Double-layered wrap-around sensor network for three-dimensional positioning of acoustic emission sources and its effect on monitoring crack propagation in rock samples

Jing Yang,Fang Yuan,Bofei Yang,Guangjian Liu,Atif Javed,Zonglong Mu,Jinglong Cao,Shaokun Gong

doi:10.1177/1550147718803068

Abstract

The present sensor arrangement in a cubic way for monitoring crack propagation in rock samples exhibits shortfalls of blind monitoring zone and large deviation. This study proposes a double-layered wrap-around sensor network, which enhances the monitoring range and improves the location accuracy of acoustic emission source. Furthermore, based on the polar formation algorithm, acoustic emission source was positioned to explore the propagation of microscopic cracks in cylindrical rock samples and this was further validated by the acoustic emission activity index. The results show that: (1) The double-layered wrap-around sensor network exhibits considerably broader monitoring range and enhanced precision. The simulated fracture formed from cracks of high-energy release had a favorable consistency with the macro-failure surface of rock specimens; (2) During the loading process, acoustic emission activity had a significant positive correlation with signal amplitude and the number of events. In addition, acoustic emission activity of medium-grained sandstone showed a tendency of decreasing—remaining at a low value—increasing—remaining at a high value, which exactly corresponds to the four rock loading stages of compaction, elastic deformation, crack development, and crack connection; (3) rock samples experienced micro-cracking of low energy, micro-cracking of high energy, and crack connection in sequence in the failure process, which shows a high consistency between crack development and acoustic emission activity. Thus, acoustic emission activity could be used as an index for assessing the rock failure state.

Highlights

Acoustic emission source (AES) monitoring refers to monitoring acoustic emission (AE) signals emitted from rock masses subjected to loading, and AES can be used to evaluate the stress level and damage degree of rock masses
In order to improve sensor efficiency, an optimized microfiber coupling sensor, the bar wave calibration method based on AE sensor, a new denoising method based on p-phase shifted fiber Bragg grating sensors, SA ultrasonic sensor were proposed to increase the sensitivity of AE sensors in terms of receiving signals and to improve the accuracy of location.[11,12,13,14]
Based on equation (16), the number of AE events in a cyclic loading–unloading process was taken as a group for calculating S (y-direction) of acoustic emission activity (AEA)

Summary

Introduction

Acoustic emission source (AES) monitoring refers to monitoring acoustic emission (AE) signals emitted from rock masses subjected to loading, and AES can be used to evaluate the stress level and damage degree of rock masses. The arrangement is capable of monitoring the crack development in the cylindrical rock specimens and accurately positioning AES. As crack locations in the rock specimens are stochastically distributed, the number of sensors can be increased to form multiple three-dimensional wraparound monitoring networks to achieve more accurate monitoring results.

Results

Conclusion