Control Decision of Equipment Health State based on Big Data Reasoning
GUO Lu1，2， LIU Xiaodong2， WANG Yufeng1， ZHANG Zhen1
1. Jiangnan Institute of Mechanical and Electrical Design， Guiyang 550009， Guizhou， China；
2. School of Equipment Management and UAV Engineering， Air Force Engineering University， Xi'an 710051， Shaanxi， China
Abstract：To acquire precise control of weaponry and equipment health state, a decisive control method is proposed using comprehensive reasoning of big data. First, the whole life cycle data of weaponry and equipment was collected and processed to form knowledge as one of the characteristic attributes. Then, according to the dynamic control flow of weaponry and equipment health state, a mechanism of an integrated case using reasoning and rule base reasoning was proposed. Thirdly, the k-nearest neighbour algorithm is used to calculate similarity for case-based reasoning, and fact feature set matching was used for rule reasoning where new knowledge was constantly formed. Finally, taking the hydraulic system of a certain weapon as a case study, the control strategy was deduced from its health monitoring and other attribute data. The simulation results show that the integrated intelligent reasoning method integrated with big data can generate precise and accurate dynamic control decisions adapted to the health state of weaponry and equipment, and can effectively support the accurate management of the health state of weaponry and equipment.
郭璐, 刘晓东, 王玉峰, 张振. 基于大数据推理的装备健康状态控制决策[J]. 空天防御, 2023, 6(3): 85-94.
GUO Lu, LIU Xiaodong, WANG Yufeng, ZHANG Zhen. Control Decision of Equipment Health State based on Big Data Reasoning. Air & Space Defense, 2023, 6(3): 85-94.
