Stator ITSC Fault Diagnosis for EMU Induction Traction Motor Based on Goertzel Algorithm and Random Forest

Jie Ma, Yingxue Li, Liying Wang, Jisheng Hu, Hua Li, Jiyou Fei (), Lin Li and Geng Zhao
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Jie Ma: College of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, China
Yingxue Li: College of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, China
Liying Wang: College of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, China
Jisheng Hu: College of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, China
Hua Li: College of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, China
Jiyou Fei: College of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, China
Lin Li: College of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, China
Geng Zhao: College of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, China

Energies, 2023, vol. 16, issue 13, 1-17

Abstract: The stator winding insulation system is the most critical and weakest part of the EMU’s (electric multiple unit’s) traction motor. The effective diagnosis for stator ITSC (inter-turn short-circuit) faults can prevent a fault from expanding into phase-to-phase or ground short-circuits. The TCU (traction control unit) controls the traction inverter to output SPWM (sine pulse width modulation) excitation voltage when the traction motor is at a standstill. Three ITSC fault diagnostic conditions are based on different IGBTs’ control logics. The Goertzel algorithm is used to calculate the fundamental current amplitude difference Δ i and phase angle difference Δ θ of equivalent parallel windings under the three diagnostic conditions. The six parameters under the three diagnostic conditions are used as features to establish an ITSC fault diagnostic model based on the random forest. The proposed method was validated using a simulation experimental platform for the ITSC fault diagnosis of EMU traction motors. The experimental results indicate that the current amplitude features Δ i and phase angle features Δ θ change obviously with an increase in the ITSC fault extent if the ITSC fault occurs at the equivalent parallel windings. The accuracy of the ITSC fault diagnosis model based on the random forest for ITSC fault detection and location, both in train and test samples, is 100%.

Keywords: Goertzel algorithm; ITSC fault; traction motor; random forest; fault diagnosis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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