Research review on life-cycle health management and intelligent maintenance of coal mining equipment

In recent years, with the rapid development of intelligent technology in coal mines, the whole life cycle health management and intelligent maintenance technology of coal mine equipment has attracted wide attention. It is an essential means to realize intelligent perception, intelligent identification, and maintenance decisions of the health status of coal mine equipment and ensure its efficient and reliable operation. However, at present, the coal mine is still primarily based on post-maintenance and preventive maintenance, which is challenging to meet the high-reliability requirements of coal mine equipment. Based on this, this paper reviews the research progress of the whole life cycle health management and intelligent maintenance of coal mine equipment to promote its application in coal mines. The connotation of health management and intelligent maintenance for coal mine equipment is explained, and the general framework of health management and intelligent maintenance for coal mine equipment is given. The research analyzes the status of coal mine equipment health management and intelligent maintenance technology from four perspectives: big data management, health status assessment, remaining useful life prediction, and intelligent maintenance decision-making technology. In the big data management of coal mine equipment, the latest achievements of multi-source information perception, big data cleaning, and big data integration and storage of coal mine equipment are summarized, the application of the relevant method is analyzed and compared, and the existing challenges of these methods are pointed out. In terms of coal mine equipment health status assessment, the latest development statuses of key methods are discussed from three aspects of feature extraction, health status classification, and health status assessment model construction, then the advantages and disadvantages of different methods are compared and analyzed, and the problems faced in this field are summarized. In the remaining useful life prediction of coal mine equipment, the advantages and disadvantages of the statistical model method, physical model method, and data-driven method are compared, and the problems of existing methods are expounded. In terms of intelligent maintenance of coal mine equipment, the main steps of coal mine equipment predictive maintenance are defined, the latest research results of intelligent maintenance methods of coal mine equipment and their advantages and disadvantages are compared and analyzed, and the deficiencies of the current research on intelligent maintenance decision technology are summarized. Combined with the challenges and development requirements, the prospect of coal mine equipment health management and intelligent maintenance technology is explored from the aspects of big data management, health status assessment under time-varying working conditions, remaining useful life prediction under the influence of multiple factors, multi-objective intelligent maintenance decision-making, algorithm integration and system development of coal mine equipment. The research direction of critical theories and methods of health management and intelligent maintenance for coal mine equipment is pointed out, which provides a basis for improving the level of health management and intelligent maintenance of the coal mine equipment and promoting the transformation and upgrading of coal industry and high-quality development.