Spatiotemporal Evolution Characteristics of Apparent Resistivity and Its Response Correlation with Acoustic Emission of Coal under Multi-Step Loading

Xinyu Wang, Guoqing Zhu, Deqiang Cheng, Bin Miao (), Fanbao Chen and He Tian
Additional contact information
Xinyu Wang: School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
Guoqing Zhu: School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
Deqiang Cheng: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China
Bin Miao: School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China
Fanbao Chen: School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
He Tian: School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China

Sustainability, 2022, vol. 14, issue 16, 1-17

Abstract: To understand the early warning signs of damage during the coal mass deformation process, an integrated monitoring procedure was designed that combines the apparent resistivity (AR) and acoustic emission (AE) of coal damage under multi-step loading. The spatiotemporal response characteristics of AR and the time-varying evolution of AE were studied and the varying correlation between the two was discussed. Additionally, the macro–microscopic mechanics of the AR response during the coal deformation process was explored. The results show that the AR and AE signals corresponded well with the applied load during the coal deformation process. In the early loading stage, variations in AR and AE signals were not apparent. As the applied load increased, the high-resistance area of AR increased and the AE signals became active. The local variation characteristics of AR could be used to indirectly invert the internal structure of the coal samples. The electrical variation in the loaded coal was mainly controlled by the conductive surface of cracks. The acoustic and resistivity methods can strongly complement the spatial and temporal dimensions of early warning systems for disasters. The AE technique can continuously monitor a test area for abnormal occurrences in the engineering site, and AR tomography images that are obtained can be used to locate inversions in the source coal in order to take pre-emptive action before disaster occurs. This research can provide new ideas for monitoring and early warning systems for coal and rock dynamic disasters.

Keywords: multi-step load; acoustic emission; resistivity method; coal fracture; spatiotemporal evolution; early disaster warning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/16/10061/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/16/10061/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:16:p:10061-:d:887998

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().