首页|Extraction of the key infrared radiation temperature features concerning stress and crack evolution of loaded rocks

Extraction of the key infrared radiation temperature features concerning stress and crack evolution of loaded rocks

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The infrared radiation temperature(IRT)variation concerning stress and crack evolution of rocks is a crit-ical focus in rock mechanics domain and engineering disaster warning.In this paper,a methodology to extract the key IRT features related to stress and crack evolution of loaded rocks is proposed.Specifically,the wavelet denoising and reconstruction in thermal image sequence(WDRTIS)method is employed to eliminate temporal noise in thermal image sequences.Subsequently,the adaptive partition temperature drift correction(APTDC)method is introduced to alleviate temperature drift.On this basis,the spatial noise correction method based on threshold segmentation and adaptive median filtering(OTSU-AMF)is proposed to extract the key IRT features associated with microcracks of loaded rocks.Following temperature drift correction,IRT provides an estimation of the thermoelastic factor in rocks,typically around 5.29x10 5 MPa 1 for sandstones.Results reveal that the high-temperature concentrated region in cumulative thermal images of crack evolution(TICE)can elucidate the spatiotemporal evolution of localized damage.Additionally,heat dissipation of crack evolution(HDCE)acquired from TICE quanti-fies the progressive failure process of rocks.The proposed methodology enhances the reliability of IRT monitoring results and provides an innovative approach for conducting research in rock mechanics and monitoring engineering disasters.

Infrared radiation(IR)Temperature driftSpatial background noiseRock fractureAverage infrared radiation temperature(AIRT)Heat dissipation of crack evolution(HDCE)

Wei Liu、Liqiang Ma、Michel Jaboyedoff、Marc-Henri Derron、Qiangqiang Gao、Fengchang Bu、Hai Sun

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Key Laboratory of Xinjiang Coal Resources Green Mining(Xinjiang Institute of Engineering),Ministry of Education,Urumqi 830023,China

Xinjiang Key Laboratory of Coal-bearing Resources Exploration and Exploitation,Xinjiang Institute of Engineering,Urumqi 830023,China

Xinjiang Engineering Research Center of Green Intelligent Coal Mining,Xinjiang Institute of Engineering,Urumqi 830023,China

School of Mines,China University of Mining & Technology,Xuzhou 221116,China

Institute of Earth Sciences,University of Lausa

Institute of Earth Sciences,University of Lausanne,Lausanne 1015,Switzerland

School of Civil Engineering,Liaoning Petrochemical University,Fushun 113001,China

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National Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesGraduate Innovation Program of China University of Mining and TechnologyPostgraduate Research &Practice Innovation Program of Jiangsu ProvinceProject of Liaoning Provincial Department of Education

518742802021ZDPY02112023WLKXJ046KYCX23_2811JYTMS20231458

2024

10.1016/j.ijmst.2024.08.003

矿业科学技术学报(英文版)
中国矿业大学

矿业科学技术学报(英文版)

CSTPCDEI
影响因子：1.222
ISSN：2095-2686
年,卷(期)：2024.34(8)