基于平移窗信号自相关分析的振动稳定性研究
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摘要
针对目前潜油电泵的振动信号稳定性分析方法存在的不足,提出了基于平移窗信号自相关分析方法,并定义了稳定指数用于定量评价振动信号的稳定性。首先利用滑动叠加平均法获得一个能够最大程度地代表振动信号周期性特征的窗信号;然后将该窗信号在振动信号上平移并进行自相关分析,从而获得自相关系数序列;最后对自相关系数序列进行处理得到稳定指数。仿真及实验结果表明,本方法可有效地评判信号是否存在振动幅度不稳定或振动周期不稳定的现象,并成功地检验出具有潜在故障的电泵,验证了该方法在评价振动信号稳定性方面的可行性和有效性。
Targeting the limitations of the current analysis methods for vibration signals of electric submersible pumps,an autocorrelation analysis method based on translating window signals is proposed,and a stability index is defined to evaluate the stability of the vibration signals quantitatively.First,a window signal that can best represent the periodic characteristics of the vibration signals is obtained using the moving average method.Subsequently,the window signal is translated on the vibration signals while autocorrelation analysis is performed to obtain the autocorrelation coefficient series.Finally,the autocorrelation coefficient series is processed to obtain the stability index.Simulation and experiment results show that this method can effectively judge whether the signal has an unstable vibration amplitude or period to determine the electric pump with potential fault successfully,which verifies the feasibility and effectiveness of the method in evaluating the stability of vibration signals.
Targeting the limitations of the current analysis methods for vibration signals of electric submersible pumps,an autocorrelation analysis method based on translating window signals is proposed,and a stability index is defined to evaluate the stability of the vibration signals quantitatively.First,a window signal that can best represent the periodic characteristics of the vibration signals is obtained using the moving average method.Subsequently,the window signal is translated on the vibration signals while autocorrelation analysis is performed to obtain the autocorrelation coefficient series.Finally,the autocorrelation coefficient series is processed to obtain the stability index.Simulation and experiment results show that this method can effectively judge whether the signal has an unstable vibration amplitude or period to determine the electric pump with potential fault successfully,which verifies the feasibility and effectiveness of the method in evaluating the stability of vibration signals.
引文
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[22]KABIR M A,SHAHNAZ C.Denoising of ECG signals based on noise reduction algorithms in EMD and wavelet domains[J].Biomedical Signal Processing&Control,2012,7(5):481-489.doi:10.1016/j.bspc.2011.11.003
[23]秦毅,王家序,毛永芳.基于软阈值和小波模极大值重构的信号降噪[J].振动、测试与诊断,2011,31(5):543-547.doi:10.3969./j.issn.1004-6801.2011.05.001QIN Yi,WANG Jiaxu,MAO Yongfang.Signal denoising based on soft thresholding and reconstruction from dyadic wavelet transform modulus maximum[J].Journal of Vibration,Measurement&Diagnosis,2011;31(5):543-547.doi:10.3969/j.issn.1004-6801.2011.05.001
[24]THOMSON W T,MARIE D D,汤姆逊,等.振动理论及应用[M].北京:清华大学出版社,2005.
[2]FENG Zhipeng,MA Haoqun,ZUO Ming J.Vibration signal models for fault diagnosis of planet bearings[J].Journal of Sound Vibration,2016,370:372-393.doi:10.-1016/j.jsv.2016.01.041
[3]司景萍,高志鹰,梁红波,等.基于瞬时基频的发动机表面振动信号时域定位[J].噪声与振动控制,2010,30(6):153-156.doi:10.3969/j.issn.1006-1355.-20 10.06.037SI Jingping,GAO Zhiying,LIANG Hongbo,et al.Time domain location of engine surface vibration signal based on instantaneous fundamental fre quency[J].Noise and Vibration Control,2010, 30(6):153-156.doi:10.3969/j.-issn.1006-1355.2010.06.037
[4]王亚昆.基于RSGWPT-MSE和PNN的潜油电泵故障诊断方法[J].机械工程师,2018(1):167-170,172.doi:10.3969/j.issn.1002-2333.201 8.01.057WANG Yakun.A diagnosis method for electrical submersible pump based on RSGWPT-MSE and PNN[J].Mechanical Engineer,2018(1):167-170,172.doi:10.-3969/j.issn.1002-2333.2018.01.057
[5]马建仓,刘小龙.航空发动机转子振动信号的早期故障分析[J].计算机测量与控制,2010,18(2):276-279.MA Jiancang,LIU Xiaolong.Early analysis of vibration signal for aero-engine rotor faults[J].Computer Measurement&Control,2010,18(2):276-279.
[6]余红英,闫宏伟,潘宏侠.齿轮振动信号分解及其在故障诊断中的应用[J].振动、测试与诊断,2005,25(2):109-113.doi:10.3969/j.issn.1004-6801.2005.02.007YU Hongying,YAN Hongwei,PAN Hongxia.Gear vibration signal analysis and its application to fault diagnosis[J].Journal of Vibration,Measurement&Diagnosis,2005,25(2):109-113.doi:10.3969/j.issn.1004-6801.-2005.02.007
[7]陈涛,李林.基于振动信号分析的齿轮故障诊断方法研究[J].科技广场,2011(9):29-33.doi:10.3969/j.issn.-1671-4792.2011.09.008CHEN Tao,LI Lin.Research of gear fault diagno sis'method based on analysis of vibration signal[J].Science Mosaic,2011(9):29-33.doi:10.3969/j.issn.1671-4792.2011.-09.008
[8]沈颖.信号相关分析及其在工程测试中的应用[J].石油仪器,2002,16(6):39-42.doi:10.3969/j.issn.1004-9134.2002.06.014SHEN Ying.Signal correlation analysis and its application to engineering te st[J].Petroleum Instruments,2002,16(6):39-42.doi:10.3969/j.issn.1004-9134.2002.06.014
[9]王建国,吴林峰,秦绪华.基于自相关分析和LMD的滚动轴承振动信号故障特征提取[J].中国机械工程,2014,25(2):186-191.doi:10.3969/j.issn.1004-132X.-2014.02.009WANG Jianguo,WU Linfeng,QIN Xuhua.Rolling bearing vibration signal fault feature extraction based on autocorrelation analysis and LMD[J].China Mechanical Engineering,2014,25(2):186-191.doi:10.3969/j.issn.1004-132X.2014.02.009
[10]管河山,邹清明,罗智超.时间序列平稳性分类识别研究[J].统计与信息论坛,2016,31(4):3-8.GUAN Heshan,ZOU Qingming,LUO Zhichao.Study on classification and identification of time series stationarity[J].Statistics&Information Forum,2016,31(4):3-8.
[11]刘广孚,朱赫,周凯迪,等.基于改进K-means的潜油电泵质量评估方法研究[J].西南石油大学学报(自然科学版),2018,40(1):173-180.doi:10.11885/j.issn.-1674-5086.2016.11.25.02LIU Guangfu,ZHU He,ZHOU Kaidi,et al.Study on the quality evaluation of electric submersible pumps based on improved K-means[J].Journal of Southwest Petroleum University(Science&Technology Edition),2018,40(1):173-180.doi:10.11885/j.issn.1674-5086.2016.11.25.02
[12]李星蓉,李永倩,张硕.同步叠加平均算法抑制噪声的Labview实现[J].华北电力大学学报,2009,36(4):73-76.doi:10.3969/j.issn.1007-2691.2009.04.016LI Xingrong,LI Yongqian,ZHANG Shuo.The LabView implement of synchronization overlapping average algorithm to suppress noise[J].Journal of North China Electric Power University,2009,36(4):73-76.doi:10.3969/j.-issn.1007-2691.2009.04.016
[13]国家标准化管理委员会.GB/T 16750-2015潜油电泵机组国家标准[S].北京:中国标准出版社,2016:61-62.
[14]常兆光,王清河,杜彩凤.应用统计方法[M].北京:石油工业出版社,2009.CHANG Zhaoguang,WANG Qinghe,DU Caifeng.Applied statistical methods[M].Beijing:Petroleum Industry Press,2009.
[15]吕苗荣,丁宇,徐清武.基于自相关分析的离心泵振动信号的分段方法[J].自动化仪表,2016,37(10):83-85.LU Miaorong,DING Yu,XU Qingwu.Segmentation method based on autocorrelation analysis for vibration signal of centrifugal pump[J].Process Automation Instrumentation,2016,37(10):83-85.
[16]HOLL M,KANTZ H.The relationship between the detrendend fluctuation analysis and the autocorrelation function of a signal[J].European Physical Journal B,2015.88(12):1-7.doi:10.1140/epjb/e2015-60721-1
[17]姚诚,刘广孚,谢文献,等.基于振动检测的潜油电泵机组转速测量方法的研究[J].仪表技术与传感器,2008(12):52-54.doi:10.3969/j.issn.1002-1841.2008.-12.020YAO Cheng,LIU Guangfu,XIE Wenxian,et al.Rotation speed measurement method for electrical submersible pumps based on vibration detecting[J].Instrument Technique and Sensor,2008(12):52-54.doi:10.3969/j.issn.-1002-1841.2008.12.020
[18]刘树林,徐敏强,董振刚,等.潜油电泵机组振动状态评估系统[J].大庆石油学院学报,2008,32(5):58-60,74.doi:10.3969/j.issn.2095-4107.2008.05.017LIU Shulin,XU Minqinag,DONG Zhengang,et al.Vibration state assessment system for electric submersible pump unit[J].Journal of Northeast Petroleum University,2008.32(5):58-60,74.doi:10.3969/j.issn.2095-4107.2008.05.-017
[19]郑思莉,桂预风,陈先桥,等.小波阈值法在机械信号降噪研究中的应用[J].机械设计与制造,2014(1):222-225.doi:10.3969/j.issn.1001-3997.2014.01.068ZHENG Sili,GUI Yufeng,CHEN Xianqiao,et al.The application of mechanical signals processing in wavelet threshold denoising method[J].Machinery Design&Manufacture,2014(1):222-225.doi:10.3969/j.issn.1001-3997.2014.01.068
[20]王秉仁,杨艳霞,蔡伟,等.小波阈值降噪技术在振动信号处理中的应用[J].噪声与振动控制,2008,28(6):9-12.doi:10.3969/j.issn.1006-13 55.2008.06.003WANG Binren,YANG Yanxia,CAI Wei,et al.Application of wavelet threshold de-noising technique in vibration signals processing[J].Noise and Vibration Control,2008.28(6):9-12.doi:10.3969/j.issn.1006-13 55.2008.06.003
[21]陈涛,徐小力,王少红.基于小波包惩罚函数的烟机振动信号软阈值降噪[J].北京理工大学学报,2010,30(8):906-909,914.CHEN Tao,XU Xiaoli,WANG Shaohong.Method of wavelet packet-based penalty function soft-threshold to de-noise vibration signals for flue gas turbine[J].Transactions of Beijing Institute of Technology,2010,30(8):906—909,914.
[22]KABIR M A,SHAHNAZ C.Denoising of ECG signals based on noise reduction algorithms in EMD and wavelet domains[J].Biomedical Signal Processing&Control,2012,7(5):481-489.doi:10.1016/j.bspc.2011.11.003
[23]秦毅,王家序,毛永芳.基于软阈值和小波模极大值重构的信号降噪[J].振动、测试与诊断,2011,31(5):543-547.doi:10.3969./j.issn.1004-6801.2011.05.001QIN Yi,WANG Jiaxu,MAO Yongfang.Signal denoising based on soft thresholding and reconstruction from dyadic wavelet transform modulus maximum[J].Journal of Vibration,Measurement&Diagnosis,2011;31(5):543-547.doi:10.3969/j.issn.1004-6801.2011.05.001
[24]THOMSON W T,MARIE D D,汤姆逊,等.振动理论及应用[M].北京:清华大学出版社,2005.