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Investigation on the Elastic-Plastic Deformation of Bearing Plates for Rock Bolting System

ROCK MECHANICS AND ROCK ENGINEERING 2025年 1-12页

作者： Liu, Wenju Gao, Fuqiang Dong, Shuangyong Cui, Chunyang Wang, Xiaoqing Yuan, Guiyang Cao, Shuwen CCTEG Coal Min Res Inst Beijing Peoples R China China Coal Res Inst State Key Lab Intelligent Coal Min & Strata Contro Beijing Peoples R China

Recent advancements in laser scanning technology and deep learning have enabled novel approaches for measuring rock bolt load by analyzing deformation fields of bearing plates. Building on these developments, a critical challenge was raised that the plastic deformation and mechanical error of bearing plate may significantly influence the measurement accuracy of bolt load. Thus, understanding the mechanical behavior of the bearing plate, particularly its plastic deformation, is of great importance for ensuring the measurement accuracy of the proposed approach and evaluating its effectiveness in providing surface support under conditions of high rock deformation. For this purpose, in this study, extensive laboratory tests were performed in the laboratory to investigate the mechanical behavior of bearing plates under different rock bolting conditions, including bolt loads, rock types, and installation conditions. It is found that the hemispheric and flat regions of the bearing plate exhibit distinct deformation characteristics, with the flat region being particularly prone to plastic deformation, especially in softer rock and under less-favorable installation conditions. Furthermore, an onsite method was developed to invert mechanical error fields, achieving an accuracy of 0.18-0.27 mm and thereby improving the precision of rock bolt load assessments by accounting for initial mechanical errors. In addition, a novel approach was proposed to estimate the historical maximum bolt load independently of the loading path, achieving an accuracy of approximately 3.5 kN. These advancements provide a more accurate foundation for rock bolt load evaluation and practical guidance for optimizing support system parameters in mining and underground engineering.

关键词： Rock bolt load Bearing plate Elastic-plastic deformation Laser scanning

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A Novel Method for Estimating Axial Force of Rock Bolt Through 3D Laser Scanning and Deep Learning

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ROCK MECHANICS AND ROCK ENGINEERING 2024年第2期57卷 1437-1450页

作者： Liu, Wenju Gao, Fuqiang Dong, Shuangyong Yuan, Guiyang China Coal Res Inst State Key Lab Intelligent Coal Min & Strata Contro Beijing Peoples R China Coal Min Res Inst CCTEG Beijing Peoples R China

Estimating the axial force of rock bolts is vital for the stability and safety of underground excavations. Current methods suffer from being labor-intensive, time-consuming, and prone to inaccuracies. This paper presents a novel method for estimating the axial force of a rock bolt, a critical element in underground engineering, by analyzing the deformation field of the bearing plate. This innovative approach combines 3D laser scanning for data acquisition with a developed convolutional neural network (CNN) model for data processing, resulting in an efficient and non-destructive external monitoring technique. The proposed method was verified with 27 laboratory experiments. The results showed an accurate estimation of the axial forces of rock bolts with an average error of +/- 5 kN, underlining the method's potential for in-situ application in underground engineering. This research not only contributes to the development of intelligent systems in rock mechanics and engineering but also has significant implications for industries, such as mining, tunneling, and underground engineering. The study introduces a novel method that utilizes 3D laser scanning and a developed CNN model to accurately estimate the axial force of rock *** proposed method achieves accurate estimations of rock bolts' axial forces with an average error of +/- 5 *** work includes the integration of object detection algorithms for large-scale 3D laser scanning and the creation of a database of various bearing plates to enhance the method's robustness.

关键词： Rock bolts Non-destructive testing 3D laser scanning Deep learning

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Milling Tool Condition Monitoring Based on an Integrated Wireless Vibration Sensing Tool Holder

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INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING 2024年第12期25卷 2611-2623页

作者： Sun, X. China Coal Technol & Engn Grp Shanghai Co Ltd Shanghai 200030 Peoples R China State Key Lab Intelligent Coal Min & Strata Contro Shanghai Peoples R China

Tool condition monitoring (TCM) is crucial for smart manufacturing and cutting vibration signal is proven to be highly related to tool wear state. In this paper, a wireless smart tool holder is designed for online vibration signal sensing for TCM with accelerometer embedded close to vibration source and signal processing circuits integrated, showing good performance of vibration sensing ability compared with traditional wired ways. Cutting experiments are designed with cutting parameters of great varied range to guarantee the generalization ability of TCM algorithm for different machining conditions and vibration signal of whole tool life cycle is collected by smart handle. Then feature extraction and selection are studied to provide valuable information and artificial neural network algorithm is realized. Results show the algorithm has an accuracy of 85.0% with poor performance in distinguishing some wear states. To solve this problem, an optimized method based on two ANNs in series with new feature sets is proposed. The optimized algorithm has an accuracy of 90.0% with an accuracy increase of 16.8% and the average predicted probability increase of 15.0% in initial wear samples. In spite of speed sacrifice, the optimized algorithm makes progress in recognition accuracy and data confidence level.

关键词： Smart tool handle Milling vibration Tool condition monitoring Feature extraction and selection Artificial neural network

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Coal mine Methane Gas Concentration Prediction Based on PSO-VMD-LSTM and Error Quadratic Decomposition

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minING METALLURGY & EXPLORATION 2025年第2期42卷 647-663页

作者： Hu, Qingsong Cheng, Yuanxun Zheng, Shuo Zhao, Die Li, Shiyin Sun, Yanjing Zhang, Yuansheng China Univ Min & Technol Engn Res Ctr Intelligent Control Underground Space Minist Educ Xuzhou Peoples R China China Univ Min & Technol Sch Informat & Control Engn Xuzhou Peoples R China State Key Lab Intelligent Optimized Mfg Min & Met Beijing Peoples R China Beijing Key Lab Proc Automat Min & Met Beijing Peoples R China

High gas concentration in coal mine is easy to lead to explosion and poisoning accidents, and timely and accurate prediction can effectively prevent such accidents. A new prediction method is proposed to improve the accuracy of prediction coal mine gas concentration, which combines Variational Mode Decomposition (VMD) with Long Short-Term Memory (LSTM) to mitigate the impact of the complexity on prediction accuracy. Firstly, the penalty factor and the modes number of VMD are optimized using the Particle Swarm Optimization. Subsequently, the lengths of one-step prediction windows for different Intrinsic Mode Functions (IMFs) after VMD decomposition are determined through autocorrelation and partial autocorrelation analysis. LSTM one-step prediction models are built for different IMFs to obtain prediction results. Finally, by reorganizing the dataset to construct an error sequence, a VMD-LSTM model is established on the error sequence to perform a secondary decomposition and predict the errors at future time steps. The prediction results and the error prediction results are combined to obtain the final prediction results for the test set. Experimental results show that the proposed method achieves the highest prediction accuracy compared to the other four methods.

关键词： Gas concentration prediction Variational mode decomposition Long short-term memory intelligent coal mining

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Automatic Identification of Rock Discontinuity Sets by a Fuzzy C-Means Clustering Method Based on Artificial Bee Colony Algorithm

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APPLIED SCIENCES-BASEL 2025年第3期15卷 1497-1497页

作者： Li, Peng Chen, Tianqi Liu, Yan Cai, Meifeng Sun, Liang Wang, Peitao Wang, Yu Zhang, Xuepeng Univ Sci & Technol Beijing Key Lab Minist Educ Efficient Min & Safety Met Min Beijing 100083 Peoples R China Shandong Univ Sci & Technol State Key Lab Strata Intelligent Control & Green M Qingdao 266590 Peoples R China Shandong Univ Sci & Technol Minist Sci & Technol Qingdao 266590 Peoples R China Univ Sci & Technol Beijing Key Lab Intelligent Bion Unmanned Syst Minist Educ Beijing 100083 Peoples R China

The identification and classification of rock discontinuities are crucial for studying rock mechanical properties and rock engineering optimization design and safety assessment. An improved artificial bee colony (ABC) algorithm is proposed and combined with the fuzzy C-means (FCM) clustering method to develop an FCM clustering method for automatically identifying rock discontinuity sets based on the ABC algorithm (FCM-ABC method). All the equations of the method are fully developed, and the methodology is presented in its entirety. Moreover, the rock structural planes are investigated in a gold mine in China using a ShapeMetriX 3D system. Based on the measured structural plane data, the specific calculation process, selection of parameters, effectiveness of grouping, and the dominant orientation of the proposed method for structural plane occurrence classification are analyzed and discussed, and satisfactory clustering results are achieved. This validates the validity and reliability of the method. Furthermore, multiple aspects of the excellent performance of this method for the identification of structural plane sets compared to traditional clustering methods are demonstrated. In addition, the significance of structural plane identification in the prevention and control of rock engineering disasters is discussed. This new method theoretically expands the technology of rock mass structural plane identification and has important application value in practical engineering.

关键词： rock discontinuity sets structural plane investigation FCM-ABC method automatic identification

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Study on Surface Activity of Inorganic Salts on [C12MIm]Cl and Wetting Characteristics of Compound Modified Bituminous Coal

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ENERGY & FUELS 2024年第5期38卷 3728-3739页

作者： Zhang, Xiangfei Ni, Guanhua Jiang, Yuangang Gong, Li Li, Zhao Ban, Jing Shandong Univ Sci & Technol Sch Safety & Environm Engn Qingdao 266590 Peoples R China State Key Lab Intelligent Control & Green Min Min Qingdao 266590 Peoples R China

The technical problem of the difficult wetting of coal bed water injection urgently needs to be solved, and the wetting of surfactants on the coal body is mainly affected by the concentration. In recent years, research related to surface-active ionic liquids (SAILs) with long-chain alkyl groups has attracted much attention. Salt can enhance the wetting effect of surfactants, but there are few studies on the effect of inorganic salts on the surface activity of [C(12)MIm]Cl and the effect of compound wetting bituminous coal. In this paper, NaCl was selected to be complexed with [C(12)MIm]Cl, and the trends of key functional groups and surface activity changes during coal wetting were quantitatively characterized from a microscopic point of view by functional group and wetting characterization analysis. The results showed that under the treatment of 0.6 mol/L of NaCl + 10 mmol/L of the [C(12)MIm]Cl compound, the surface tension was reduced by 7 N m/m and the minimum contact angle by 15.5 degrees. In the modified coal, the peak area of the =CH2 group is reduced by 29%, the peak area of the -CH3 group is increased by 24%, the peak area of the OH center dot center dot center dot N group is reduced by 14%, and the wetting effect is enhanced. However, the high concentration of NaCl in the composite solution will weaken the wetting effect on bituminous coal. The research results provide theoretical support for coal seam composite wetting by water injection.

关键词： Chemical structure Coal Functional groups Surface tension Wetting

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Localization of Acoustic Emission Source in Rock Using SMIGWO Algorithm

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INTERNATIONAL JOURNAL OF COAL SCIENCE & TECHNOLOGY 2025年第1期12卷 1-10页

作者： Wei, Jiong Gao, Fuqiang Lou, Jinfu Yang, Lei Wang, Xiaoqing China Coal Technol & Engn Grp Co Ltd Coal Min Res Inst Beijing 100013 Peoples R China State Key Lab Intelligent Coal Min & Strata Contro Beijing 100013 Peoples R China China Univ Min & Technol Beijing Sch Energy & Min Engn Beijing 100083 Peoples R China Sichuan Univ State Key Lab Hydraul & Mt River Engn Chengdu 610065 Peoples R China

The Grey Wolf Optimization (GWO) algorithm is acknowledged as an effective method for rock acoustic emission localization. However, the conventional GWO algorithm encounters challenges related to solution accuracy and convergence speed. To address these concerns, this paper develops a Simplex Improved Grey Wolf Optimizer (SMIGWO) algorithm. The randomly generating initial populations are replaced with the iterative chaotic sequences. The search process is optimized using the convergence factor optimization algorithm based on the inverse incomplete & Gcy;function. The simplex method is utilized to address issues related to poorly positioned grey wolves. Experimental results demonstrate that, compared to the conventional GWO algorithm-based AE localization algorithm, the proposed algorithm achieves a higher solution accuracy and showcases a shorter search time. Additionally, the algorithm demonstrates fewer convergence steps, indicating superior convergence efficiency. These findings highlight that the proposed SMIGWO algorithm offers enhanced solution accuracy, stability, and optimization performance. The benefits of the SMIGWO algorithm extend universally across various materials, such as aluminum, granite, and sandstone, showcasing consistent effectiveness irrespective of material type. Consequently, this algorithm emerges as a highly effective tool for identifying acoustic emission signals and improving the precision of rock acoustic emission localization.

关键词： Acoustic emission Source localization Iterative chaotic mapping Simplex method Grey wolf optimizer algorithm

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Risk Assessment of Water and Sand Inrush in mining under Thick Loose Layer Based on Comprehensive Weight-Cloud Model

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GEOFLUIDS 2023年第1期2023卷

作者： Zhang, Wenquan Wu, Xintao Wu, Xunan Lei, Yu Shao, Jianli Wang, Zaiyong Shandong Univ Sci & Technol Coll Energy & Min Engn Qingdao 266590 Peoples R China Minist Sci & Technol State Key Lab Strata Intelligent Control & Green M Qingdao 266590 Peoples R China

Many deep mining mines in southwestern Shandong Province of China are covered with thick loose layers. When mining near the loose layers, there is a risk of water and sand inrush, which threatens the personal safety of miners. The prediction of sudden water and sand inrush is difficult due to the comprehensive influence of many factors, and the influencing factors are fuzzy and random. To solve this problem, in this paper, a new risk assessment method of water and sand inrush based on comprehensive weight and cloud model was proposed. Seven factors are selected as indexes: the aquifer thickness, the thickness ratio of sand layer to clay layer, the thickness of bottom clay layer, the coal seam thickness, the percentage of core recovery, the geological structure, and the bedrock thickness. The assessment index system is established, and the index is divided into three grades. A comprehensive weighting method, which combines analytic hierarchy process (AHP), entropy weight method (EWM), and minimum entropy principle, is used to reasonably assign the weight of index. Based on the cloud generator equation, the membership function is obtained. The assessment result of the assessment object is obtained by combining the membership degree and the weight of index. The comprehensive weight-cloud model assessment method is applied to the risk assessment of water and sand inrush in the 6311-2 working face in the sixth mining area of Baodian Coal mine. According to the assessment results, the following conclusions can be drawn: (1) the bedrock thickness and the coal seam thickness are the main factors of water and sand inrush under loose layer mining;(2) the assessment results obtained by the comprehensive weight-cloud model method are consistent with the actual situation. The assessment method can provide scientific reference for the safe mining under the thick loose layer in the deep mines of southwest Shandong.

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Field and Numerical Investigations on Pumpable Standing Supports Failure Analysis in the Longwall Pre-driven Recovery Room

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ROCK MECHANICS AND ROCK ENGINEERING 2025年第1期58卷 1199-1220页

作者： Zhang, Dong Bai, Jianbiao Zhang, Zizheng Zhu, Qiancheng Deng, min Yan, Shuai Wang, Rui Liu, Shuaigang China Univ Min & Technol State Key Lab Fine Explorat & intelligent Dev Coal Xuzhou 221116 Peoples R China Xinjiang Inst Engn Xinjiang Engn Res Ctr Green Intelligent Coal Min Key Lab Xinjiang Coal Resources Green Min Xinjiang Key Lab Coal Bearing Resources Explorat & Urumqi 830023 Peoples R China Hunan Univ Sci & Technol Work Safety Key Lab Prevent & Control Gas & Roof D Hunan Prov Key Lab Safe Min Tech Coal Mines Xiangtan 411201 Peoples R China China Univ Min & Technol Sch Mines Xuzhou 221116 Peoples R China

Pumpable standing supports without sufficient loading-bearing capacity (LBC) will result in the deformation failure of the pre-driven recovery room (PRR). A combined method of numerical simulation and field investigation is adopted to analyze the failure mechanism of the high-water cementitious material (HWCM) pier cribs and the PRR. The influence of main roof hanging length (MRHL), height-to-diameter ratio, and external constraint strength on the LBC of the HWCM pier cribs are analyzed accordingly. It indicates that when the MHHL increases, the bending deformation of the roof increases (eccentric load and eccentricity increase), the pier cribs gradually change from axial compression to shear sliding failure, the limit LBC of the inby pier crib is reduced from 13.5 to 8.6 MPa, and the maximum roof subsidence of the PRR is increased from 267 to 595 mm. The height-to-diameter ratio is negatively correlated with the LBC of the HWCM pier cribs, but the external constraint strength is positive. A corresponding optimization scheme is proposed and applied to engineering practice. The monitoring results exhibit that the maximum stress on the pier cribs was 18.5 MPa (without failure), and the maximum roof-to-floor convergence of the PRR is 220 mm, ensuring the safe and efficient recovery of mining equipment. Establishing a UDEC model to analyze the failure mechanism of the pier cribs under the eccentric load induced by advanced abutment pressure and roof rotation *** contribution indicators of MRHL, height-to-diameter ratio, and external constraint strength to the load-bearing capacity of pier cribs were analyzed.A collaborative support method for pier cribs in PRR was proposed and applied to engineering practice, ensuring the recovery of mining equipment.

关键词： Pre-driven recovery room Pumpable standing supports High-water cementitious material Eccentric load Collaborative support

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Failure evolution and precursor prediction of fissured sandstone based on power-law behavior of electric potential

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ENGINEERING GEOLOGY 2025年 346卷

作者： Shan, Tiancheng Li, Zhonghui Wang, Enyuan Zhang, Xin Jia, Haishan Wang, Xiaoran Zhao, Enlai Niu, Yue Chen, Dong China Univ Min & Technol State Key Lab Coal Mine Disaster Prevent & Control Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol Natl Engn Res Ctr Coal Gas Control Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol Sch Safety Engn Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol State Key Lab Fine Explorat & Intelligent Dev Coal Xuzhou 221116 Peoples R China China Univ Min & Technol State Key Lab Geomech & Deep Underground Engn Xuzhou 221116 Jiangsu Peoples R China

The engineering rock with defects is prone to induce serious geological disasters such as rockbursts under stress disturbance. Exploring the power-law failure prediction method of electric potential (EP) signals is effective and has great potential. In this study, the EP monitoring tests of the fissured red sandstone samples with variable crack angles under uniaxial compression were carried out. Spatiotemporal response, The Hurst statistical feature and Benioff-type power law of EPs were adopted to analyze the scale invariance of EPs and their relationship with damage evolution during rock failure. The failure prediction method based on Benioff potential and early warming assessment system were further proposed to predict the failure time range of potential rock instability in real time. The results show that with increasing crack angle, the mechanical strength and macroscopic crack number of samples reduce, and the power rate growth trend of EPs is delayed. The EP intensity increases closer to the crack propagation path, which is associated with the local damage and moving charged dislocations. Benioff potential of all samples shows power-law properties and is closely related to the internal damage evolution. With decreasing the remaining failure time, the variable power exponent mt in the local temporal window gradually increases and approaches the upper limit of 1, indicating an increased possibility of potential catastrophic failure in rocks. The failure time range is predicted in real time through Benioff power behaviors with the upper and lower limits of mt, and the prediction accuracy improves as the rock failure approaches.

关键词： Fissured sandstone Electric potential Failure evolution Power-law properties Early warning assessment

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