基于机器学习算法的寿命预测与故障诊断技术应用与发展综述

A Survey of Application and Development ofLife Prediction and Fault Diagnosis Technology Based on

摘要:

寿命预测与故障诊断作为复杂装备系统可靠性分析中的两类重要问题，基于数据驱动的机器学习分析方法具有良好的工程效果。本文系统地从故障预测与寿命估算及后续健康管理的实际工程需求出发，深入分析该类型系统因性能衰退出现的早期故障诊断与维护时间确定的共性难点问题并深度挖掘其所对应的关键科学问题，对机器学习算法在其中的应用与研究进行综述，重点阐述了人工神经网络、支持向量机等机器学习算法，对于完善可靠性分析方法，进一步推动机器学习算法在可靠性工程领域的运用具有一定的指导意义。

Abstract:

Life prediction and fault diagnosis are two important problems in the reliability analysis of complex equipment systems, and The data-driven machine learning analysis method has good engineering effects. Based on the actual engineering requirements of fault prediction, life estimation and subsequent health management，this paper systematically analyzes the common emblems of early fault diagnosis and maintenance time determination due to performance degradation and deeply explores the key scientific problems. We review the application and research of machine learning algorithms, and focuses on machine learning algorithms such as artificial neural networks and support vector machines. It is necessary to improve the reliability analysis method and further promote the application of machine learning algorithms in the field of reliability engineering.