors greater than 0.25% of specimen thickness but it is difficult to believe that this could be achieved in practice. As regards flaw length, the results from this study highlight a distinction between flaws with a substantially flat profile (broadly parallel to the surface) and flaws with a continuously curving profile. The former group would include many common flaws such as slag lines and most lack of fusion defects. The latter would include most surface-breaking cracks. Generally, the estimation of flaw length using TOFD is based on assumptions which are correct only for the first class offlaws. For flaws with curved profiles the estimate of length can be quite seriously in error. The results of blind trials, where some attempt has been made to estimate properly the flaw length, tend to suggest an error of about 7 mm to 10 mm. However, it now appears probable that this is a compromise between data for flat profile and curved profile flaws. The former are sized in length to a precision of a few millimetres, whereas the latter may be in error by well over 10 mm. A number of procedures for flaw length estimation have been evaluated in this study and it is shown that the optimum approach is to identify the flaw type and employ a different sizing procedure for each. This would be expected to give an overall precision of better than 4 mm. One empirical procedure appears to provide acceptable length estimates for both types of flaw and the mean error using this would be in the region of 6.5 mm. At first sight the use ofa single procedure appears to have some advantages. However, the identification of flaw profiles is straightforward from TOFD B-scans, so the use of the twin procedures appears to be the optimum under most conditions that can be envisaged. This identification could be made automatic tofit in with modern trends in data analysis.

Automatic defect detection in industrial radioscopic and ultrasonic images

Abstract: This thesis describes a number of approaches to the problems of automatic defect detection in ultrasonic Time of Flight Diffraction (TOFD) and X-ray radioscopic images of butt welds in steel plate. A number of novel image segmentation techniques are developed, two of which feature the use of backpropagation artificial neural networks. Two new methods for defect detection in ultrasonic TOFD images are described - the first uses thresholding of individual one-dimensional A-scans, and the second uses a neural network to classify pixels using two dimensional local area statistics. In addition, three new methods for defect detection in radioscopic images are described - the first is based on the use of two conventional spatial filters, the second uses grey level morphology to replace the 'blurring' stage of conventional "blur and subtract' procedures, and the third uses a neural network to classify pixels using raw grey level data at the input layer. It is considered that all five methods which have been developed show novelty in their methodology, design and implementation, most specifically in that (1) no previous methods for automatic defect detection in TOFD images, (2) very few successful implementations of grey level data processing by neural networks, and (3) few examples of local area segmentation of 'real' textured images for automatic inspection have been reported in the literature. The methods developed were tested against data interpreted by skilled NDT inspectors. In the case of the ultrasonic TOFD image processing, both automatic methods performed exceptionally well, producing results comparable to that of a human inspector. In the case of the radioscopic image processing, the ANN method also produced results comparable to that achieved by a human inspector and also gave comparable or consistently better results than those obtained using a number of existing techniques.

Detection of fatigue cracks in eyebars using time of flight diffraction

Abstract: This paper examines the development of a Time of Flight Diffraction (TOFD) ultrasonic method for defect detection and sizing in eyebars. Eyebars from the Pasko - Kennewick bridge are utilized as test specimens to determine eyebar fatigue performance, and to test the effectiveness of the TOFD method. The test setup for making crack depth measurements in eyebars is described. Measured results of the depth of machines slot test specimens and results of fatigue crack growth are presented.