Research on Equipment Health Evaluation Method Based on Fault Case Learning

被引：0
作者：
Wang Q. [1 ]
Li Z. [1 ]
Xu S. [2 ]
Chen W. [2 ]
机构：
[1] Diagnosis and Self-recovering Research Center, Beijing University of Chemical Technology, Beijing
[2] State Key Laboratory of Safety and Control for Chemicals, SINOPEC Research Institute of Safety Engineering, Qingdao
来源：
Wang, Qingfeng (wangqf2422@163.com) | 1600年 / Chinese Mechanical Engineering Society卷 / 56期
关键词：
Case study; Health evaluation; Health index model; Health rating criteria; Predictive maintenance;
D O I：
10.3901/JME.2020.20.028
中图分类号：
学科分类号：
摘要：
Analyzing and extracting fault feature information from equipment condition monitoring data to accurately and quickly identify equipment health status is very important for carrying out predictive maintenance and ensuring equipment operation reliability and safety. Taking the centrifugal compressor as the research object and taking the vibration monitoring data of the normal state of the equipment as the reference data,the correlation health index model,the coherence health index model,and the spectral distance health index model applying with the normal state original signal and the real-time monitoring signal are constructed. Based on a large number of failure case studies for the three health index models and statistical analysis of health degree distribution,equipment health rating criteria are developed,a data-driven mechanical equipment health evaluation method is formed,and the mapping relationship between centrifugal compressor health degree characterization and running status is revealed. The bearing experiment data and centrifugal compressor rotor imbalance failure data are used to verify the accuracy and applicability of the constructed equipment health index model and health rating criteria,respectively. The results show that the constructed health index models can better characterize the operating state of the equipment. Compared with the fixed threshold alarm methods of effective value and peak-peak,the constructed health evaluation criteria for mechanical equipment is more practical for guiding predictive maintenance. © 2020 Journal of Mechanical Engineering.
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页码：28 / 37
页数：9
相关论文
共 20 条
  • [1] LEI Yaguo, JIA Feng, KONG Detong, Et al., Opportunities and challenges of machinery intelligent fault diagnosis in big data era, Journal of Mechanical Engineering, 54, 5, pp. 94-104, (2018)
  • [2] ABICHOU B, VOISIN A, IUNG B., Choquet integral capacity calculus for health index estimation of multi-level industrial systems[J], Ima Journal of Management Mathematics, 2, pp. 205-224, (2015)
  • [3] LEI Yaguo, LI Naipeng, GUO Liang, Et al., Machinery health prognostics:A systematic review from data acquisition to RUL prediction, Mechanical Systems and Signal Processing, 104, pp. 799-834, (2018)
  • [4] CHEN X, SHEN Z, HE Z, Et al., Remaining life prognostics of rolling bearing based on relative features and multivariable support vector machine[J], ARCHIVE Proceedings of the Institution of Mechanical Engineers, Part C:Journal of Mechanical Engineering Science 1989-1996, 227, 12, pp. 2849-2860, (2013)
  • [5] LEI Yaguo, LI Naipeng, LIN Jing, A new method based on stochastic process models for machine remaining useful life prediction, IEEE Transactions on Instrumentation and Measurement, 65, 12, pp. 2671-2684, (2016)
  • [6] LI Naipeng, LEI Yaguo, LIN Jing, Et al., An improved exponential model for predicting remaining useful life of rolling element bearings[J], IEEE Transactions on Industrial Electronics, 62, 12, pp. 7762-7773, (2015)
  • [7] CHEN X, SHEN Z, HE Z, Et al., Remaining life prognostics of rolling bearing based on relative features and multivariable support vector machine[J], Proceedings of the Institution of Mechanical Engineers,Part C:Journal of Mechanical Engineering Science, 227, 12, pp. 2849-2860, (2013)
  • [8] MA Lun, KANG Jianshe, ZHAO Chunyu, Research on condition monitoring of bearing health using vibration data[J], Applied Mechanics and Materials, 226-228, pp. 340-344, (2012)
  • [9] ZHAO Shuai, HUANG Yixiang, WANG Haoren, Laplacian eigenmaps and Mahalanobis distance based health assessment methodology for ball screw, Journal of Mechanical Engineering, 53, 15, pp. 125-130, (2017)
  • [10] HE Zhengjia, CAO Hongrui, ZI Yanyang, Et al., Development and thoughts of operational reliability assessment of mechanical equipment, Journal of Mechanical Engineering, 50, 2, pp. 171-186, (2014)
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