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YANG Jingzong, SHI Chunchao, YANG Tianqing, LI Changfang. Research on fault diagnosis method based on LMD and grey correlation degree[J]. Manufacturing Technology & Machine Tool, 2022, (1): 158-164. doi: 10.19287/j.cnki.1005-2402.2022.01.029
Citation: YANG Jingzong, SHI Chunchao, YANG Tianqing, LI Changfang. Research on fault diagnosis method based on LMD and grey correlation degree[J]. Manufacturing Technology & Machine Tool, 2022, (1): 158-164. doi: 10.19287/j.cnki.1005-2402.2022.01.029

Research on fault diagnosis method based on LMD and grey correlation degree

doi: 10.19287/j.cnki.1005-2402.2022.01.029
Funds:

 2019FH001-121

 202109

  • Received Date: 2021-10-19
    Available Online: 2022-03-07
  • Aiming at the nonstationary characteristics of the fault vibration signal of high pressure diaphragm pump check valve, a fault diagnosis method based on local meandecomposition (LMD) and grey correlation theory is proposed. Firstly, LMD is used to decompose the vibration signals of the check valve of high pressure diaphragm pump under different operating conditions into multiple product functions. Then the cross-correlation coefficients of all product functions are calculated, and the product functions with high cross-correlation degree are selected to extract the corresponding feature vectors. Finally, the grey correlation theory is introduced to construct the fault diagnosis and identification model of one-way valve, and the results are compared with those obtained by empirical mode decomposition (EMD), mixed feature modeling and single feature modeling. The experimental results show that the proposed method can decompose the fault signal of one-way valve well, and effectively identify the fault signal of one-way valve under the condition of small samples.

     

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  • [1]
    Cattermole K W. The fourier transform and its applications[J]. Electronics & Power, 2009, 11(10): 357-359.
    [2]
    Griffin D, Lim J S. Signal estimation from modified short-time fourier transform[J]. IEEE Transactions on Acoustics Speech & Signal Processing, 1984, 32(2): 236-243.
    [3]
    Georgakis A, Stergioulas L K, et al. Wigner filtering with smooth roll-off boundary for differentiation of noisy non-stationary signals[J]. Signal Processing, 2002, 82(10): 1411-1415. doi: 10.1016/S0165-1684(02)00215-3
    [4]
    Smith J S. The local mean decomposition and its application to EEG perception data[J]. Journal of the Royal Society Interface, 2005, 2(5): 443-454. doi: 10.1098/rsif.2005.0058
    [5]
    Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings Mathematical Physical & Engineering Sciences, 1998, 454(1971): 903-995.
    [6]
    林江刚, 胡正新, 李晶, 等. 低转速下基于AE信号与LMD的滚动轴承故障诊断[J]. 动力工程学报, 2019, 39(4): 293-298. doi: 10.3969/j.issn.1674-7607.2019.04.006
    [7]
    沈超, 杨建伟, 姚德臣, 等. 基于改进局部均值分解和流形学习的齿轮故障诊断研究[J]. 机械传动, 2018, 42(1): 137-142. https://www.cnki.com.cn/Article/CJFDTOTAL-JXCD201801029.htm
    [8]
    王名月, 缪炳荣, 李旭娟, 等. 基于LMD样本熵和RBF网络的结构损伤识别研究[J]. 机械强度, 2018, 40(3): 522-527. https://www.cnki.com.cn/Article/CJFDTOTAL-JXQD201803004.htm
    [9]
    王海军, 李康, 练继建. 基于数据融合和LMD的厂房结构动参数识别研究[J]. 振动与冲击, 2018, 37(2): 175-181. https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCJ201802026.htm
    [10]
    孙曙光, 张强, 杜太行, 等. 基于灰色关联度的框架式断路器故障诊断方法[J]. 仪器仪表学报, 2017(10): 177-187. https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB201710022.htm
    [11]
    于大程, 朱晨光, 张铭钧. 自主式水下机器人推进器弱故障辨识方法[J]. 哈尔滨工程大学学报, 2020(8): 1223-1229. https://www.cnki.com.cn/Article/CJFDTOTAL-HEBG202008021.htm
    [12]
    杨超, 杨晓霞. 基于灰色关联度和Teager能量算子的轴承早期故障诊断[J]. 振动与冲击, 2020, 39(13): 224-229. https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCJ202013033.htm
    [13]
    刘建锋, 张科曌, 田权, 等. 基于序电流灰色关联分析与多信息融合的广域后备保护算法[J]. 电力系统保护与控制, 2018, 46(19): 19-25. doi: 10.7667/PSPC171422
    [14]
    Qiu B, Wang F, Li Y, et al. Research on method of simulation model validation based on improved grey relational analysis[J]. Physics Procedia, 2012, 25: 1118-1125. doi: 10.1016/j.phpro.2012.03.208
    [15]
    梁涛, 杨改文, 董玉兰, 等. 基于灰色关联度的变权组合模型的齿轮箱温度故障预测[J]. 太阳能学报, 2020, 41(12): 199-207. https://www.cnki.com.cn/Article/CJFDTOTAL-TYLX202012028.htm
    [16]
    Li Y, Jiao S, Geng B. A comparative study of four multi-scale entropies combined with grey relational degree in classification of ship-radiated noise[J]. Applied Acoustics, 2021, 176(4): 107865.
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