基于多点噪声分析的离心泵早期汽蚀故障诊断

PDF(1139 KB)

振动与冲击 ›› 2017, Vol. 36 ›› Issue (7) : 39-44.

论文

周云龙吕远征

作者信息 +

Incipient cavitations fault diagnosis for a centrifugal pump based on multi-position noise analysis

ZHOU Yunlong1,LV Yuanzheng2

Author information +

文章历史 +

摘要

本文提出了一种多点噪声分析法研究汽蚀故障下的离心泵噪声，总结其规律并应用到故障诊断当中。将多个单指向性麦克风附着于泵体的不同部位采集信号，通过多种矩阵的奇异值分解提取高品质的水动力噪声，根据Lighthill声学理论，水动力噪声详细的反映着测点处的流场变化。出于加快计算速度、降低内存的考虑，利用二代小波提取各点噪声能量谱，并将所有测点的敏感频带共同组成特征向量以训练BP神经网络。经诊断测试，多点噪声法快速、稳定且诊断成功率达到93.5%，证明比传统噪声诊断法更适合工业用途。

Abstract

Here,an analysis method of multi-position noise was proposed for studying a centrifugal pump’s noise when cavitations occurs to summarize its law and to apply this law in its incipient cavitations fault diagnosis.Several single directional microphones were attached to different positions of the pump,the high quality hydrodynamic noise was extracted by constructing several matrices and their singular value decomposition.According to Lighthill acoustics theory,the hydrodynamic noise reflects changes of the flow field near the placed microphones.In order to speed up the calculation and reduce the memory,energy spectra of all positions of hydrodynamic noise were extracted with the second generation wavelet transformation,then the feature vectors were constructed with the sensitive frequency bands of all measured points to train a BP artificial neural network.The diagnosis results showed that the success rate of the multi-position noise analysis method is 93.5%,and it is fast and stable,it is more suitable for industrial application than the traditional noise diagnosis method be.

Key words

centrifugal pump / cavitations / hydrodynamic noise / singular value decomposition (SVD) second generation wavelet

引用本文

EndNote

Ris (Procite)

Bibtex

导出引用

周云龙吕远征. 基于多点噪声分析的离心泵早期汽蚀故障诊断[J]. 振动与冲击, 2017, 36(7): 39-44

ZHOU Yunlong1,LV Yuanzheng2. Incipient cavitations fault diagnosis for a centrifugal pump based on multi-position noise analysis[J]. Journal of Vibration and Shock, 2017, 36(7): 39-44

参考文献

[1]. 周云龙,刘永奇.基于EMD和边际谱频带能量的离心泵汽蚀故障诊断[J].化工学报,2012,63(2):545-550.
ZHOU Yunlong，LIU Yongqi.Fault diagnosis of cavitation for centrifugal pump based on EMD and HHT marginal spectrum energy[J]. Journal of Chemical Industry and Engineering（China）,2012,63(2):545-550.
[2]. 张娜.离心泵汽蚀现象分析及防汽蚀措施[J].流体机械, 2013,41(7):53-55.
ZHANG Na, ZHANG Jing. Cavitations Phenomena Analysis and Improvement of the Centrifugal Pump[J]. Fluid Machinery, 2013, 41(7):53-55.
[3]. 肖庆荣.水泵汽蚀的危害及预防[J].排灌机械工程学报,2003,21(5):29-30.
XIAO Qingrong. The Damage and Prevention of Pump Cavitations[J]. Journal of Drainage and Irrigation Machinery Engineering,2003,21(5):29-30.
[4]. 段向阳,王永生.离心泵空化监测试验[J].振动．测试与诊断,2011,31(3):385-388.
Duan Xiangyang, Wang Yongsheng. Experimental Study of Cavitation Monitoring in Centrifugal Pump[J]. Journal of Vibration, Measurement ＆ Diagnosis, 2011,31(3):385-388.
[5]. 段向阳,王永生.基于声压测量的离心泵空化监测[J].兵工学报,2010,(9):1268-1273. DUAN Xiang-yang,WANG Yong-sheng.Cavitation Monitoring in Centrifugal Pump Based on Sound Pressure Measurement[J]. Acta Armamentarii, 2010,(9):1268-1273.
[6]. 叶学民,裴建军.基于近场声压法的离心泵噪声特性试验研究[J].动力工程学报,2013,33(5):375-380.
YE Xuemin.Experimental Study on Noise Characteristics of Centrifugal Pump Based on Near-field Acoustic Pressure Method[J].Power Engineering, 2013,33(5):375-380.
[7]. M. Čudina.Detection of cavitation phenomenon in a centrifugal pump using audible sound[J]. Mech Syst Signal Process, 2003, 17(6):1335–1347.
[8]. 周云龙,郭柯.离心泵空化超声信号频谱特征研究[J].化工机械,2014,(4):418-422. ZHOU Yun-long, GUO Ke.Spectrum Characteristics Research for Cavitation Ultrasound Signal of Centrifugal Pumps[J].Chemical Engineering ＆ Machinery, 2014,(4):418-422.
[9]. Langthjem M A,Olhoff N.A numerical Study of Flow-induced noise in a two-dimensional centrifugal pump[J].Part I: Hydrodynamics. Journal of Fluids and Structures,2004(19): 349-368.
[10]. Wang M,Freund J.B,Lele S.K. Computational prediction of flow-generated sound[J].Annual Review of Fluid Mechanics, 2005,38(1):483-512.
[11]. Jan Černetič, Mirko Čudina. Estimating uncertainty of measurements for cavitation detection in a centrifugal pump[J],Measurement, 2011, 44(7):1293-1299.
[12]. 蒋月红,肖大雏,盛赛斌.锅炉给水泵大流量工况下汽蚀的防治[J].华东电力,2002,30(12):41-42.
Jiang Yuehong,Xiao Dachu,Sheng Saibin. Preventive Treatment of Feedwater Pump Cavitations Under Large Flow-rate[J].East China Electric Power, 2002,30(12):41-42.
[13]. ISO9906:1999.Rotodynamic pumps-hydraulic performance acceptance tests-grades 1 and 2[S].
[14]. 王太勇,王正英.基于SVD降噪的经验模式分解及其工程应用[J].振动与冲击,2005,24(4):96-98.
Wang Taiyong,Wang Zhengying. Empirical Mode Decomposition and its Engineering Applications Based on SVD Denoising[J]. Journal of Vibration and Shock, 2005, 24(4):96-98.
[15]. 赵学智,叶邦彦,陈统坚.矩阵构造对奇异值分解信号处理效果的影响[J].华南理工大学学报：自然科学版,2008,36(9):86-93.
Zhao Xuezhi, Ye Bangyan ,Chen Tongjian.Influence of Matrix Creation Way on Signal Processing Effect of Singular Value Decomposition[J].Journal of South China University of Technology(Natural Science Edition), 2008,36(9):86-93.
[16]. 高立新,殷海晨.第二代小波分析在轴承故障诊断中的应用[J].北京工业大学学报,2009,(5):577-581.
GAO Lixin, YIN Haichen.An Application of the Second Generation of Wavelet Transform in the Fault Diagnosis of Rolling Bearings[J].Journal of Beijing Polytechnic University,2009,(5):577-581.
[17]. 何为,杨洪耕.基于第二代小波变换和矢量量化理论的电能质量扰动分类方法.电网技术,2007，31(12):82-86.
HE Wei, YANG Honggeng.Power Quality Disturbances Classification Based on Second Generation of Wavelet Transform and Vector Quantization Theory[J].Power System Technology, 2007，31(12):82-86.
[18]. 赵弘,周瑞祥,林廷圻.基于Levenberg-Marquardt算法的神经网络监督控制[J]. 西安交通大学学报,2002,36(5):523~527.
Zhao Hong,Zhou Ruixiang ,Lin Tingqi. Neural Network Supervised Control Based on Levenberg-Marquardt Algorithm[J]. Journal of Xi'an Jiaotong University, 2002,36(5):523~527.