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

摘要: 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 operate in unbalanced status, resulting noise increases. In event such a remains untreated, will further destroy rest of normal phases, even leading tragic incident entire drive application. To improve reliability SRD, an efficient on-line diagnosis method ISCF should be proposed. This paper focused on employing strong track filter (STF) achieve real-time phase resistance differences between before after ISCF, which are used as features diagnose occurrence phase. Furthermore, classification namely linear discriminant analysis (LDA) selected estimate severity. Finally, simulation experiments correspond various running statuses executed their results can verify that has accuracy robustness.