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基于LabVIEW的异步电机转子断条检测

消耗积分:10 | 格式:rar | 大小:1.14 MB | 2011-03-05

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 针对三相异步电动转子断条的故障检测中故障信号很小，其与基波频率很接近，可能被基波分量泄漏或噪声所淹没，不能准确的判断。提出了一种LabVIEW平台下基于数字滤波、频谱细化分析和定子电流齿槽谐波分量的转差率在线检测方法。先对提取到的定子电流进行频谱细化分析，提高频谱分辨率，然后设计一个数字滤波器滤除定子电流基频信号，避免基波分量造成干扰。详细介绍了定子电流齿槽谐波分量的转差率估计的原理，通过该方法找出故障信号，并有效的区分出段子断条故障和负载波动。仿真和实验结果表明，该方法能够准确的找到故障信号，解决基波分量泄漏等引起的干扰，提高故障检测的可靠性和准确性。

Abstract:
 Because of the characteristic frequency ingredient’s peak-to-peak value is small， and close to the fundamental component， it is easily submerged by fundamental component. To solve the problem， this paper addressed a new approach based on digital filter， zoom-FFT， and rotor slot harmonics based slip estimation to detect rotor bar faults online， calculated the zoom-FFT of stator current to improve the resolution of frequency ingredient， then designed a digital filter to filter the fundamental component， introduced the theory of rotor slot harmonics based slip estimation detailed. The method found the characteristic component exactly and correctly distinguished rotor bars breaking and loan oscillation. Result of numerical simulation and test shows that the approach can find the fault signal accurately， solve the interference caused by fundamertal component leaking， and improve the reliability and accuraly of fault detection.

 


 

 

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程凡凡 2012-09-04
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