A physically based classification approach for identifying AE source mechanism

D. Rajendra; A. Esterline; M. Sundaresan

doi:10.1117/12.847781

8 April 2010 A physically based classification approach for identifying AE source mechanism

D. Rajendra, A. Esterline, M. Sundaresan

Proceedings Volume 7648, Smart Sensor Phenomena, Technology, Networks, and Systems 2010; 76480Y (2010) https://doi.org/10.1117/12.847781
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2010, San Diego, California, United States

Abstract

Identification of the source mechanism and measurement of source strength are important requirements for wider field application of the acoustic emission technique. It is difficult to relate a given source event to resulting acoustic emission waveforms in experimental results. However, it is practical to simulate such source events using numerical simulations and examine the resulting waveforms. The present paper uses such an approach to identify the patterns embedded in the waveforms and their variation with relative positions of the source and sensor. Important elements in the waveforms are shown to have strong variation with respect to the relative positions of the source and sensor. The resulting amplitude variations should be taken into account in the measurement of acoustic emission source strength. In addition, it is shown that the shear horizontal wave has a prominent component in the normal stresses in the radial direction. Acoustic emission waveforms obtained from the numerical simulations were also used to demonstrate pattern classification of these waveforms and identify the source mechanisms. The three elements of the waveforms, So, Ao, and Shear, were considered as the basic elements of the waveform. These elements have different frequency bandwidths that are directly related to the impulse duration of the incremental crack growth. Correlation coefficients between these elements and the acoustic emission waveforms were used as a means for identifying the source type.

Citation Download Citation

D. Rajendra, A. Esterline, and M. Sundaresan "A physically based classification approach for identifying AE source mechanism", Proc. SPIE 7648, Smart Sensor Phenomena, Technology, Networks, and Systems 2010, 76480Y (8 April 2010); https://doi.org/10.1117/12.847781

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