Fault diagnosis method for power transistors in switched reluctance machine drive system

2016 ◽  
Author(s):  
Hye-Ung Shin ◽  
Kyo-Beum Lee
Keyword(s):  
Fault Diagnosis ◽  
Drive System ◽  
Switched Reluctance Machine ◽  
Switched Reluctance ◽  
Power Transistors ◽  
Reluctance Machine ◽  
Machine Drive ◽  
Diagnosis Method

Impact of Current Profiling For NVH Mitigation On Switched Reluctance Machine Drive Accessories

2021 ◽  
Author(s):  
Shuvajit Das ◽  
Anik Chowdhury ◽  
Md. Ehsanul Haque ◽  
Md Tawhid Bin Tarek ◽  
Yilmaz Sozer ◽  
...  
Keyword(s):  
Switched Reluctance Machine ◽  
Switched Reluctance ◽  
Reluctance Machine ◽  
Machine Drive

scholarly journals Applications of a Strong Track Filter and LDA for On-Line Identification of a Switched Reluctance Machine Stator Inter-Turn Shorted-Circuit Fault

Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 134 ◽  
Author(s):  
Li Xiao ◽  
Hexu Sun ◽  
Liyi Zhang ◽  
Feng Niu ◽  
Lu Yu ◽  
...  
Keyword(s):  
Switched Reluctance Machine ◽  
Switched Reluctance ◽  
Linear Discriminant ◽  
Reluctance Machine ◽  
Before And After ◽  
Diagnosis Method ◽  
On Line ◽  
Unbalanced Status ◽  
Machine Drives ◽  
Track Filter

Reliability is pivotal significance for switched reluctance machine drives (SRD) applied to safety essential transportation and industrial fields. An inter-turn shorted-circuit fault (ISCF) could incite the machine to operate in unbalanced status, resulting in the noise increases. In the event such a fault remains untreated, the fault will further destroy the rest of the normal phases, even leading to a tragic incident for the entire drive application. To improve the reliability of SRD, an efficient on-line fault diagnosis method for ISCF should be proposed. This paper is focused on employing the strong track filter (STF) to achieve real-time phase resistance differences between before and after ISCF, which are used as features to diagnose the fault occurrence and the fault phase. Furthermore, a classification namely as linear discriminant analysis (LDA) is selected to estimate fault severity. Finally, simulation and experiments correspond to various running statuses are executed and their results can verify that the diagnosis method has accuracy and robustness.

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