Performance evaluation method for laser inertial measurement units under non-equivalent priority of indicators

A laser inertial measurement unit (LIMU) is a navigation subsystem for rockets, airplanes, and other systems, and its reliability is highly demanding. Maintenance and selection based on performance evaluation are effective ways to improve the reliability of LIMUs. Therefore, this study presents a performance evaluation method for LIMUs under the non-equivalent priority of indicators. First, the LIMUs’ properties and expert knowledge ambiguity are analyzed, and the difficulties in the performance evaluation of LIMUs are described in detail, which are the difficulty in embedding expert knowledge, the explosion of rule combinations, and the non-equivalent priority of indicators, respectively. Second, to address the problems of difficulty in embedding expert knowledge and rule explosion, a hierarchical indicator system is constructed by synthesizing the historical information and test information, and a hierarchical evaluation model is built further. The “or operation” is introduced into the Belief Rule Base (BRB) model to realize the rule formulation and fusion in the case of non-equivalent priority of indicators, and the novel BRB-non-equal priority model is unified with the BRB model in the form of reasoning through the rational design of parameters. Third, an artificial bee colony algorithm is used to optimize the parameters of the hierarchical evaluation model, which can integrate test data and expert knowledge. Finally, using the performance evaluation of 8 LIMUs as a case, the feasibility and superiority of the performance evaluation method are validated.