基于统计数据驱动的复杂性能退化过程剩余寿命预测方法

项目名称： 基于统计数据驱动的复杂性能退化过程剩余寿命预测方法

项目编号： No.61473254

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 自动化技术、计算机技术

项目作者： 徐正国

作者单位： 浙江大学

项目金额： 80万元

中文摘要： 剩余寿命预测技术是实现设备高效预测维护策略的核心技术。非线性、非高斯性、多阶段性等性能退化特征，多性能退化过程相互关联，存在外部冲击过程作用，构成了性能退化过程的复杂性，并对剩余寿命预测技术提出了更高的要求。本项目在分析统计退化数据的基础上，重点研究基于精确剩余寿命分布计算的退化过程非线性、非高斯性特征建模；处理退化过程多阶段性特征的自适应剩余寿命预测方法；多性能退化过程的关联性分析与建模、竞争失效分析及剩余寿命预测方法；离散冲击过程和连续性能退化过程的混合建模、估计离散冲击损伤量和连续退化量的混合贝叶斯滤波算法及混合剩余寿命分布模型。通过本项目的研究，期望能够建立灵活而精确的非线性、非高斯、多阶段性等复杂性能退化特征的模型及相应的剩余寿命分布模型；揭示多性能退化过程相互关联、以及外部冲击过程作用于性能退化过程等复杂现象的机理，并提出相应的性能退化模型和剩余寿命预测方法。

中文关键词： 故障预测与健康管理；预测维护；性能退化建模；剩余寿命预测；可靠性

英文摘要： Remaining useful lifetime prediction is one key to efficient predictive maintenance. The complexities of degradation processes include the nonlinear, non-Gaussian, and multistage properties; the relationships between multiple degradation processes; and the effect on degradation from external impact. Therefore, more effective remaining useful lifetime prediction methods are needed. Based on the analysis for statistical degradation data, this project will establish nonlinear and non-Gaussian models that can be used to predict the remaining useful lifetime accurately. Adaptive strategy will be adopted to process the multistage property. The models of the relationships between different degradation processes will be studied, and these models will further be used to analyze the competition between different failure modes, as well as to predict the remaining useful lifetime. The hybrid models including discrete impact and continuous degradation processes will also be considered. Based on the hybrid models, Bayesian filtering will be designed to estimate the degradation levels and the distribution of the remaining useful lifetime. After completing this project, we hope that some good results can be obtained. First, we could get some accurate and flexible models that can characterize the nonlinear, non-Gaussian, and multistage properties. Based on these models, we could also provide accurate distributions of the remaining useful lifetime. Second, we could discover how different degradation processes are related, and how impact processes affect degradation processes. Then the effective degradation models and remaining useful lifetime prediction methods could be proposed.

英文关键词： prognostics and health management;predictive maintenance;degradation modeling;remaining useful lifetime prediction;reliability