基于参数自适应变分模态分解的行星齿轮箱故障诊断

孙灿飞; 王友仁; 沈勇; 陈伟

doi:10.13224/j.cnki.jasp.2018.11.022

基于参数自适应变分模态分解的行星齿轮箱故障诊断

doi: 10.13224/j.cnki.jasp.2018.11.022

1.
南京航空航天大学自动化学院，南京 211106；中国航空工业集团有限公司故障诊断与健康管理技术航空科技重点实验室试验与验证中心，上海 201601
2.
南京航空航天大学自动化学院，南京 211106
3.
中国航空工业集团有限公司故障诊断与健康管理技术航空科技重点实验室试验与验证中心，上海 201601

基金项目: 中央高校基本科研业务费专项资金；国家商用飞机制造工程技术研究中心创新基金(SAMC14-JS-15-051)；航空科学基金(2013ZD52055)；江苏省普通高校研究生科研创新计划资助项目(KYLX16_0336)

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出版历程
- 收稿日期: 2017-07-18
- 刊出日期: 2018-11-28

Fault diagnosis of planetary gearbox based on adaptive parameter variational mode decomposition

摘要

摘要: 针对变分模态分解需要人为设定模态数量以及在强噪声情况下容易造成分解错误的问题，提出了依据功率谱密度极值点自适应确定模态数量与中心频率的参数自适应变分模态分解方法，通过信号仿真分析验证了方法的有效性。基于参数自适应变分模态分解提出了一种行星齿轮箱故障诊断方法，应用于行星齿轮箱第2级太阳轮裂纹的故障诊断，行星齿轮箱传动实验台的试验结果表明：该方法能实现振动信号准确分解，有效提取和辨别出故障特征频率，实现了在强背景噪声和微弱故障信号情况下对第2级太阳轮裂纹故障的准确诊断。
- 行星齿轮箱 /
- 故障诊断 /
- 参数估计 /
- 变分模态分解 /
- 频谱分析
Abstract: In order to solve the problems of variational mode decomposition, including presetting parameter of mode number and failure liability in signal decomposition under the condition of strong noise, an improved method for determining the number of modal decomposition modes and the center of frequency band based on the extreme point of power spectral density was proposed. The effectiveness of the method was verified by signal simulation analysis. Based on the adaptive parameter variational mode decomposition, a fault diagnosis procedure was applied to diagnose the second level sun gear crack of planetary gearbox test platform. Test results proved that the method can accurately decompose the vibration signal, effectively extract and identify the fault characteristic frequency, and achieve accurate diagnosis of the second-stage sun gear crack fault under the condition of strong background noise and weak fault signal.
- planetary gearbox /
- fault diagnosis /
- parameter estimation /
- variational mode decomposition /
- frequency spectrum analysis

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参考文献(18)

[1]	孙灿飞,王友仁.直升机行星传动轮系故障诊断研究进展［J］.航空学报,2017,38(7):106-119. SUN Canfei,WANG Youren.Advance in the study on fault diagnosis of helicopter planetary gears［J］.Acta Aeronautica et Astronautica Sinca,2017,38(7):106-119.(in Chinese)
[2]	ZHAO Jianmin,LI Haiping,LIU Jian,et al.Planetary gearboxes fault diagnosis based on EMD and EDT［R］.Beijing：Prognostics and System Health Management Conference,2015.
[3]	SMITH J S.The local mean decomposition and itsapplication to EEG perception data［J］.Journal of the Royal Society Interface,2005,2(5):443-454.
[4]	FREI M G,OSORIO I.Intrinsic time-scale decomposition:analysis and real-time filtering of non-stat-ionary signals［J］.Proceedings of the Royal Society,2007,463:321-342.
[5]	李志农,朱明,褚福磊,等.基于经验小波变换的机械故障诊断方法研究［J］.仪器仪表学报,2014,35(11):2423-2432.LI Zhinong,ZHU Ming,CHU Fulei,et al.Mechanical fault diagnosis method based on empirical wavelet transform［J］.Chinese Journal of Scientific Instrument,2014,35(11):2423-2432.（in Chinese）
[6]	DRAGOMIRESTKIY K,ZOSSO D.Variational mode decomposition［J］.IEEE Transactions on Signal Processing,2014,62(3):531-54.
[7]	刘长良,武英杰,甄成刚.基于变分模态分解和模糊C均值聚类的滚动轴承故障诊断［J］.中国电机工程学报,2015,35(13):3358-3365.LIU Changliang,WU Yingjie,ZHEN Chenggang.Rolling bearing fault diagnosis based on variational mode decomposition and fuzzy c means clustering［J］.Proceedings of the CSEE,2015,35(13):3358-3365.（in Chinese）
[8]	ZHANG Ming,JIANG Zhinong,FENG Kun.Research on variational mode decomposition in rolling bearings fault diagnosis of the multistage centrifugal pump［J］.Mechanical Systems and Signal Processing,2017,93:460-493.
[9]	唐贵基,王晓龙.参数优化变分模态分解方法在滚动轴承早期故障诊断中的应用［J］.西安交通大学学报,2015,49(5):73-81.TANG Guiji,WANG Xiaolong.Parameter optimized variational mode decomposition method with application to incipient fault diagnosis of rolling bearing［J］.Journal of Xian Jiaotong University,2015,49(5):73-81.（in Chinese）
[10]	刘尚坤,唐贵基,王晓龙.基于改进变分模态分解的旋转机械故障时频分析方法［J］.振动工程学报,2016,29(6):1119-1126.LIU Shangkun,TANG Guiji,WANG Xiaolong.Time frequency analysis method for rotary mechanical fault based on improved variational mode decomposition［J］.Journal of Vibration Engineering,2016,29(6):1119-1126.(in Chinese)
[11]	WANG Yanxue,LIU Fuyun,JIANG Zhansi,et al.Complex variational mode decomposition for signal processing applications［J］.Mechanical Systems and Signal Processing,2017,86:75-85.
[12]	WANG Yanxue,MARKERT R.Filter bank propertyof variational mode decomposition and its applications［J］.Signal Processing,2015,120:509-521.
[13]	INALPOLAT M,KAHRAMAN A.A theoretical andexperimental investigation of modulation sidebandsof planetary gear sets［J］.Journal of Sound and Vibration,2009,323(3/4/5):677-696.
[14]	雷亚国,汤伟,孔德同.基于传动机理分析的行星齿轮箱振动信号仿真及其故障诊断［J］.机械工程学报,2014,50(17):61-68.LEI Yaguo,TANG Wei,KONG Detong.Vibration signal simulation and fault diagnosis of planetary gearboxes based on transmission mechanism analysis［J］.Journal of Mechanical Engineering,2014,50(17):61-68.(in Chinese)
[15]	FENG Zhipeng,ZUO Mingjian,QU Jian,et al.Joint amplitude and frequency demodulation analysis based on local mean decomposition for fault diagnosis of planetary gearboxes［J］.Mechanical Systems and Signal Processing,2013,40(1):56-75.
[16]	FENG Zhipeng,ZUO Mingjian.Vibration signal models for fault diagnosis of planetary gearboxes［J］.Journal of Sound and Vibration,2012,331(22):4919-4939.
[17]	冯志鹏,赵镭镭,褚福磊.行星齿轮箱故障诊断的幅值解调分析方法［J］.中国电机工程学报,2013,33(8):107-111.FENG Zhipeng,ZHAO Leilei,ZHU Fulei.Amplitude demodulation analysis method for fault diagnosis planetary gearboxes［J］.Proceedings of the CSEE,2013,33(8):107-111.(in Chinese)
[18]	冯志鹏,褚福磊.行星齿轮箱故障诊断的频率解调分析方法.中国电机工程学报,2013,33(11):112-117.FENG Zhipeng,ZHU Fulei.Frequency demodulationanalysis method for fault diagnosis of planetary gearboxes［J］.Proceedings of the CSEE,2013,33(11):112-117.(in Chinese)