基于灰色聚类决策的监测参数优化选择方法研究

预测与健康管理(PHM,prognostics and health management)已成为复杂系统的有机组成部分,选择合适的监测参数是实现PHM的前提和基础.针对PHM中监测参数选择缺乏定量方法的问题,提出了基于灰色聚类决策模型的监测参数优化选择方法.首先确定了监测参数选择基本准则并进行了定量描述;然后建立了用于监测参数优化选择的灰色聚类决策模型,并提出了基于层次分析法和信息熵的综合权重确定方法;最后以某航空发动机为案例详细说明了监测参数优化选择过程.分析结果表明所提方法具有一定的合理性和有效性.

Optimization of Monitoring Parameters Selection Based on Grey Clustering Decision

Prognostics and health management (PHM) has become an important part in complex systems,and selecting proper monitoring parameters(MPs) is the precondition and basis of PHM realization.Aiming at the lack of quantitative methods of MP selection in PHM,a novel approach based on grey clustering decision is proposed.Firstly,the basic MP selection criteria and the corresponding calculation methods are presented.Then,the grey clustering decision model for MP optimization selection is constructed,and an integrated weight determination method based on analytic hierarchy process and information entropy is provided.Finally,an aero engine is used as an example to demonstrate the proposed approach,and the analysis results show the proposed method is effective and feasible.