电机转子断条故障信号准确诊断研究
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摘要
研究电机转子断条故障准确诊断问题,有利于电机设备的安全稳定运行。由于电机转子断条故障信号中故障特征被基波和噪声淹没难以准确识别,传统识别诊断理论方法存在使频谱复杂化、识别准确率较低等缺陷。为提高电机转子断条故障识别准确率,提出一种利用改进混合PSO算法结合断条数目估计公式的断条故障诊断方法。首先将基波信号与单位余弦基函数内积最大准则作为改进混合PSO算法约束条件,准确估计出基波、故障谐波参数以及对应表达式并依次剔除,然后结合转子断条数目估计公式,达到准确检测和估计断条故障程度的目的。最后,对模拟和实际信号的处理结果表明,该算法能够准确的检测出转子断条故障程度,验证了该方法的有效性和优越性。
This paper studies the fault diagnosis of broken rotor bar,which is conductive to the safe and stable operation of motor equipment.In order to improve diagnosis accuracy,an improved hybrid PSO optimization algorithm is proposed in the paper,which is combined with the formula for estimating the number of the broken rotor bar to detect the fault.With the constraints of the maximum inner product between the basic wave and cosine basis functions,the method can estimate precisely the parameters of basic wave and harmonic fault component,and the corresponding expressions of them can be constructed and then eliminated,combining with the formula.Then the purposes of detecting and estimating the rotor broken bar fault degree accurately were achieved.Finally,the results of the simulation and the actual signal processing show that the algorithm can accurately detect the fault degree of the rotor broken bar,and verify the effectiveness and superiority of the proposed method.
This paper studies the fault diagnosis of broken rotor bar,which is conductive to the safe and stable operation of motor equipment.In order to improve diagnosis accuracy,an improved hybrid PSO optimization algorithm is proposed in the paper,which is combined with the formula for estimating the number of the broken rotor bar to detect the fault.With the constraints of the maximum inner product between the basic wave and cosine basis functions,the method can estimate precisely the parameters of basic wave and harmonic fault component,and the corresponding expressions of them can be constructed and then eliminated,combining with the formula.Then the purposes of detecting and estimating the rotor broken bar fault degree accurately were achieved.Finally,the results of the simulation and the actual signal processing show that the algorithm can accurately detect the fault degree of the rotor broken bar,and verify the effectiveness and superiority of the proposed method.
引文
[1]A H Bonnet,G C Soukup.Rotor failures in squirrel cage induction motore[J].IEEE Transactions on Industry Applications,1986,IA-22(6):1165-1173.
[2]曹建刚.Hilbert变换在转子断条故障诊断中的应用研究[D].东北大学,2010.
[3]魏云冰,黄进,牛发亮,任秉知.基于小波脊线的笼型异步电动机转子故障特征提取[J].电工技术学报,2003-4:123-127.
[4]张征平,任震,黄雯莹,管霖,杨楚明,何建军.基于小波脊线的电动机转子故障检测新方法[J].中国电机工程学报,2003-1:98-102.
[5]安国庆,刘教民,郭立炜,刘玉坤.利用相关性基波消去法诊断电机转子断条故障[J].电机与控制学报,2011-3:69-73.
[6]张晓春,严民雄,刘静,许允之.利用相关性基波消去法诊断电动机转子断条故障[J].煤矿机电,2014-4:56-59.
[7]张建文,张振明,朱宁辉,姚奇.基于Park矢量的变频电源供电的笼型异步电机转子断条故障诊断方法[J].华北电力大学学报,2006-6:39-42.
[8]F Filippetti,M Martelli,G Franceschini,C Tassoni.Development of expert system knowledge base to on-line diagnosis of rotor electrical faults of induction motors[C].Proceedings of IEEE Industrial Application Society 1992 Annual Meeting,Houston(USA),1992-1:92-99
[9]Fiorenzo Filippetti,Giovanni Franceschini,Carla Tassoni,Peter Vas.AI techniques in induction machines diagnosis including the speed ripple effect[J].IEEE Transactions on Industry Applications,1998,34(1):98-108
[10]孙丽玲.异步电动机故障检测与诊断方法研究[D].华北电力大学(河北),2007.
[11]王攀攀,史丽萍,张勇,韩丽.采用一种混合骨干微粒群优化算法的感应电机转子断条故障诊断[J].中国电机工程学报,2012,30:73-81,13.
[2]曹建刚.Hilbert变换在转子断条故障诊断中的应用研究[D].东北大学,2010.
[3]魏云冰,黄进,牛发亮,任秉知.基于小波脊线的笼型异步电动机转子故障特征提取[J].电工技术学报,2003-4:123-127.
[4]张征平,任震,黄雯莹,管霖,杨楚明,何建军.基于小波脊线的电动机转子故障检测新方法[J].中国电机工程学报,2003-1:98-102.
[5]安国庆,刘教民,郭立炜,刘玉坤.利用相关性基波消去法诊断电机转子断条故障[J].电机与控制学报,2011-3:69-73.
[6]张晓春,严民雄,刘静,许允之.利用相关性基波消去法诊断电动机转子断条故障[J].煤矿机电,2014-4:56-59.
[7]张建文,张振明,朱宁辉,姚奇.基于Park矢量的变频电源供电的笼型异步电机转子断条故障诊断方法[J].华北电力大学学报,2006-6:39-42.
[8]F Filippetti,M Martelli,G Franceschini,C Tassoni.Development of expert system knowledge base to on-line diagnosis of rotor electrical faults of induction motors[C].Proceedings of IEEE Industrial Application Society 1992 Annual Meeting,Houston(USA),1992-1:92-99
[9]Fiorenzo Filippetti,Giovanni Franceschini,Carla Tassoni,Peter Vas.AI techniques in induction machines diagnosis including the speed ripple effect[J].IEEE Transactions on Industry Applications,1998,34(1):98-108
[10]孙丽玲.异步电动机故障检测与诊断方法研究[D].华北电力大学(河北),2007.
[11]王攀攀,史丽萍,张勇,韩丽.采用一种混合骨干微粒群优化算法的感应电机转子断条故障诊断[J].中国电机工程学报,2012,30:73-81,13.