Application of guided waves and probability imaging approach for insulation damage detection of large generator stator bar

Abstract

Effective insulation condition diagnosis for large generator stator is critical to ensure safe operation and to extend operation life. In this study, elastic guided waves and probability imaging approach is introduced to detect stator insulation damage. A distributed actuator-sensor network was established to acquire Lamb wave signals before and after the presence of damage. Flight time of Lamb wave scattered signals were calculated using Hilbert transform to locate the insulation damage. Gaussian distribution was employed to quantify the damage presence probability at different spatial locations in stator insulation bar. The damage features were reconstructed and strengthened using an image fusion method. Moreover, FEM simulations and experiments of stator insulation damage detection were carried out to demonstrate the feasibility of the method. The results demonstrate that the A0 mode of Lamb wave is appropriate to characterize and identify the location of insulation damage in the stator bar. The proposed method provides an effective and feasible method for stator insulation damage detection.