首页> 外文期刊>Industrial Electronics, IEEE Transactions on >Stator Current Analysis From Electrical Machines Using Resonance Residual Technique to Detect Faults in Planetary Gearboxes
【24h】

Stator Current Analysis From Electrical Machines Using Resonance Residual Technique to Detect Faults in Planetary Gearboxes

机译:使用共振残留技术从电机进行定子电流分析,以检测行星齿轮箱中的故障

获取原文
获取原文并翻译 | 示例
       

摘要

Motor current signal analysis (MCSA) provides an alternative nonintrusive approach to detect mechanical faults by using the fault signature transmitted along the torsional direction through the rotor. In existing fault detection methods based on MCSA, the gearbox health condition is monitored through the amplitude of the fault-related sidebands in the lower frequency range of the motor current spectra. However, their practical implementation is challenged by the harmonics resulting from the structural properties of the electrical machines and the inherent system imperfections. This effect is even more severe in case of a drivetrain containing planetary gearboxes due to its more complex assembly. In this paper, the resonance residual technique, which investigates the spectrum region around the resonance frequency where rich fault information may occur, is applied for the first time to MCSA to detect planetary gearbox faults. This proposed approach is verified through both simulation and experiments. A lumped parameter model for an electromechanical drive train with an annulus gear tooth crack is simulated to investigate its effect on the stator current. For experimental verification, a similar 4-kW motor-planetary gearbox–generator test rig is used. The robustness of the proposed method is demonstrated through simulations of a nonlinear finite-element model and experiments under different operating conditions. Furthermore, the effectiveness of the proposed method to extract fault information over the existing methods is also shown.
机译:电动机电流信号分析(MCSA)提供了一种替代性的非侵入式方法,通过使用沿着转子扭转方向传递的故障特征来检测机械故障。在基于MCSA的现有故障检测方法中,通过在电动机电流谱的较低频率范围内与故障相关的边带的幅度来监视齿轮箱的健康状况。然而,它们的实际实施受到了由电机的结构特性和固有的系统缺陷引起的谐波的挑战。如果动力传动系统包含行星齿轮箱,则由于其更为复杂的装配,这种效果会更加严重。在本文中,共振残差技术首次在MCSA中应用,该技术研究共振频率周围可能会产生大量故障信息的频谱区域,以检测行星齿轮箱故障。通过仿真和实验验证了该方法的有效性。模拟了具有环形齿轮齿裂纹的机电传动系统的集总参数模型,以研究其对定子电流的影响。为了进行实验验证,使用了类似的4 kW电机行星齿轮箱-发电机测试台。通过对非线性有限元模型的仿真和不同工作条件下的实验,证明了该方法的鲁棒性。此外,还显示了所提出的方法在现有方法之上提取故障信息的有效性。

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