计算机集成制造系统 ›› 2022, Vol. 28 ›› Issue (5): 1314-1336.DOI: 10.13196/j.cims.2022.05.005

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工业大数据驱动的故障预测与健康管理

金晓航1,2,王宇3,ZHANG Bin4   

  1. 1.浙江工业大学机械工程学院
    2.浙江工业大学特种装备制造与先进加工技术教育部重点实验室
    3.西安交通大学机械制造系统工程国家重点实验室
    4.南卡罗来纳大学电气工程系
  • 出版日期:2022-05-30 发布日期:2022-06-10
  • 基金资助:
    国家重点研发计划资助项目(2022YFE0198900);国家自然科学基金资助项目(51505424,51875437);宁波市自然科学基金资助项目(2021J038)。

Industrial big data-driven fault prognostics and health management

  • Online:2022-05-30 Published:2022-06-10
  • Supported by:
    Project supported by the National Key Research and Development Program,China(No.2022YFE0198900),the National Natural Science Foundation,China (No.51505424,51875437),and the Natural Science Foundation of Ningbo City,China (No.2021J038).

摘要: 新一代人工智能技术的发展与应用装备积累了大量数据,推动着故障预测与健康管理(PHM)进入了工业大数据时代。结合装备的功能作用、结构组成和工作特点,分析装备大数据,进行价值挖掘、信息提取进而实现装备的状态监测、异常预警、故障诊断、寿命预测、智能维护等工作十分迫切。在回顾并剖析当前PHM技术内涵、发展现状与应用的同时讨论了装备工业大数据的特点、分析方法及其工作中的难点和疑点。以风力发电机组和机械硬盘两类典型复杂装备为例,从工业大数据角度对其PHM技术进行探讨,总结当前研究工作的热点与不足,思考未来研究方向,以期为相关领域的研究人员提供一定参考。

关键词: 故障预测与健康管理, 工业大数据, 风力发电机组, 机械硬盘

Abstract: With the development and application of  artificial intelligence technology,equipment has accumulated massive amount of industrial big data,which pushed the equipment Prognostics and Health Management (PHM) technology into the era of industrial big data.There had great economic and social value to extract useful information in industrial big data for PHM by combining with the function,structure and working characteristics of the equipment.The development and application of PHM technology were reviewed,and the industrial big data analysis methods were discussed.Two case studies of unity-scale wind turbines and hard disk drives in big data environments were presented to demonstrate the advantages of industrial big data-driven PHM,which could provide a reference for researchers in related fields.

Key words: prognostics and health management, industrial big data, wind turbine, hard disk drive

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