A PSO-NLM Weight Curve Envelope Analysis Method for Fault Diagnosis of Check Valve
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摘要: 针对单向阀受大量背景噪声干扰致使其故障特征难以提取的问题，提出一种粒子群算法（Particle swarm optimization, PSO）寻找非局部均值（Non-local mean, NLM）最优参数，对最优参数NLM权值曲线作包络分析的单向阀故障诊断方法。首先，运用粒子群优化算法以NLM滤波后信号的包络熵最小作为目标函数选取参数；其次，对于NLM算法取平均值的特性在滤波处理时会将部分冲击特征均值化，直接利用最优参数NLM加权运算得到的信号样本点权值分布曲线作为处理信号，从权重角度使故障冲击得到增强；最后，对权值分布曲线进行希尔伯特包络分析进而得到诊断结果。工程数据验证表明，提出的方法能更精准的提取到单向阀故障特征频率。Abstract: Aiming at the problem that the check valve is interfered by a large amount of background noise, which makes it difficult to extract the fault characteristics, a particle swarm optimization (PSO) non-local mean (NLM) weighted envelope analysis method for check valve fault diagnosis is proposed in this paper. First, the particle swarm optimization algorithm uses the minimum envelope entropy of the signal after NLM filtering as the objective function selection parameter; secondly, the averaging characteristic of the NLM algorithm will average some impact features during the filtering process, and directly use the weight distribution curve of the signal sample points obtained by the NLM weighting operation is used as the processing signal to enhance the fault impact from the perspective of weight; finally, the weight distribution curve is subjected to Hilbert envelope analysis to obtain the diagnosis result. Engineering data verification shows that the proposed method can more accurately extract the fault characteristic frequency of the check valve.
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Key words:
- check valve /
- particle swarm optimization algorithm /
- non-local mean /
- weight curve /
- fault diagnosis
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[1] 张德山. 矿浆管道输送技术的发展与展望[J]. 现代国企研究, 2016(4): 212-213ZHANG D S. Development and prospect of slurry pipeline transportation technology[J]. Modern SOE Research, 2016(4): 212-213 (in Chinese) [2] 马军. 往复式高压隔膜泵单向阀状态监测及故障诊断研究 [D]. 昆明: 昆明理工大学, 2016MA J. Research on Condition monitoring and fault diagnosis of check valve of reciprocating high-pressure diaphragm Pump [D]. Kunming: Kunming University of Science and Technology, 2016 (in Chinese) [3] 牟竹青, 黄国勇, 吴建德, 等. 基于DEMD的高压隔膜泵单向阀早期故障诊断[J]. 振动、测试与诊断, 2018, 38(4): 758-764MU Z Q, HUANG G Y, WU J D, et al. Early fault diagnosis of high pressure diaphragm pump check valve based on differential empirical mode decomposition[J]. Journal of Vibration, Measurement & Diagnosis, 2018, 38(4): 758-764 (in Chinese) [4] 张丹威, 王晓东, 黄国勇. 相关系数SVD增强随机共振的单向阀故障诊断[J]. 电子学报, 2018, 46(11): 2696-2704 doi: 10.3969/j.issn.0372-2112.2018.11.017ZHANG D W, WANG X D, HUANG G Y, et al. Check valve fault diagnosis with correlation coefficient SVD enhanced stochastic resonance[J]. Acta Electronica Sinica, 2018, 46(11): 2696-2704 (in Chinese) doi: 10.3969/j.issn.0372-2112.2018.11.017 [5] LV Y, ZHU Q L, YUAN R. Fault diagnosis of rolling bearing based on fast nonlocal means and envelop spectrum[J]. Sensors, 2015, 15(1): 1182-1198 doi: 10.3390/s150101182 [6] BUADES A, COLL B, MOREL J M. A review of image denoising algorithms, with a new one[J]. Multiscale Modeling & Simulation, 2006, 4(2): 490-530 [7] TRACEY B H, MILLER E L. Nonlocal means denoising of ECG signals[J]. IEEE Transactions on Biomedical Engineering, 2012, 59(9): 2383-2386 doi: 10.1109/TBME.2012.2208964 [8] VAN M, KANG H J, SHIN K S. Rolling element bearing fault diagnosis based on non-local means de-noising and empirical mode decomposition[J]. IET Science, Measurement & Technology, 2014, 8(6): 571-578 [9] 张龙, 胡俊锋, 熊国良. 基于加权非局部平均算法的滚动轴承故障诊断[J]. 振动与冲击, 2016, 35(19): 156-161ZHANG L, HU J F, XIONG G L. Fault diagnosis of rolling bearings based on weighted nonlocal means algorithm[J]. Journal of Vibration and Shock, 2016, 35(19): 156-161 (in Chinese) [10] 唐晓红, 胡俊锋, 熊国良, 等. 自适应非局部均值及在轴承故障检测中的应用[J]. 振动、测试与诊断, 2019, 39(1): 61-67TANG X H, HU J F, XIONG G L, et al. Adaptive non-local means with applications in fault detection of rolling bearings[J]. Journal of Vibration, Measurement & Diagnosis, 2019, 39(1): 61-67 (in Chinese) [11] 万书亭, 彭勃. 基于非局部均值去噪和快速谱相关的滚动轴承早期故障诊断方法[J]. 中南大学学报(自然科学版), 2020, 51(1): 76-85 doi: 10.11817/j.issn.1672-7207.2020.01.010WAN S T, PENG B. Early fault diagnosis method of rolling bearing based on nonlocal mean denoising and fast spectral[J]. Journal of Central South University (Science and Technology), 2020, 51(1): 76-85 (in Chinese) doi: 10.11817/j.issn.1672-7207.2020.01.010 [12] 施杰, 伍星, 柳小勤, 等. 变分模态分解结合深度迁移学习诊断机械故障[J]. 农业工程学报, 2020, 36(14): 129-137 doi: 10.11975/j.issn.1002-6819.2020.14.016SHI J, WU X, LIU X Q, et al. Mechanical fault diagnosis based on variational mode decomposition combined with deep transfer learning[J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(14): 129-137 (in Chinese) doi: 10.11975/j.issn.1002-6819.2020.14.016 [13] 潘峰, 安启超, 刁奇, 等. 基于粒子群算法的多尺度反卷积特征融合的道路提取[J]. 北京理工大学学报, 2020, 40(6): 640-647PAN F, AN Q C, DIAO Q, et al. Road extraction based on PSO different ratio deconvolution feature fusion[J]. Transactions of Beijing Institute of Technology, 2020, 40(6): 640-647 (in Chinese) [14] 蒋永华, 汤宝平, 刘文艺, 等. 基于参数优化Morlet小波变换的故障特征提取方法[J]. 仪器仪表学报, 2010, 31(1): 56-60JIANG Y H, TANG B P, LIU W Y, et al. Feature extraction method based on parameter optimized Morlet wavelet transform[J]. Chinese Journal of Scientific Instrument, 2010, 31(1): 56-60 (in Chinese) [15] 李洋, 焦宗夏, 吴帅. 应用单向阀配流的高频往复泵的流量特性分析及优化设计[J]. 机械工程学报, 2013, 49(14): 154-163 doi: 10.3901/JME.2013.14.154LI Y, JIAO Z X, WU S. Flow characteristics analysis and optimization design of high frequency reciprocation pump applying check valve to rectification[J]. Journal of Mechanical Engineering, 2013, 49(14): 154-163 (in Chinese) doi: 10.3901/JME.2013.14.154 [16] VAN DE VILLE D, KOCHER M. SURE-based non-local means[J]. IEEE Signal Processing Letters, 2009, 16(11): 973-976 doi: 10.1109/LSP.2009.2027669 [17] VAN DE VILLE D, KOCHER M. Nonlocal means with dimensionality reduction and SURE-based parameter selection[J]. IEEE Transactions on Image Processing, 2011, 20(9): 2683-2690 doi: 10.1109/TIP.2011.2121083 -
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