An Effective Method for Detection of Demagnetization Fault in Axial Flux Coreless PMSG With Texture-Based Analysis

Abstract

Due to its high power densities and compact dimensions, the axial flux coreless permanent magnet synchronous generator (PMSG) is used in a wide range of areas such as wind turbines and electric vehicles. It is extremely important to detect magnetization faults that occur in these generators. The occurrence of such faults in these machines with a wide range of areas of use affects their operation negatively. In this study, an effective method has been proposed to detect the demagnetization fault occurring in axial flux coreless PMSGs. The relevant method proposes an effective texture analysis-based feature extraction method, which is an original method in contrast to conventional methods used in the literature. It has been revealed that it is a method that can be used instead of conventional methods such as time-frequency analysis, frequency spectrum analysis, and motor current signature analysis (MCSA) methods. Using the finite element method, current and voltage signals were taken from the healthy and axial flux coreless PMSG with 3% and 6% demagnetization fault. Besides, these signals were retaken at different speeds and loads. After the signals were converted into images, using the features obtained from the images with LBP, fault diagnosis processes were carried out with Knn. It was tested both at different fault rates and under different load and speed conditions to test whether the proposed method worked properly. The success rate of this method was observed as 97.16% and 100%. With the proposed method, it has been revealed that the demagnetization fault can be detected in axial flux coreless PMSGs.

Keywords

• Image texture analysis
• demagnetization
• fault detection
• permanent magnet machines