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Smart-Sensors to Estimate Insulation Health in Induction Motors via Analysis of Stray Flux

Author

Listed:
  • Israel Zamudio-Ramirez

    (Engineering Faculty, San Juan del Río Campus, Universidad Autónoma de Querétaro, Av. Río Moctezuma 249, C.P. 76808 San Juan del Río, Querétaro, México)

  • Roque Alfredo Osornio-Rios

    (Engineering Faculty, San Juan del Río Campus, Universidad Autónoma de Querétaro, Av. Río Moctezuma 249, C.P. 76808 San Juan del Río, Querétaro, México)

  • Miguel Trejo-Hernandez

    (Engineering Faculty, San Juan del Río Campus, Universidad Autónoma de Querétaro, Av. Río Moctezuma 249, C.P. 76808 San Juan del Río, Querétaro, México)

  • Rene de Jesus Romero-Troncoso

    (Engineering Faculty, San Juan del Río Campus, Universidad Autónoma de Querétaro, Av. Río Moctezuma 249, C.P. 76808 San Juan del Río, Querétaro, México)

  • Jose Alfonso Antonino-Daviu

    (Instituto Tecnológico de la Energía, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain)

Abstract

Induction motors (IMs) are essential components in industrial applications. These motors have to perform numerous tasks under a wide variety of conditions, which affects performance and reliability and gradually brings faults and efficiency losses over time. Nowadays, the industrial sector demands the necessary integration of smart-sensors to effectively diagnose faults in these kinds of motors before faults can occur. One of the most frequent causes of failure in IMs is the degradation of turn insulation in windings. If this anomaly is present, an electric motor can keep working with apparent normality, but factors such as the efficiency of energy consumption and mechanical reliability may be reduced considerably. Furthermore, if not detected at an early stage, this degradation could lead to the breakdown of the insulation system, which could in turn cause catastrophic and irreversible failure to the electrical machine. This paper proposes a novel methodology and its application in a smart-sensor to detect and estimate the healthiness of the winding insulation in IMs. This methodology relies on the analysis of the external magnetic field captured by a coil sensor by applying suitable time-frequency decomposition (TFD) tools. The discrete wavelet transform (DWT) is used to decompose the signal into different approximation and detail coefficients as a pre-processing stage to isolate the studied fault. Then, due to the importance of diagnosing stator winding insulation faults during motor operation at an early stage, this proposal introduces an indicator based on wavelet entropy (WE), a single parameter capable of performing an efficient diagnosis. A smart-sensor is able to estimate winding insulation degradation in IMs using two inexpensive, reliable, and noninvasive primary sensors: a coil sensor and an E-type thermocouple sensor. The utility of these sensors is demonstrated through the results obtained from analyzing six similar IMs with differently induced severity faults.

Suggested Citation

  • Israel Zamudio-Ramirez & Roque Alfredo Osornio-Rios & Miguel Trejo-Hernandez & Rene de Jesus Romero-Troncoso & Jose Alfonso Antonino-Daviu, 2019. "Smart-Sensors to Estimate Insulation Health in Induction Motors via Analysis of Stray Flux," Energies, MDPI, vol. 12(9), pages 1-16, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1658-:d:227487
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    References listed on IDEAS

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    1. Miguel E. Iglesias-Martínez & Jose Alfonso Antonino-Daviu & Pedro Fernández de Córdoba & J. Alberto Conejero, 2019. "Rotor Fault Detection in Induction Motors Based on Time-Frequency Analysis Using the Bispectrum and the Autocovariance of Stray Flux Signals," Energies, MDPI, vol. 12(4), pages 1-16, February.
    2. Luo Wang & Yonggang Li & Junqing Li, 2018. "Diagnosis of Inter-Turn Short Circuit of Synchronous Generator Rotor Winding Based on Volterra Kernel Identification," Energies, MDPI, vol. 11(10), pages 1-15, September.
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    Cited by:

    1. Yury Kuznetsov & Igor Kravchenko & Dmitry Gerashchenkov & Mikhail Markov & Vadim Davydov & Anna Mozhayko & Valentin Dudkin & Alina Bykova, 2022. "The Use of Cold Spraying and Micro-Arc Oxidation Techniques for the Repairing and Wear Resistance Improvement of Motor Electric Bearing Shields," Energies, MDPI, vol. 15(3), pages 1-12, January.
    2. Mateusz Dybkowski & Szymon Antoni Bednarz, 2019. "Modified Rotor Flux Estimators for Stator-Fault-Tolerant Vector Controlled Induction Motor Drives," Energies, MDPI, vol. 12(17), pages 1-21, August.

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