Among the methods for detecting stator inter-turn faults, the techniques that use the harmonic characteristics have been researched in induction motors with distributed windings. However, it is questionable that the techniques are available to apply in permanent magnet machines with concentrated windings and different control methods. First of all, this study analyzes the harmonic components of line current in a brushless dc (BLDC) motor, including the issues such as supply imbalance and inherent structural asymmetry, through the developed finite-element analysis and experiment under different operating conditions. As a result, the third harmonic in negative frequency (-3f) is suitable as a fault detector because it is free from those issues. Finally, in BLDC motors with 120° conduction in a six-step operation, the faults can be detected by determining whether or not the third harmonics exist at the incipient state.

This paper proposes a diagnosis technique algorithm for a brushless dc motors under a stator inter-turn fault (ITF) condition using input impedance. The algorithm has early detection and various speed-range detection advantages. To early and accurately detect the ITF, the rotating speed, input current, voltage, resistance, and inductance must be analyzed. Therefore, we choose the input impedance as the detection factor because it includes all these factors. In this paper, the fault-detection system works without requiring a fast Fourier transform and the calculation of the negative-sequence impedance from the comparison of the measured impedance with the database impedance. The proposed technique was verified by the simulation and experiment.

Interturn faults (ITFs) cause significant changes in the electrical and magnetic characteristics of motors. In particular, ITFs can be the cause of serious distortions in the magnetic field of an air gap. Therefore, we develop a system matrix with an ITF for FEM simulation, which considers the nonlinearity of the ITF. Using the analysis of the magnetic characteristics of the detection coil from the FEM results, a circuit that employs the proposed diagnosis algorithm is shown to detect the phase and the location of a fault.

Common-mode voltage by switching pattern of space vector pulse width modulation excites parasitic capacitance coupling in interior permanent magnet synchronous motors, and it finally causes a shaft-to-frame voltage. Among all parasitic capacitances, winding-to-rotor parasitic capacitance has the greatest effect on the shaft-to-frame voltage, which means the winding-to-rotor parasitic capacitance must be suppressed for noticeable mitigation of the shaft-to-frame voltage. This paper proposes two suppression methods by changing the stator winding-to-rotor and end winding-to-rotor capacitances. First, modified winding shape is utilized for the suppression of stator winding-to-rotor capacitance. Second, a copper shield is applied to suppress the end winding-to-rotor parasitic capacitance. Finally, both methods are applied together to mitigate the effect of the stator winding-to-rotor and end winding-to-rotor capacitances on the shaft-to-frame voltage.

Condition monitoring of the stator and rotor problems such as inter-turn-short fault (ITSF) and partial irreversible demagnetization fault (PIDF) in an interior permanent magnet synchronous motor (IPMSM) is essential for achieving high efficiency and reliability. This paper presents a torque angle based inverter-embedded technique for the online detection and identification of ITSF and the PIDF. This technique monitors the deviation in the torque angle caused due to ITSF and PIDF at a certain operating point. In steady-state operation, the torque angle decreases from its original value (healthy state) due to ITSF while increases in the case of PIDF. This particular trend of torque angle is used for the detection and the identification of ITSF and PIDF. In this paper, the torque angle for healthy IPMSM is first obtained using multivariate regression analysis over the entire operating region and then compared with the torque angle during operation for any potential variation. The proposed method is verified using finite element method based simulation and experiment on a 400-watt IPMSM. The results suggest that the proposed method can be a viable candidate for efficient ITSF and PIDF detection and identification in real-time.

Brushless direct-current (BLDC) motors are widely used in industrial applications. These motors should be considered for high stability and reliability under faults which can seriously threaten safe operation. Among these fault types, a stator winding inter-turn fault (ITF) is one of the most common faults that occur in BLDC motors. Moreover, the propagation of the fault could quickly lead to shutdown of the motor within a few seconds. In order to prevent the problem, we proposed a diagnosis technique of ITF using variations of back electromotive force generated in detection coils in BLDC motors. The technique can relatively achieve more rapid response and lower cost than previous detection techniques, because the proposed technique does not require spectral analysis and complicated computation. The detection technique is verified by simulation and experiment under dynamic fault.