Study On ECT/UT And Evaluation Technology Of The Conductive Structures

With the rapid development of the modern industrial production, higher and higher demands have been put forward for the nondestructive testing technique. As representative measures of the nondestructive testing (NDT) methods, Eddy current testing (ECT) and Ultrasonic Testing (UT) techniques have gained better effects in the qualitative inspection of the conventional defects. However, due to their own limitations, lots of difficult problems remain unsolved for ECT and UT in the defects classification and quantitative inspection of the multi-layer conductive structures, the qualitative inspection and the quantitative evaluation of the minor defects, and the practical inspection demands can't be satisfied. In this dissertation, supported by the National Natural Science Foundation of China and the Ph.D. Programs Foundation of Ministry of Education of China, investigations have been conducted on the optimization of ECT and UT and their compound application technology, much effort has been devoted to the investigation of the optimization design of ECT experiment, the defects classification and quantitative testing of the conductive structures, the data fusion from different types of sensors of ECT and UT, the probability of detection (POD) and the uncertainty of measurement research of the testing results by means of two different kinds of NDT methods, and some primary results have been obtained in the end. The main contents of the dissertation and the innovations of the research chiefly include the following:1. The robust design based on Taguchi method is introduced into the optimization design of the ECT experiment so as to determine the optimal inspection parameters of ECT conveniently. In accordance with the parameters selection and determination method in the Taguchi method, utilizing the SNR analysis principle, such key inspection parameters as the excitation frequency and voltage have been optimized by means of analyzing and comparing the experiment data. In addition, the assessing technology of uncertainty of measurement for ECT is investigated based on the theory of uncertainty of measurement, and the typical assessing scheme and process have been presented.2. In order to solve the problems in detecting deep defects and the minor surface defects of the conductive structures for ECT and UT, Dempster-Shafer evidence theory and BP networks are applied to fusing different detecting results from ECT and UT and the precision of defects classification has been improved. A data fusion method of different sources to combine the fuzzy C-means clustering algorithm with Dempster-Shafer evidence theory is proposed, avoiding depending on large amounts of experiment data or the expert knowledge in combining different evidences. The practicability of the algorithm is improved and thus it's convenient for the quantitative evaluation of defects.3. On the basis of detection parameters optimization and the defects classification, the radial basis function neural networks (RBFNN) and the fuzzy Bayesian networks (FBN) are used to evaluate the defects parameters quantitatively. The subtractive algorithm is utilized to improve the conventional radial basis function neural network, and the fuzzy processing is combined with Bayesian networks to construct the FBN, the ECT and UT data are used to train the networks and inverse the defects quantitatively, and better effect has been achieved in the inversion precision and efficiency.4. The application of probability of detection (POD) in the evaluation of the inspection results is introduced. Firstly, the fundamentals of evaluating the inspection results of the flaws in the conductive materials are discussed by means of POD. On the basis of analyzing different existing POD empirical models synthetically, a practical three-parameter empirical model is put forward, and a certain precision has been arrived at in evaluating the inspection results; then the modeling and evaluating schemes based on model-assisted POD (MAPOD) are investigated, the experiment results validate the generalization performance of MAPOD, and the limitation of the empirical model has been offset.