Model-Based Luenberger State Observer for Detecting Interturn Short Circuits in PM Machines

被引:0
|
作者
Qin, Y. [1 ]
Li, G. J. [1 ]
Zhu, Z. Q. [1 ]
Foster, M. P. [1 ]
Stone, D. A. [1 ]
Jia, C. J. [2 ]
Mckeever, P. [2 ]
机构
[1] Univ Sheffield, Sch Elect & Elect Engn, Sheffield S1 3JD, England
[2] Offshore Renewable Energy Catapult, Blyth NE24 1LZ, Northd, England
关键词
Observers; Circuit faults; Windings; Fault detection; Resistance; Transportation; Electrification; Coils; Fault diagnosis; Contact resistance; interturn short circuit (ITSC); Luenberger observer; PM machine; PWM; FAULT-DIAGNOSIS; WINDINGS; MOTORS;
D O I
10.1109/TTE.2024.3478840
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This article proposes a novel model-based Luenberger state observer for interturn short-circuit (ITSC) fault diagnostics. The residuals between the observed currents and the measured currents in the alpha- and beta-axes serve as fault indicator, which can be used to detect ITSC faults not only at an early stage with contact resistance but also at the fully short-circuited stage. These currents are observed by the Luenberger observer, which is designed under the assumption that the machine is operating in a healthy condition. In addition, the investigation results indicate that with a greater fault ratio, larger load current, and higher speed, detecting the ITSC fault becomes easier. Moreover, three sets of Luenberger observers, assuming the ITSC fault is in phases A, B, and C, have been designed to identify the faulted phase. A series of experiments have been carried out to validate the developed fault detection method.
引用
收藏
页码:5302 / 5311
页数:10
相关论文
共 50 条
  • [1] Detecting interturn short circuits in rotor windings
    Ramírez-Niño, J
    Pascacio, A
    IEEE COMPUTER APPLICATIONS IN POWER, 2001, 14 (04): : 39 - 42
  • [2] Model-Based Diagnosis and RUL Estimation of Induction Machines Under Interturn Fault
    Viethung Nguyen
    Seshadrinath, Jeevanand
    Wang, Danwei
    Nadarajan, Sivakumar
    Vaiyapuri, Viswanathan
    IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2017, 53 (03) : 2690 - 2701
  • [3] Model-Based Field Winding Interturn Fault Detection Method for Brushless Synchronous Machines
    Mahtani, Kumar
    Guerrero, Jose M.
    Beites, Luis F.
    Platero, Carlos A.
    MACHINES, 2022, 10 (12)
  • [4] Model-Based Sensor Fault Detection to Brushless DC Motor using Luenberger Observer
    Eissa, M. Abdullah
    Ahmed, Mahmoud S.
    Darwish, R. R.
    Bassiuny, A. M.
    2015 7th International Conference on Modelling, Identification and Control (ICMIC), 2014, : 320 - 325
  • [5] A signal-based strategy model for the diagnosis of interturn short circuits in PMSM
    Mazzoletti, Manuel A.
    Bossio, Guillermo R.
    De Angelo, Cristian H.
    Espinoza-Trejo, Diego R.
    2016 IEEE BIENNIAL CONGRESS OF ARGENTINA (ARGENCON), 2016,
  • [6] A Model-Based Strategy for Interturn Short-Circuit Fault Diagnosis in PMSM
    Mazzoletti, Manuel A.
    Bossio, Guillermo R.
    De Angelo, Cristian H.
    Espinoza-Trejo, Diego R.
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2017, 64 (09) : 7218 - 7228
  • [7] PWM Voltage-Based Modeling for PM Machines With Interturn Short Circuit Fault Considering the Effect of Drives
    Qin, Ying
    Li, Guang-Jin
    Jia, Chunjiang
    Mckeever, Paul
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2023, 70 (11) : 10981 - 10991
  • [8] Adaptive Dynamic Surface Control of Epileptor Model Based on Nonlinear Luenberger State Observer
    Dolatabadi, Mahdi Kamali
    Kamali, Marzieh
    Shayegh, Farzaneh
    INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2025, 35 (05)
  • [9] A mathematical method for improving the detecting of interturn short circuits in rotor windings of power generators
    Ramírez-Niño, J
    García, A
    Robles, E
    Castaño, VM
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2001, 12 (02) : 213 - 219
  • [10] Novel Generic Fault Model Considering Fundamental and PWM Current Components of PM Machines With Interturn Short-Circuit
    Qin, Y.
    Li, G. J.
    Zhu, Z. Q.
    Foster, M. P.
    Stone, D. A.
    Jia, C. J.
    McKeever, P.
    IEEE TRANSACTIONS ON POWER ELECTRONICS, 2024, 39 (07) : 8709 - 8720