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摘要
Automatic identification of flaws is very important for ultrasonic nondestructive testing and evaluation of pipelines. A novel automatic identification approach of flaws using support vector machine (SVM) is presented. Wavelet transform is applied to feature extraction of ultrasonic echo signals, and SVM is to perform the identification task. To validate this approach, some experiments are performed. The results show that unlike conventional and artificial neural networks (ANN) identification methods the new technique performs better than conventional evaluation ones with advantages of high identification performance for pipeline flaws, lower cost, excellent generalization.
- 出版日期2015
- 单位宁波工程学院
