Spatiotemporal early prediction of rock damage in rock engineering based on infrared radiation monitoring technology
Qiangqiang Gao (China University of Mining and Technology)
Liqiang Ma (China University of Mining and Technology, Ministry of Education, Urumqi, Xinjiang Institute of Engineering)
Wei Liu (China University of Mining and Technology)
Naseer Muhammad Khan (National University of Science and Technology (NUST), China University of Mining and Technology)
X.Z. Wang (TU Delft - Geo-engineering)
Yanxiao Ni (China University of Mining and Technology)
Kunpeng Yu (China University of Mining and Technology)
Saad S. Alarifi (King Saud University)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
This study introduces the Spatio-Temporal Attention Enhanced Encoder-Decoder Damage Prediction Network (STAE-EDDPNet), an innovative deep learning model designed to enhance the predictive capabilities of coal-rock damage infrared temperature fields, which is crucial for the safe production in rock engineering and mining engineering. STAE-EDDPNet integrates a spatio-temporal attention mechanism, significantly improving the capture of complex nonlinear spatio-temporal information in rock infrared radiation. Compared with baseline models such as 3DCNN, ConvLSTM, and EDDPNet, STAE-EDDPNet demonstrated superior performance in both single-step and multi-step forecasting tasks. Test set results show that its predictive accuracy is 25.56% higher than 3DCNN, 5.69% higher than ConvLSTM, and 0.19% higher than EDDPNet. The study also found that the characteristics of brittle failure rock data significantly affect model training and predictive performance, providing a direction for future data collection and experimental design improvements. The introduction of STAE-EDDPNet not only promotes the application of infrared monitoring technology in the field of safety monitoring but also provides valuable reference for rock damage early warning.