基于涡流/超声数据融合的复合无损检测技术

In order to overcome the disadvantages of the commonly-used ultrasonic testing method, the application of the eddy current testing (ECT) in the quantitative nondestructive testing of the rail cracks was investigated in this paper, the structure and the principle of the ECT experiment system and the experiment design were expounded. The subtractive clustering algorithm was used to improve the RBF neural network, and the data acquired from the specimen by means of the experiment system was used to train the network model. A pair of GMR-based probes were used to increase the detecting performance for the deep defects and the minor surface defects. The experiment results show that the constructed model by the improved algorithm possesses higher accuracy in the inversing of the rail cracks, in the mean time, the training time of the inversing model is decreased, and it satisfies the demand of the inline inspection for the parameter of the rail crack.