Research on ultrasonic detection and recognition methods for debonding defects in rubber-lined pipes
In view of the current lack of effective detection methods for debonding defects in in-service rubber-lined pipes,as well as low detection efficiency and accuracy,based on the basic principle of ultrasonic pulse echo method,a scanning and probe clamping device suitable for ultrasonic detection of cylindrical rubber-lined pipes was designed,and a corresponding ultrasonic detection experimental system was established.Various interference factors that affect ultrasound echo signals in practical applications have been analyzed,and a binary classification model for ultrasound echo signals based on one-dimensional convolutional neural network(CNN)has been specifically constructed.Through experiments and comparison with traditional ultrasonic detection defect recognition methods,the results show that the established ultrasonic detection system and one-dimensional CNN model can achieve more accurate identification of debonding defects even in the presence of multiple interference factors,with an accuracy rate of 96.22%.This provides an effective method and means for the automated detection and recognition of debonding defects in in-service rubber-lined pipes.
万方数据
维普
