多状态切换下随机退化设备剩余寿命预测  

Remaining Useful Life Prediction for Multi-state Switching Random Degradation Equipment

作　　者：幸元兴 张建勋 满谦 胡昌华 杜党波 裴洪 XING Yuanxing;ZHANG Jianxun;MAN qian;HU Changhua;DU Dangbo;PEI Hong(Rocket Force University of Engineering,Xi'an 710000,China;The Second Military Representative Office of the Rocket Army Equipment Department in Xi'an Region,Xi'an 710000,China)

机构地区：[1]火箭军工程大学,西安710000 [2]火箭军装备部驻西安地区第二军事代表室,西安710000

出　　处：《电光与控制》2023年第7期111-118,共8页Electronics Optics & Control

基　　金：国家自然科学基金重点项目(61833016);国家自然科学基金青年基金(61903376,62103433)。

摘　　要：工业设备、武器装备等大型复杂系统在全寿命周期中通常会经历贮存、待机、测试、运转、维修等多个状态,且不同状态下设备内部损耗速率各不相同,这给设备的剩余寿命预测问题带来新的挑战。鉴于此,提出了基于维纳过程建立多状态切换设备的退化模型,结合半马尔可夫模型和离散马尔可夫链模型,推导得到了多状态切换设备的剩余寿命,并提出了一种蒙特卡罗仿真算法进行求解。此外,采用了期望最大化算法和极大似然算法辨识所提模型参数。最后,通过仿真实验和实际案例证明了所提算法的有效性。Large-scale complex systems such as industrial equipment and weapons usually go through storage,standby,testing,operation,maintenance and other states in the whole life cycle,and the internal wear rate of equipment is different in different states,which brings new challenges to the problem of remaining useful life prediction of equipment.In view of this,the degradation model of multi-state switching equipment is established based on Wiener process,and the remaining useful life of multi-state switching equipment is derived by combining semi-Markov model and discrete Markov chain model,and a Monte Carlo simulation method is proposed to solve it.In addition,expectation maximization algorithm and maximum likelihood algorithm are used to identify the parameters of the proposed model.Finally,the effectiveness of the proposed method is proved by simulation experiments and practical cases.

关 键 词：多状态 剩余寿命预测 维纳过程 半马尔可夫 离散马尔可夫链 

分 类 号：TP202[自动化与计算机技术—检测技术与自动化装置]