单相永磁同步电机自学习故障检测
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摘要
针对小功率单相永磁同步电容电机的实际应用场合,研究一种在线自学习故障检测方法。以电容电机为被控对象,建立了其数学模型,推导了归算后对称机的相电压对称分量及相电流正负序分量,并以此计算相电压及相电流;根据BP网络神经建立起自学习网络层,详细介绍了BP网络神经算法实施过程,分析了电机运行过程中的模式切换。最后,对随机抽取的3个电机进行了实验验证,结果表明该方法能够准确地检测出电机故障。
A method of fault detection which was applied to the single phase permanent magnet synchronous motor( PMSM) based on self-learning was proposed. The mathematical model was established based on the capacitor motor.Symmetrical components of phase voltage and component of positive sequence and negative sequence of phase current were derived after the motor was transformed into a symmetrical support vector machine,and the phase voltage and phase current could be figured up accordingly. The structure of self-learning network has been figured out based on BP network. The actualization of arithmetic was introduced. And the operational mode was sketched out. The experiments on three motors show that the fault can be diagnosed accurately and effectively by this method.
A method of fault detection which was applied to the single phase permanent magnet synchronous motor( PMSM) based on self-learning was proposed. The mathematical model was established based on the capacitor motor.Symmetrical components of phase voltage and component of positive sequence and negative sequence of phase current were derived after the motor was transformed into a symmetrical support vector machine,and the phase voltage and phase current could be figured up accordingly. The structure of self-learning network has been figured out based on BP network. The actualization of arithmetic was introduced. And the operational mode was sketched out. The experiments on three motors show that the fault can be diagnosed accurately and effectively by this method.
引文
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[5]钱华明,王雯升.遗传小波神经网络及在电机故障诊断中的应用[J].电子测量与仪器学报,2009,3(23):81-86.
[6]黄道,宋欣.神经网络在化工过程故障诊断中的应用[J].控制工程,2006,13(1):6-9.
[7]宋宜斌.多层感知器的一种快速网络训练法及其应用[J].控制与决策,2000,15(1):125-127.
[8]戴志辉,李芷筠,焦彦军,等.基于BP神经网络的小样本失效数据下继电保护可靠性评估[J].电力自动化设备,2014,34(11):129-134.
[9]杨存祥,朱琛,解豪杰.基于RPROP神经网络算法的异步电动机故障诊断[J].电力自动化设备,2012,32(1):80-83.
[10]汤蕴璆.电机学[M].北京:机械工业出版社,2008:391-392.
[2]邓建国,罗隆福,彭晓. Semihex TM接法三相感应电动机的瞬态仿真研究[J].系统仿真学报,2005,17(11):2745-2748.
[3]沈艳霞,纪志成,姜建国.电机故障诊断的人工智能方法综述[J].微特电机,2004,32(2):39-42.
[4]王志伟,胡瑜,李银伟.基于小波和自适应模糊神经的旋转设备故障诊断[J].华东交通大学学报,2010,1(27):72-77.
[5]钱华明,王雯升.遗传小波神经网络及在电机故障诊断中的应用[J].电子测量与仪器学报,2009,3(23):81-86.
[6]黄道,宋欣.神经网络在化工过程故障诊断中的应用[J].控制工程,2006,13(1):6-9.
[7]宋宜斌.多层感知器的一种快速网络训练法及其应用[J].控制与决策,2000,15(1):125-127.
[8]戴志辉,李芷筠,焦彦军,等.基于BP神经网络的小样本失效数据下继电保护可靠性评估[J].电力自动化设备,2014,34(11):129-134.
[9]杨存祥,朱琛,解豪杰.基于RPROP神经网络算法的异步电动机故障诊断[J].电力自动化设备,2012,32(1):80-83.
[10]汤蕴璆.电机学[M].北京:机械工业出版社,2008:391-392.