基于电机起动时间检测转子断条故障的研究

Research on the Detection of Broken Rotor Bars Fault Based on Motor Starting Time

以定子电流和振动信号为基础的特征分析方法是转子断条故障检测的常用方法,但是在起动阶段,由于电机的振动信号和定子电流都是交变量,会随着转差率的变化而变化,因此这些方法不适用于暂态情况。为了实现电机起动阶段故障检测,提出了基于电机起动时间检测转子断条故障的方法。通过有限元方法构建笼型异步电动机故障仿真模型,并设置不同断条数量和间距角度的故障仿真实验。结果表明:相比于断条间距角度,起动时间对连续断条故障更敏感一些,其最大值为导条健康时的1.593倍。因此,电机起动时间是转子断条故障的有效特征,利用该特征可以实现电机故障的早期预判检测,并可作为以定子电流或振动信号为基础的电机转子断条故障特征分析方法的有效补充。

The characteristic analysis method based on stator current and vibration signal is a common method for detecting broken rotor bars faults, but in the starting stage, since the vibration signal and stator current of the motor are both alternating variables, they will change with the change of slip rate, so these methods are not suitable for transient situations. In order to realize the fault detection in the starting stage of the motor, this research proposes a method to detect the broken rotor bars faults based on the starting time of the motor. The fault simulation model of the squirrel-cage asynchronous motor is constructed with the finite element method, and the fault simulation experiments with the different number of broken bars and spacing angles are set up. The results show that compared with other broken bars spacing angles in this experiment, the starting time is more sensitive to the continuous broken bars faults, and its maximum value is 1.593 times than that when the bar is healthy. Therefore, the starting time of the motor is an effective feature of the broken rotor bars fault, which can be used to realize the early pre-judgment detection of the motor failures, and serves as an effective supplement to the feature analysis methods of the broken bars faults of the motor rotor based on the stator current or vibration signal.