摘要
随着人工智能技术的快速发展及其在工业系统中卓有成效的应用,工业智能化成为当前工业生产转型的一个重要趋势.论文提炼了工业人工智能(Industrial artificial intelligence,IAI)的建模、诊断、预测、优化、决策以及智能芯片等共性关键技术,总结了生产过程监控与产品质量检测等4个主要应用场景.同时,论文选择预测性维护作为工业人工智能的典型应用场景,以工业设备的闭环智能维护形式,分别从模型方法、数据方法以及融合方法出发,系统的总结和分析了设备的寿命预测技术和维护决策理论,展示了人工智能技术在促进工业生产安全、降本、增效、提质等方面的重要作用.最后,探讨了工业人工智能研究所面临的问题以及未来的研究方向.
With the rapid development of artificial intelligence technology and its effective application in industrial system,industrial intelligentization has become an important trend of current industrial production transformation.In this paper,the general key technologies of industrial artificial intelligence(IAI)such as modeling,diagnosis,prediction,optimization,decision and intelligent chip are extracted,and four main application scenarios including production process monitoring and product quality detection are summarized.Then,predictive maintenance of industrial equipment in this paper is selected as a typical application scenario.Starting from model,data and fusion method,respectively,both remaining useful life prediction and maintenance decision are systematically analyzed and summarized with the form of closed-loop intelligent maintenance.Especially,the important role of artificial intelligence technology in promoting industrial production safety,cost reduction,efficiency enhancement and quality improvement has been verified.Finally,both existing problems and future research direction of IAI is also discussed.
作者
袁烨
张永
丁汉
YUAN Ye;ZHANG Yong;DING Han(School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074;School of Information Science and Technology,Wuhan University of Science and Technology,Wuhan 430081;School of Mechanical Science and Technology,Huazhong University of Science and Technology,Wuhan 430074)
出处
《自动化学报》
EI
CSCD
北大核心
2020年第10期2013-2030,共18页
Acta Automatica Sinica
基金
国家自然科学基金(9174812,61873197)
江苏省重点研发计划(BE2017002)资助。
关键词
工业人工智能
预测性维护
机器学习
寿命预测
维修决策
Industrial artificial intelligence(IAI)
predictive maintenance
machine learning
remaining useful life prediction
maintenance strategy
