Abstract
Stator winding faults may cause severe damages in Permanent Magnet Synchronous Motors (PMSM) if not detected early on. The earliest fault detection in motors should be made during transient states throughout the initial starting period. A new approach based on Empirical Mode Decomposition (EMD) and statistical analysis was presented for detecting stator winding fault by way of transient state phase current of PMSM in this study. Models based on finite elements method were developed for the PMSM representing the healthy and faulty states in order to implement the suggested fault detection method. Afterwards, transient state stator phase winding currents were measured for healthy and faulty states under nominal load in accordance with motor models. These non-linear current signals monitored were separated into its Intrinsic Mode Functions (IMF) via the EMD method. Pearson Correlation Coefficient was used for determining the IMF that most resembles the characteristics of the main signal. Statistical parameter-based feature extractions were carried out for the IMF signals determined for the healthy and faulty states. Fault and fault level detection were carried out successfully by comparing the obtained feature vectors. The acquired results have put forth that the suggested method can be used securely for fault detection in electrical machines especially for early fault detection.
Highlights
PERMANENT MAGNET synchronous motors (PMSMs) are frequently used in various industrial and military applications such as wind energy, electrical vehicles, railroad transportation, military planes etc. due to their various advantages such as high efficiency, high torque, power and flux density, wide speed ranges, long service life, simple structure and precise torque control [1,2,3,4,5,6]
A new approach based on Empirical Mode Decomposition (EMD) and statistical analysis was presented for detecting stator winding fault by way of transient state phase current of PMSM in this study
A new approach based on the signal processing method of EMD and statistical analysis for winding fault detection in PMSMs using temporary state phase current
Summary
PERMANENT MAGNET synchronous motors (PMSMs) are frequently used in various industrial and military applications such as wind energy, electrical vehicles, railroad transportation, military planes etc. due to their various advantages such as high efficiency, high torque, power and flux density, wide speed ranges, long service life, simple structure and precise torque control [1,2,3,4,5,6]. Various signal processing methods are used for fault detection in electrical motors. This study puts forth the capability for determining unstable fault current types for different speed intervals [24]. In their studies, Mejia-Barron et al presented the application of empirical mode decomposition-based methods such as Ensemble EMD (EEMD) and complete EMD (CEEMD) for inrush current analysis. Steady state motor currents have been used in majority of the studies in literature in this field for determining PMSM winding faults [12,15]. The present study puts forth a detection method for stator winding fault in PMSM based on the EMD analysis of Transient Motor Current Signals (TMCSs). It has a rotor surface mounted magnet with a magnet type of XG196/96
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