基于定量知识数据驱动故障诊断方法的研究综述

Research on Fault Diagnosis Method Based on Quantitative Knowledge Data Driven

基于定量知识数据驱动故障诊断方法是一种将历史数据灵活运用在故障诊断领域的关键技术之一。本文主要对基于定量知识数据驱动故障诊断中的神经网络、支持向量机、模糊控制三个方向的方法进行了全面的论述和研究,通过阐述神经网络、支持向量机、模糊控制的基本算法和理论,给出了三种方法和机器学习结合的研究成果。最后,对基于定量知识数据驱动故障诊断方法未来发展的趋势和研究方向进行了展望。

The fault diagnosis method based on quantitative knowledge data is one of the key technologies for flexible application of historical data in the field of fault diagnosis. This paper mainly elaborates and studies the three directions of the basic neural network, support vector machine and fuzzy control based on quantitative knowledge data driven fault diagnosis. By expounding the basic algorithms and theories of neural network, support vector machine and fuzzy control The research results of these three methods combined with today＇s machine learning are given. Finally, the development and research direction of fault diagnosis based on quantitative knowledge data is prospected.