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Gear Tooth Surface Damage Fault Detection Using Induction Machine Stator Current Space Vector Analysis

机译:基于感应电机定子电流空间矢量分析的齿轮齿面损伤故障检测

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摘要

A noninvasive technique for the diagnosis of gear tooth surface damage faults based upon the stator current space vector analysis is presented. The torque oscillation profile produced by the gear tooth surface damage fault in the mechanical torque experimented by the driven electrical machine is primarily investigated. This profile consists of a mechanical impact generated by the fault followed by a damped oscillation that can be identified through the mechanical system torsional natural frequency and damping factor. Through theoretical developments, it is shown that the periodic behavior of this particular shape produces fault-related frequencies in the stator current and harmonics integer multiple of the rotation frequency in the stator current space vector instantaneous frequency. The fault signature related to the gear tooth surface damage fault is predicted through the numerical simulation. The simulation results are validated through experimental tests, illustrating a possible noninvasive gear tooth surface damage fault detection with a fault sensitivity comparable to invasive methods. A dedicated experimental setup, which is based on a 250-W squirrel-cage three-phase induction machine that is shaft connected to a single-stage gear, has been used for this purpose.
机译:提出了一种基于定子电流空间矢量分析的齿轮齿面损伤故障诊断方法。首先研究了齿轮齿表面损坏故障所产生的扭矩振荡曲线,该故障是由被驱动电机实验得出的机械扭矩。该曲线由故障产生的机械冲击和阻尼振荡组成,可以通过机械系统的扭转固有频率和阻尼因子来识别。通过理论研究表明,这种特定形状的周期性行为会在定子电流中产生与故障相关的频率,并在定子电流空间矢量瞬时频率中产生旋转频率的谐波整数倍。通过数值模拟预测了与齿轮齿面损坏故障有关的故障特征。通过实验测试验证了仿真结果,该结果说明了可能的非侵入式齿轮齿表面损坏故障检测,其故障敏感性可与侵入式方法媲美。为此,使用了一个专用的实验装置,该装置基于一个250 W鼠笼式三相感应电机,该电机与轴连接到单级齿轮。

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