首页> 外文OA文献 >Modulation signal bispectrum analysis of electric signals for the detection and diagnosis of compound faults in induction motors with sensorless drives
【2h】

Modulation signal bispectrum analysis of electric signals for the detection and diagnosis of compound faults in induction motors with sensorless drives

机译:用于无传感器驱动的感应电动机复合故障检测和诊断的电信号调制信号双谱分析

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

As a prime driver, induction motor is the most electric energy consuming component in industry. The exposure of the motor to stator winding asymmetry, combined with broken rotor bar fault significantly increases the temperature and reduces the efficiency and life of the motor. Accurate and timely diagnosis of these faults will help to maintain motors operating under optimal status and avoid excessive energy consumption and severe damages to systems. This paper examines the performance of diagnosing the effect of asymmetry stator winding on broken rotor bar (BRB) faults under closed loop operation modes. It examines the effectiveness of conventional diagnostic features in both motor current and voltage signals using spectrum and modulation signal bispectrum analysis (MSBA). Evaluation results show that the combined faults cause an additional increase in the sideband amplitude and this increase in sideband can be observed in both the current and voltage signals under the sensorless control mode. MSB analysis has a good noise reduction capability and produces a more accurate and reliable diagnosis in that it gives a more correct indication of the fault severity and its location for all operating conditions.
机译:作为主要驱动器,感应电动机是工业上最耗电的组件。电机暴露于定子绕组的不对称状态,以及转子条故障而大大提高了温度,并降低了电机的效率和寿命。准确,及时地诊断这些故障将有助于使电动机保持最佳状态,并避免过多的能耗和对系统的严重损坏。本文研究了在闭环运行模式下诊断不对称定子绕组对断裂的转子条(BRB)故障的影响的性能。它使用频谱和调制信号双频谱分析(MSBA)来检查电动机电流和电压信号中常规诊断功能的有效性。评估结果表明,组合故障导致边带幅度进一步增加,并且在无传感器控制模式下的电流和电压信号中都可以观察到边带增加。 MSB分析具有良好的降噪能力,并且可以对所有操作条件下的故障严重程度及其位置给出更正确的指示,从而产生更准确,更可靠的诊断。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号