A combined fault detection and diagnoses algorithm for open circuit faults and magnetic faults in a five-phase PMSM drive

Five-phase Permanent Magnet Synchronous Motors (5 ϕ -PMSM) are commonly used in high-power and fault-tolerant applications due to high reliability and fault-tolerant capability. In processing and manufacturing industries, maintenance processes contribute to approximately half of the operating costs. The early detection and diagnosis of faults can significantly reduce maintenance costs. This paper proposes a single algorithm, to detect and diagnose open circuit and demagnetization faults in 5 ϕ -PMSM drives. The signal-based discrete wavelet transforms and the statistical parameters extract the fault features from the normalized stator currents under normal and faulty conditions. A fuzzy logic-based knowledge system is developed to diagnose these faults. Since the algorithm uses normalized stator currents for fault detection and diagnosis, it applies to 5 ϕ -PMSM drives with any capacity. The proposed algorithm is experimentally validated using a Raspberry Pi. The proposed algorithm detects and diagnoses the open circuit faults and demagnetization faults in a 5 ϕ -PMSM drive within two cycles of normalized stator currents. • Single algorithm for open circuit and magnetic fault diagnosis of a 5 ϕ PMSM. • Detection and diagnosis of faults within two cycles of stator currents. • Normalized stator currents are used for analysis purposes. • The proposed algorithm can be adapted for a 5 ϕ PMSM with any power capacity.