摘要
随着工业4.0技术的发展,越来越多的公司应用传感器和信息技术来采集生产过程中各个阶段的数据。同时,诸如大数据、物联网(IoT)、服务互联网(IoS)、人工智能(AI)和数据挖掘(DM)等技术也被用于进一步的数据分析和开发更具有适应性和智能的预测性维修策略和系统。深度学习算法技术已在预测性维修中发挥着非常重要的作用,本文介绍了最新深度学习技术在实现预测性维护策略中的应用。
With the development of Industry 4.0,companies are increasingly applying sensors and information technologies to capture data at all stages of production.Simultaneously,technologies such as Big data,Internet of Things (IoT),Internet of Services (IoS),Artificial intelligence (AI),and data mining (DM),are being used to facilitate a more adaptable and smart maintenance policy.The deep learning algorithms has been playing a very important role in predictive maintenance.This paper presents a review of deep leaning application in realizing predictive maintenance policy.
作者
王毅
戴国洪
王克胜
WANG Yi;DAI Guohong;WANG Kesheng(School of Business,Plymouth University,Plymouth,Devon PL4 8AA,UK;School of Mechanical Engineering,Changzhou University,Changzhou 213164,China;Norwegian University of Science and Technology,Trondheim NO-7491,Norway)
出处
《常州大学学报（自然科学版）》
CAS
2019年第3期1-22,共22页
Journal of Changzhou University：Natural Science Edition
关键词
深度学习
计算智能
人工智能
预测性维修
故障诊断和预测
deep learning
computational intelligence
artificial intelligence
predictive maintenance
diagnosis and prognosis
