首页> 外文期刊>Mechanical systems and signal processing >Induction motor stator current analysis for planetary gearbox fault diagnosis under time-varying speed conditions
【24h】

Induction motor stator current analysis for planetary gearbox fault diagnosis under time-varying speed conditions

机译:异步电动机定子电流分析在时变转速条件下的行星齿轮箱故障诊断

获取原文
获取原文并翻译 | 示例

摘要

Vibration-based planetary gearbox fault diagnosis under time-varying speed conditions is challenging. This work exploits the advantages of motor stator current signal in easier accessibility and simpler frequency modulation structure, and applies the motor current signature analysis technique on planetary gearbox fault diagnosis. Firstly, the induction motor stator current signal with both planetary gearbox fault and airgap eccentricity under time-varying speed conditions is analytically modeled, and properties of time-varying planetary gearbox fault signatures are summarized. Then, to address the difficulties of revealing and presenting relatively weak and time-varying fault signatures in motor stator current signal, the adaptive iterative generalized demodulation is utilized. The Fourier transform surrogate test is integrated with iterative generalized demodulation algorithm to solve the problem of weak fault signature extraction, and Hilbert spectra of validated mono-components finally compose the time-frequency representation of analyzed motor stator current signal. Both numerical simulation as well as lab experimental evaluations in different gear fault cases, have been conducted to verify the correctness of the derived time-varying gear fault signatures, and the effectiveness of accurate planetary gearbox fault diagnosis.
机译:在时变速度条件下基于振动的行星齿轮箱故障诊断具有挑战性。这项工作充分利用了电动机定子电流信号的优势,即易于访问和简化调频结构,并将电动机电流信号分析技术应用于行星齿轮箱故障诊断。首先,对时变转速条件下具有行星齿轮箱故障和气隙偏心的感应电动机定子电流信号进行了建模,总结了时变行星齿轮箱故障特征。然后,为了解决在电动机定子电流信号中揭示和呈现相对较弱且随时间变化的故障特征的困难,利用了自适应迭代广义解调。将傅里叶变换替代测试与迭代广义解调算法集成在一起,以解决故障特征签名提取不可靠的问题,经过验证的单分量的希尔伯特频谱最终构成了分析后的电机定子电流信号的时频表示。在不同的齿轮故障情况下,都进行了数值模拟和实验室实验评估,以验证导出的随时间变化的齿轮故障特征的正确性以及准确的行星齿轮箱故障诊断的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

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