| 工业人工智能的关键技术及其在预测性维护中的应用现状 |
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| 引用本文： | 袁烨, 张永, 丁汉. 工业人工智能的关键技术及其在预测性维护中的应用现状. 自动化学报, 2020, 46(10): 2013−2030 doi: 10.16383/j.aas.c200333 |
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| 作者姓名： | 袁烨 张永 丁汉 |
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| 作者单位： | 1.华中科技大学人工智能与自动化学院 武汉 430074;;2.武汉科技大学信息科学与工程学院 武汉 430081;;3.华中科技大学机械科学与工程学院 武汉 430074 |
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| 基金项目： | 国家自然科学基金(9174812, 61873197), 江苏省重点研发计划(BE2017002)资助 |
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| 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.
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| 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 |
| 收稿时间： | 2020-05-20 |
Research on Key Technology of Industrial Artificial Intelligence and Its Application in Predictive Maintenance |
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| Yuan Ye, Zhang Yong, Ding Han. Research on key technology of industrial artificial intelligence and its application in predictive maintenance. Acta Automatica Sinica, 2020, 46(10): 2013−2030 doi: 10.16383/j.aas.c200333 |
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| Authors: | YUAN Ye ZHANG Yong DING Han |
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| Affiliation: | 1. School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074;;2. School of Information Science and Technology, Wuhan University of Science and Technology, Wuhan 430081;;3. School of Mechanical Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 |
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| Abstract: | 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. |
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| Keywords: | Industrial artificial intelligence (IAI) predictive maintenance machine learning remaining useful life prediction maintenance strategy |
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