Similarity assessment of acoustic emission signals and its application in source localization.

In conventional AE source localization acoustic emission (AE) signals are applied directly to localize the source without any waveform identification or quality evaluation, which always leads to large errors in source localization. To improve the reliability and accuracy of acoustic emission source localization, an identification procedure is developed to assess the similarity of AE signals to select signals with high quality to localize the AE source. Magnitude square coherence (MSC), wavelet coherence and dynamic timing warping (DTW) are successively applied for similarity assessment. Results show that cluster analysis based on DTW distance is effective to select AE signals with high similarity. Similarity assessment results of the proposed method are almost completely consistent with manual identification. A novel AE source localization procedure is developed combining the selected AE signals with high quality and a direct source localization algorithm. AE data from thermal-cracking tests in Beishan granite are analyzed to demonstrate the effectiveness of the proposed AE localization procedure. AE events are re-localized by the proposed AE localization procedure. And the accuracy of events localization has been improved significantly. The reliability and credibility of AE source localization will be improved by the proposed method.