基于特征参数趋势进化的故障诊断和预测方法

 采用时间序列方法对可以表征系统故障状态的特征参数的趋势进化进行预测，同时考虑特征参数的概率分布特性，给出了对系统进行故障诊断和预测的方法。在已获得特征参数监测数据的基础上，分别对具有广义强度/故障阈值确定分布或故障模式特征参数空间分布两种形式的故障判据，提出了利用二次指数平滑预测模型对系统未来某时刻的故障状态进行预测的方法。给出包括故障概率和故障指数在内的故障诊断和预测结果形式，可进一步为系统的维修决策等提供参考。

An Approach to Diagnostics and Prognostics Based on Evolutionary Feature Parameters

Time series analysis methods are used to prognostics the feature parameters evolution that can indicate the system's fault.Considering the uncertainty of feature parameters,a method for fault diagnostics and prognostics are presented.The relationship between feature parameter and fault criterion is first discussed.Then,the fault criterion is summarized to two types: general strength /fault threshold and space distribution of feature parameters for fault mode.The evolution of feature parameters along product lifetime is a stochastic process under the influence of product work conditions and environment conditions.Based on monitoring data of feature parameters,the time series analysis methods can be used to prognostics the future conditions of systems.A quadric exponential smoothing model is presented in a case study.For a certain time,the conditions of systems can be diagnosed according to the quantificational relationship between feature parameter and fault criterion.Based on the consideration of feature parameters distribution,fault probability and fault index are two kinds of results that can use to assist the decision for maintenance.