机器学习在故障检测与诊断领域应用综述

Overview of Application of Fault Detection and Diagnosis Based on Machine Learning

机器学习已经成为当前技术发展热点,由于机器学习具有快速处理大量数据、分析提取有效信息等优点,因此在故障检测与诊断技术中受到了越来越多的关注;文章系统介绍了机器学习和故障检测与诊断的概念、分类,深入了解了基于PCA和随机森林的故障检测方法和国内研究现状,以及基于决策树、支持向量机以及神经网络的故障诊断方法和国内外研究现状,其中重点介绍了卷积神经网络和递归神经网络的应用,并对机器学习算法在故障检测与诊断应用前景进行了展望,大数据时代下,机器学习在故障检测和诊断领域有着绝对优势。

Machine Learning has been a popular and well-investigated topic technology,especially because machine learning has the advantages of fast processing large amounts of data,analyzing and extracting effective information and so on,it has more and more attention to fault detection and diagnosis.This paper systematically analyzes the concepts and classifications of machine learning and fault detection and diagnosis,and deeply comprehends the method of fault detection and diagnosis based on machine learning.Then it focuses on the fault detection methods including PCA and random forests and the research status at home and abroad;it also introduces fault diagnosis methods including decision trees,support vector machines and neural networks and the research status at home and abroad,especially convolutional neural networks and recurrent neural networks,discusses its of future applications in fault detection and diagnosis.In the era of big data,machine learning has absolute advantages in the field of fault detection and diagnosis.