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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Xinyu Wang & Guoqing Zhu & Deqiang Cheng & Bin Miao & Fanbao Chen & He Tian, 2022. "Spatiotemporal Evolution Characteristics of Apparent Resistivity and Its Response Correlation with Acoustic Emission of Coal under Multi-Step Loading," Sustainability, MDPI, vol. 14(16), pages 1-17, August.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:10061-:d:887998
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