Early warning of coal dynamic disaster by precursor of AE and EMR "quiet period"

• Published in: International journal of coal science & technology 2022-12, Vol.9 (1), p.46-14, Article 46
• Main Authors: He, Shengquan, Qin, Mengli, Qiu, Liming, Song, Dazhao, Zhang, Xiufeng
• Format: Article
• Language: English
• Subjects: AE and EMR; Coal; Coal dynamic disaster; Disasters; Early warning; Energy; Fossil Fuels (incl. Carbon Capture); Geotechnical Engineering & Applied Earth Sciences; Integrated Development of Transportation and Energy; Mineral Resources; Monitoring systems; Peak load; Precursor characteristics; Quiet period; Rocks
• ISSN: 2095-8293; 2198-7823
• DOI: 10.1007/s40789-022-00514-z

Efficient and accurate monitoring and early warning of coal dynamic disaster and other disasters can provide guarantee for the efficient operation of mine transportation system. However, the traditional threshold early warning method often fails to warning some accidents. To address above issues, a new early warning method was proposed based on "quiet period" phenomenon of AE and EMR during fracture. It is found that, a "quiet period" of AE and EMR was present before the load reaches the peak stress, which could be used as one of the precursors to warn the imminent failure of coal and rock specimens. MS and AE signals increased abnormally followed by the phenomenon of "quiet period" before the occurrence of coal dynamic disaster on site, and the decrease of MS events in the "quiet period" is about 57%–88% compared with that in previous abnormal increase stage. During the damage evolution of coal and rock, "quiet period" phenomenon usually occurred at 85%–90% of the peak stress, where the slope of damage parameter curve is almost zero. The "quiet period" of the AE-EMR signals and the low change rate of damage parameter before failure provide a theoretical foundation for the coal dynamic disaster warning based on the "quiet period" precursor found in MS-AE-EMR monitoring system. These findings will help reduce the number of under-reported events and improve early warning accuracy.