A Novel Approach towards Detection and Classification of Electric Machines’ Stator Winding Insulation Degradation using Wavelet Decomposition

Nowadays, in many advanced applications, such as electric vehicles and aircrafts, electric motors are powered by voltage source inverters (VSIs) using fast-switching power electronics devices, which puts stress on stator winding insulation system and can cause accelerated degradation. Moreover, various internal and external factors influence insulation degradation process. Therefore, monitoring insulation condition becomes necessary to ensure a safe and reliable operation. This paper presents a novel insulation condition detection technique based on current response and wavelet packet decomposition (WPD), which has the capability to determine overall state of health (SOH) of insulation and classify types of insulation degradation. Capability to classify types of degradation is important because uneven temperature distribution causes uneven degradation of insulation. To investigate performance of this method comprehensively, insulation degradations of various types and severities are emulated using high-frequency (HF) model of stator winding. Afterward, the pulse voltage fed by VSI is applied to the stator winding to observe the HF transient current response under different degradations. Lastly, WPD is employed to analyze this current for insulation degradation detection and classification. The proposed method demonstrates robust performance, ability to detect even a small amount of degradation and possesses a unique capability to classify different types of degradation.