In order to solve the problem that the information silos caused by the narrow bandwidth and long delay of the network in the fully mechanized coal mining face in the coal mine fail to meet the needs of intelligent mining，the 5G communication technology with high bandwidth and low delay was proposed to upgrade the industrial control system and design an intelligent coal mine safety control platform. Firstly，based on the design concept of an intelligent coal mine safety control platform，the overall architecture of the intelligent coal mine safety control platform was introduced，and the coal mine safety information processing mechanism was analyzed. Then，a coal mine safety risk analysis index system was constructed，and an improved particle swarm optimization algorithm was used to optimize a multi-layer feedforward neural network to determine the level of coal mine safety risks. Finally，based on 5G communication technology，the intelligent remote control of coal mines was achieved by combining geological data and video analysis of the coal mining face，5G remote control，personnel safety assurance，and digital twin systems. Research has shown that the intelligent coal mine safety control platform improves the storage，transmission，and processing efficiency of data streams，effectively avoiding the phenomenon of information silos between multiple systems and providing a new method for promoting the implementation of unmanned mining mode in coal mining faces and achieving efficient coal mine safety control.

To study the damage characteristics of the circular chain of the scraper conveyor，a mathematical model was constructed for the sliding and rubbing wear and vibration impact damage of the circular chain for different damage modes. By using finite element analysis software to simulate and analyze the sliding and rubbing damage between chain links and that between the chain link and the middle groove，as well as the vibration impact damage during the circular chain transmission process，the damage characteristics of circular chains were explored. The research results indicate that under the simulation of sliding and rubbing damage between the chain link and the middle groove，the maximum force on the bottom of the chain link is 65.92 MPa，and the maximum wear depth is 0.55 mm. Under the simulation of sliding and rubbing damage between chain links，the maximum force at the chain link socket is 164.8 MPa. Under the simulation of vibration impact damage of chain links，the maximum stress value on the chain link gradually increases from 39.11 MPa to 52.61 MPa.

The roller bearings of open pit belt conveyors face problems of low fault identification accuracy. To improve the accuracy and efficiency of fault diagnosis，a fault signal detection method of roller bearings with CPSO algorithm based on OVMD was proposed. Firstly，the excellent global optimization characteristics of CPSO were utilized，and the optimal parameter setting of the variational mode decomposition (VMD) algorithm was precisely locked to achieve effective parameter tuning of VMD. Then，VMD technology after parameter tuning was used to process the vibration data，and specific frequency band signal components were accurately extracted from the vibration data. Finally，the sparse maximum harmonic noise ratio deconvolution (SMHD) technology was used to purify the above frequency band signals，which significantly enhanced the identification accuracy of the fault characteristics of roller bearings of belt conveyors. The results show that CPSO has better performance for VMD improvement than other VMD optimization algorithms. The VMD algorithm after CPSO optimization combined with SMHD can successfully identify the specific fault points of the inner and outer rings of the rolling bearings under complex working conditions and determine the specific damage forms of the bearings.

In order to reduce the serious threat of slope sliding and the geologic disasters they cause to property safety，a novel slope sliding monitoring method was proposed by using a matching algorithm based on the improved Harris corner point detection technique. First，an image processing model for predicting slope sliding displacement was constructed by optimizing the Harris corner point detection; then，based on the calibrated template，the changes in the location of the corner points were monitored to accurately estimate the sliding displacement and track its trajectory，so as to effectively monitor the movement of the slope; finally，a modularized test environment was constructed to monitor slope sliding conditions. The results show that the method reduces the generation of pseudo-corner points in slope monitoring and identification，improves the accuracy and efficiency of corner point detection，and effectively records the tiny sliding of the target in the horizontal，vertical，and inclined directions to form trajectory tracking results.

In order to solve the problems of imperfect construction of risk classification control mechanism，low informatization level，and insufficient employee participation in the construction of double-prevention mechanism in coal chemical enterprises and build a long-term double-prevention mechanism for enterprises，firstly，the design idea，system architecture，and function module of the digital platform were described in detail. Then，with risk classification control and hidden danger investigation and management as the core，data collection，intelligent analysis，early warning，task distribution，progress tracking，and other functions were integrated to realize the digital management of the whole process of safety production of coal chemical enterprises. Finally，combined with specific cases，the application effect of the double-prevention digital platform in coal chemical enterprises was evaluated. The results show that the platform can provide enterprises with a standardized and intelligent closed-loop management system from the aspects of risk identification and assessment，classification control，and hidden danger investigation and management，and it achieves good application effects in risk management and control，hidden danger investigation，and main responsibility implementation. The platform can grasp the risk dynamics in real time，discover and eliminate hidden dangers in time，improve the emergency response speed，and reduce the accident rate. It can provide a new idea for the informatization and intelligent construction of the double-prevention mechanism of coal-to-oil coal chemical enterprises and provide a reference for the construction of the double-prevention digital platform of other industrial and mining enterprises.

There are many and complex factors influencing the safety status of electromechanical equipment in coal mines，and it is difficult to identify the potential safety hazards. To address these issues，a comprehensive safety evaluation model of electromechanical equipment in coal mines based on AHP-TOPSIS method was proposed. According to the cause theory of electromechanical equipment accidents in coal mines，20 evaluation indexes were selected from four aspects of human factors，electromechanical equipment maintenance，management organization，and working environment，and the safety status evaluation index system of electromechanical equipment in coal mines was constructed. Then，the AHP method was used to calculate the weight of each index，and the TOPSIS method was used to calculate the relative nearness degree between the sample and the ideal solution. The index weight was coupled with the relative nearness degree，and the safety level of electromechanical equipment in coal mines was predicted. Finally，the model was applied to a mine of Shanxi Coal Group. The results show that the safety level of electromechanical equipment in the coal mines mine is Level Ⅱ. According to the prediction results，the potential safety hazards are identified by reverse order analysis，and the analysis results are in line with the actual situation.

In order to study the distribution characteristics of the three zones of spontaneous combustion in the goaf area of the gob-side entry retaining in the shallowly buried and easily spontaneous combustion coal seam，the variation laws of oxygen and temperature in the goaf area of the gob-side entry retaining were dynamically monitored by embedding high-pressure rubber hoses，high-strength steel pipe-protected optical fibers for temperature measurement，and monitoring beam tubes. With the help of numerical simulation software，the distribution range of the three zones of spontaneous combustion in the goaf area was determined. The results show that the oxygen concentration at the measurement points between the supports in the goaf area of the 31116 gob-side entry retaining shows an overall downward trend with the advancement of the working face，and the oxygen concentration at the measurement points in the return air channel is locally reversed due to the interference of air leakage at the corner. Based on the temperature measurement data of optical fibers，the temperature change cannot be used as the basis for the division of the three zones of spontaneous combustion in the goaf area of the gob-side entry retaining in Jinjie Coal Mine. Affected by the airflow migration and local air leakage，the oxygen concentration in the goaf area of the 31116 is slightly higher on the return air side than on the intake air side. Finally，it is obtained that the oxidation zone range on the intake air side of the 31116 is 140.4-313.3 m. In the middle part，the range is 201.2-351.6 m，and on the return air side，it is 153.2-328.1 m. According to factors such as the amount of residual coal in the goaf area and geological characteristics，it is comprehensively determined that the minimum advancing speed under normal production conditions of the working face is 3.3 m/d.

To ensure the safety of miners，protect equipment，and improve production efficiency，the identification and intrusion early warning technology of large-scale engineering vehicles in opencast coal mines based on multi-sensor information fusion was studied. Firstly，based on the overall technical framework and implementation method，the identification and detection method of engineering vehicles based on YOLOv8 was proposed. The software and hardware platform for detection was built in the opencast coal mine，and the identification accuracy of the engineering vehicle identification and detection method based on YOLOv8 was tested through a total of 6 300 sample datasets from on-site shooting and networks. The results show that the engineering vehicle detection model based on YOLOv8 can quickly and accurately identify multiple vehicle targets in the opencast coal mine，and the detection accuracy is more than 0.85，with a low missed detection rate. In addition，the incomplete vehicle image can be recognized. The engineering vehicle identification and intrusion early warning system studied in this paper provides vehicle identification and early warning hints for the working equipment to avoid safety accidents.

In order to promote the safe operation and safety management of wind turbines in icing areas during winter under the new situation，the safety risk of wind turbine falling ice，equipment operation risk，and power supply risk were analyzed，and they are the most serious risks of blade icing. Based on these risks，a comprehensive ice monitoring method based on the combination of blade ice thickness monitoring method and wind turbine operation data monitoring method was proposed，and the safe operation of the wind turbine was classified. This article elaborated on the design and construction process of the first composite coating anti-icing technology scheme for large-scale in-service wind turbines in China. The results indicate that the composite coating anti-icing technology solution can effectively solve the problem of wind turbine icing and can provide a reference for similar engineering projects.

In order to scientifically assess the firefighting and rescue capability and put forward effective suggestions for the prevention and control of fire risks，a firefighting and rescue capability assessment system applicable to the characteristics of coal chemical enterprises was constructed based on the hierarchical analysis-fuzzy comprehensive model. The scientificity，applicability，and accuracy of the assessment index system and the model were verified through specific cases. The research results show that along with the booming development of China's economy and society，the scope of the firefighting and rescue task gradually presents a trend of diversification and complexity. In this ever-changing environment，whether firefighting and emergency rescue are able to respond decisively，accurately，and efficiently at critical moments is a key issue that needs to be solved in the current research. The assessment index system and the modeling method used can provide a new perspective for the firefighting and rescue capability building of coal chemical industry-related enterprises and provide decision support for firefighting and rescue capability building.