To monitor, diagnose, and suppress the inter-turn short-circuit faults (ITSCFs) of a submersible motor, an approach for the on-line identification of its winding faults has been proposed based on monitoring the stator current. First, an ITSCF model with the global leakage referred to the stator is given. With this model, the detection parameter, which is equal to the ratio of the turns of the fault windings to the total turns of the windings in the healthy phase, can be derived. Second, a faulty model described by the fourth order state-space equation of the motor with a winding fault has been given. Based on sampled stator voltage and stator current, the detection parameter has been solved and used to estimate the location and the turns of inter-turn short-circuit windings of the motor in real time. The accuracy and the robustness of the proposed approach has been illustrated with a 1.5 kW motor that is fed by a 10 kW inverter. Experiment shows that the identification accuracy in terms of the number of the ITSCF windings of the motor stator is less than 3. It can give a reference for the on-line diagnose the ITSCFs of the stator windings of a submersible motor that works in 2 km deep well.

为了监测、诊断和抑制潜水电机的匝间短路故障（ITSCF），提出了一种基于定子电流监测的绕组故障在线识别方法。首先，给出了以定子为基准的全局泄漏的 ITSCF 模型。利用该模型，可以导出检测参数，即故障绕组匝数与健康相绕组总匝数之比。其次，给出了绕组故障电机四阶状态空间方程描述的故障模型。基于采样的定子电压和定子电流，求解出检测参数，用于实时估计电机匝间短路绕组的位置和匝数。所提出方法的准确性和鲁棒性已通过由 10 kW 逆变器供电的 1.5 kW 电机来说明。实验表明，电机定子ITSCF绕组数的识别精度小于3个，可为工作2km的潜水电机定子绕组ITSCF的在线诊断提供参考。深井。