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Fault Diagnosis of Induction Motor Using D-Q Simplified Model and Parity Equations

Author

Listed:
  • Marco Antonio Rodriguez-Blanco

    (Faculty of Engineering, Autonomous University of Carmen (UNACAR), Ciudad del Carmen 24180, Mexico)

  • Victor Golikov

    (Faculty of Engineering, Autonomous University of Carmen (UNACAR), Ciudad del Carmen 24180, Mexico)

  • René Osorio-Sánchez

    (Computer Science and Engineering Department, University of Guadalajara, Ameca 46600, Mexico)

  • Oleg Samovarov

    (Department of Physics, Ivannikov Institute for System Programming of the Russian Academy of Sciences, 109004 Moscow, Russia)

  • Gerardo Ortiz-Torres

    (Computer Science and Engineering Department, University of Guadalajara, Ameca 46600, Mexico)

  • Rafael Sanchez-Lara

    (Faculty of Engineering, Autonomous University of Carmen (UNACAR), Ciudad del Carmen 24180, Mexico)

  • Jose Luis Vazquez-Avila

    (Faculty of Engineering, Autonomous University of Carmen (UNACAR), Ciudad del Carmen 24180, Mexico)

Abstract

Induction motors are the horsepower in the industrial environment, and among them, 3-phase induction motors (3PIMs) stand out for their robustness and standard 3-phase power supply. In the literature, there are many approaches to diagnose faults for the nonlinear 3PIM model, and the vast majority focus on a single motor fault, although others address more faults but at the cost of greater computational complexity. In this sense, one of the methods with less computational load and early detection is the parity equation approach, which is based on analyzing the discrepancy between the input and output signals of a real process and a linear mathematical model to generate a residual signal, which contains important information about the fault and is obtained through a suitable selection of a weighting matrix W to isolate the faults as much as possible. The problem in this case study is that the 3PIM model is a nonlinear system. In this work, the fault detection method based on the parity equations approach applied in the 3PIM is explored using a simplified and proposed model of the 3PIM working in the D-Q synchronous reference frame, which is matched with the direct current motor model to guarantee both the existence of the parity space and to ensure a large set of detectable faults in the 3PIM parameters. Simulation and experimental results validate the proposed scheme and confirm a very simple set of residual equations to guarantee both early detection and a large set of detectable faults in: Stator and rotor resistances, stator and rotor inductances, as well as current, voltage, and speed sensors. Additionally, development of human machine interface (HMI) is implemented to validate the proposed scheme.

Suggested Citation

  • Marco Antonio Rodriguez-Blanco & Victor Golikov & René Osorio-Sánchez & Oleg Samovarov & Gerardo Ortiz-Torres & Rafael Sanchez-Lara & Jose Luis Vazquez-Avila, 2022. "Fault Diagnosis of Induction Motor Using D-Q Simplified Model and Parity Equations," Energies, MDPI, vol. 15(22), pages 1-19, November.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8372-:d:967676
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    References listed on IDEAS

    as
    1. Hong-Chan Chang & Yu-Ming Jheng & Cheng-Chien Kuo & Yu-Min Hsueh, 2019. "Induction Motors Condition Monitoring System with Fault Diagnosis Using a Hybrid Approach," Energies, MDPI, vol. 12(8), pages 1-12, April.
    2. Isac Antônio dos Santos Areias & Luiz Eduardo Borges da Silva & Erik Leandro Bonaldi & Levy Ely de Lacerda de Oliveira & Germano Lambert-Torres & Vitor Almeida Bernardes, 2019. "Evaluation of Current Signature in Bearing Defects by Envelope Analysis of the Vibration in Induction Motors," Energies, MDPI, vol. 12(21), pages 1-15, October.
    3. Maciej Skowron & Teresa Orlowska-Kowalska & Marcin Wolkiewicz & Czeslaw T. Kowalski, 2020. "Convolutional Neural Network-Based Stator Current Data-Driven Incipient Stator Fault Diagnosis of Inverter-Fed Induction Motor," Energies, MDPI, vol. 13(6), pages 1-21, March.
    4. Syaiful Bakhri & Nesimi Ertugrul, 2022. "A Negative Sequence Current Phasor Compensation Technique for the Accurate Detection of Stator Shorted Turn Faults in Induction Motors," Energies, MDPI, vol. 15(9), pages 1-17, April.
    5. Arkadiusz Duda & Piotr Drozdowski, 2020. "Induction Motor Fault Diagnosis Based on Zero-Sequence Current Analysis," Energies, MDPI, vol. 13(24), pages 1-25, December.
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