装备系统剩余使用寿命预测技术研究进展
作者:
作者单位:

1.合肥工业大学计算机与信息学院,合肥 230009;2.哈工大机器人(合肥)国际创新研究院,合肥 230601;3.天津津航技术物理研究所,天津 300192;4.北京机电工程研究所,北京 100074

作者简介:

郭忠义,男,1981年2月生,教授,黄山青年学者,主要研究方向:新型光通信技术,涡旋雷达系统及应用,智能传感信息系统及应用,偏振智能信息及应用。曾获山东省高等学校优秀科研成果奖三等奖,威海市科学技术奖二等奖,威海市第九届自然科学优秀学术成果奖一等奖,威海市第十届自然科学优秀学术成果奖二等奖。

通讯作者:

郭忠义,E-mail: guozhongyi@hfut.edu.cn。

中图分类号:

TH166

基金项目:

国家自然科学基金(61775050)。


Research Progress on Remaining Useful Life Prediction Technology of Equipment Systems
Author:
Affiliation:

1.School of Computer and Information, Hefei University of Technology, Hefei 230009, China;2.HRG International Institute (Hefei) of Research and Innovation, Hefei 230601, China;3.Tianjin Jinhang Institute of Technical Physics, Tianjin 300192, China;4.Beijing Electro-Mechanical Engineering Institute, Beijing 100074, China

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    摘要:

    社会的稳定发展离不开制造业的高水平发展,生产是制造业的关键步骤,长期持续稳定的产出依赖于装备系统的稳定运行。系统故障引起的停产势必会造成一定的经济损失。如何尽早地发现装备系统的故障来避免停工停产带来的经济损失,已经成为了当前应用研究中的热点。采用定期人工检查的传统方法不仅提高了生产成本,还使得问题发现较为滞后,达不到实时监控的目的。而且,随着信息技术的高速发展,装备系统的监测也变得更加智能化。利用装备系统的历史数据检测其状态能够更敏捷、更高效地发现装备运行中的“亚健康”问题,能给装备管理者提供有益的决策支持。基于装备剩余使用寿命的数据预测,能够提供高效智能的解决方案,在工业领域有着宽广的应用前景。因此,本文聚焦于装备系统剩余使用寿命预测技术的研究进展,对近年来剩余使用寿命预测的研究进行归纳总结,并讨论各剩余使用寿命预测理论与方法的优缺点。最后,总结并展望装备系统剩余使用寿命预测技术的未来研究方向和发展趋势。

    Abstract:

    The stable development of society is inseparable from the high-level developments of manufacturing industry. Production is the key point of manufacturing industry, and the long-term sustainable and stable output depends on the stable operation of industrial equipment systems. The production stoppage caused by systems’ failure will be bound to the economic loss. How to find the equipment system’s failure to avoid the economic loss as soon as possible has become a hotspot in the current application research. The traditional method of regular manual inspection not only increases the production cost, but also delays the finding of problems and fails to achieve the real-time monitoring purpose. Besides, with the rapid developments of information technology, the monitoring of equipment systems has become increasingly intelligent. Using the historical data of the equipment system to detect its status is a more agile and more efficient way to find the “sub-health” problems during operation. It can provide beneficial decision support for equipment administrators. Data of the remaining useful life (RUL) prediction of the equipments can provide efficient and intelligent solutions, and has broad application prospects in the industrial field. Therefore, we focus on the research progress of the RUL prediction technology for the equipment systems in recent years. We summarize studies on RUL, and discuss the advantages and disadvantages of the RUL prediction’s theories and methods. Finally, we identify the future research direction and development trend of the RUL prediction technology for equipment systems.

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郭忠义,李永华,李关辉,彭志勇,张宁,于振中.装备系统剩余使用寿命预测技术研究进展[J].南京航空航天大学学报,2022,54(3):341-364

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  • 收稿日期:2022-04-30
  • 最后修改日期:2022-05-31
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  • 在线发布日期: 2023-02-22
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