[1]王 毅,戴国洪,王克胜.深度学习技术在预测维修中的应用综述[J].常州大学学报(自然科学版),2019,31(03):1-22.[doi:10.3969/j.issn.2095-0411.2019.03.001]
 WANG Yi,DAI Guohong,WANG Kesheng.A Review on Deep Learning Techniques Applied to Predictive Maintenance[J].Journal of Changzhou University(Natural Science Edition),2019,31(03):1-22.[doi:10.3969/j.issn.2095-0411.2019.03.001]
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深度学习技术在预测维修中的应用综述()
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常州大学学报(自然科学版)[ISSN:2095-0411/CN:32-1822/N]

卷:
第31卷
期数:
2019年03期
页码:
1-22
栏目:
特约稿
出版日期:
2019-05-28

文章信息/Info

Title:
A Review on Deep Learning Techniques Applied to Predictive Maintenance
文章编号:
2095-0411(2019)03-0001-22
作者:
王 毅1戴国洪2王克胜23
(1.英国普利茅斯大学 商学院,普利茅斯 德文郡 PL48AA; 2.常州大学 机械工程学院,江苏 常州 213164; 3.挪威科技大学,特隆赫姆 NO-7491)
Author(s):
WANG Yi1 DAI Guohong2 WANG Kesheng23
(1.School of Business, Plymouth University, Plymouth, Devon PL4 8AA,UK; 2. School of Mechanical Engineering, Changzhou University,Changzhou 213164,China; 3.Norwegian University of Science and Technology, Trondheim NO-7491,Norway)
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
Keywords:
deep learning computational intelligence artificial intelligence predictive maintenance diagnosis and prognosis
分类号:
TP 39
DOI:
10.3969/j.issn.2095-0411.2019.03.001
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。
Abstract:
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.

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备注/Memo

备注/Memo:
收稿日期:2018-10-06。
作者简介:WANG Yi(1978—),male, Norwegian, PhD, Lecturer, Plymouth University.
DAI Guohong(1966—), male, Chinese, PhD, Professor, Changzhou University.
Corresponding author: WANG Kesheng(1945—), male, Norwegian, Phd, Professor of Norwegian University of Science and Technology, Academician of Norwegian Technical Science of Academy. E-mail: kesheng.wang@ntnu.no
更新日期/Last Update: 2019-05-29