Artificial Self-Recovery Opens up a New Journey of Autonomous Health of Mechanical Equipments  

作　　者：Xin Pan Haoyu Zhang Jinji Gao Weimin Wang Zhinong Jiang Lidong He 

机构地区：[1]Beijing Key Laboratory of Health Monitoring and Self-recovery for High-end Mechanical Equipment,Beijing University of Chemical Technology,Beijing 100029,China [2]Engineering Research Center of Chemical Safety Ministry of Education,Beijing University of Chemical Technology,Beijing 100029,China

出　　处：《Engineering》2024年第6期22-26,共5页工程（英文）

基　　金：supported by Natural Science Foundation of Beijing(3212010);National Natural Science Foundation of China(51875031 and 52242507).

摘　　要：1.Introduction With the implementation of modern production strategies,such as“Industry 4.0”and“Made in China 2025,”the development of high-end mechanical equipment is gradually reaching a high degree of parameterization,digitalization,networking,and intelligence[1].High-end mechanical equipment no longer consists of traditional single devices,but is closely linked to the overall production process;that is,a variety of devices interact with each other and collectively form a complex system.However,faults can lead to production delays throughout the system and even seriously threaten the safety of workers[2].In addition,equipment operating in unmanned air or space vehicles(including space robots)cannot be repaired by humans if they break down[3].Until recently,the typical method of addressing machine faults was primarily the“fault cure”method,which involves manually shutting down,inspecting,and repairing the equipment to restore normal operation.Accordingly,the maintenance cycle of the traditional“fault cure”method is time-consuming,and the quality of the maintenance depends on the skills of the technician[4].

关 键 词：COLLECTIVE consuming OPEN 

分 类 号：TH69[机械工程—机械制造及自动化]