Diagnosis of Incipient Faults in Induction Motors Using MCSA and Thermal Analysis

William Oñate; Ramon Perez; Gustavo Caiza

doi:10.1007/978-3-030-32033-1_8

Diagnosis of Incipient Faults in Induction Motors Using MCSA and Thermal Analysis

Research Group in Electronics Control and Automation (GIECA)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

Induction motors are widely used at industrial level and many researches have been conducted to predict faults and ensure their continuous operation. The present study shows a fault detection system based on the Motor Current Signature Analysis (MCSA) technique which is a non-invasive method, and the Fast Fourier Transform (FFT) algorithm to perform spectral analysis on the current to detect specific components that characterize faults in different conditions such as damaged bearings, shorted winding in turns, and broken bars. The tests were conducted using a motor test bench and the results show a spectral value obtained by FFT in the frequency of 300 Hz for faults in bearings of the motors 1 and 2. Results also reveal coincidence of 96.9% and 99.46% compared to the results obtained through the theoretical equations included in the MCSA technique, representing values that are within the fault frequency bands on 1x and 2x respectively.

Original language	English
Title of host publication	Advances in Emerging Trends and Technologies - Volume 2
Editors	Miguel Botto-Tobar, Joffre León-Acurio, Angela Díaz Cadena, Práxedes Montiel Díaz
Publisher	Springer
Pages	74-84
Number of pages	11
ISBN (Print)	9783030320324
DOIs	https://doi.org/10.1007/978-3-030-32033-1_8
State	Published - 1 Jan 2020
Event	1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019 - EC, quito, Ecuador Duration: 29 May 2019 → 31 May 2019 https://2019.icaett-conferences.org/

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1067
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019
Country/Territory	Ecuador
City	quito
Period	29/05/19 → 31/05/19
Internet address	https://2019.icaett-conferences.org/

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

FFT
Incipient faults
MSCA
Three-phase motor

Access to Document

10.1007/978-3-030-32033-1_8

Cite this

Oñate, W., Perez, R., & Caiza, G. (2020). Diagnosis of Incipient Faults in Induction Motors Using MCSA and Thermal Analysis. In M. Botto-Tobar, J. León-Acurio, A. Díaz Cadena, & P. Montiel Díaz (Eds.), Advances in Emerging Trends and Technologies - Volume 2 (pp. 74-84). (Advances in Intelligent Systems and Computing; Vol. 1067). Springer. https://doi.org/10.1007/978-3-030-32033-1_8

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title = "Diagnosis of Incipient Faults in Induction Motors Using MCSA and Thermal Analysis",

abstract = "Induction motors are widely used at industrial level and many researches have been conducted to predict faults and ensure their continuous operation. The present study shows a fault detection system based on the Motor Current Signature Analysis (MCSA) technique which is a non-invasive method, and the Fast Fourier Transform (FFT) algorithm to perform spectral analysis on the current to detect specific components that characterize faults in different conditions such as damaged bearings, shorted winding in turns, and broken bars. The tests were conducted using a motor test bench and the results show a spectral value obtained by FFT in the frequency of 300 Hz for faults in bearings of the motors 1 and 2. Results also reveal coincidence of 96.9\% and 99.46\% compared to the results obtained through the theoretical equations included in the MCSA technique, representing values that are within the fault frequency bands on 1x and 2x respectively.",

keywords = "FFT, Incipient faults, MSCA, Three-phase motor",

author = "William O{\~n}ate and Ramon Perez and Gustavo Caiza",

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Oñate, W, Perez, R & Caiza, G 2020, Diagnosis of Incipient Faults in Induction Motors Using MCSA and Thermal Analysis. in M Botto-Tobar, J León-Acurio, A Díaz Cadena & P Montiel Díaz (eds), Advances in Emerging Trends and Technologies - Volume 2. Advances in Intelligent Systems and Computing, vol. 1067, Springer, pp. 74-84, 1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019, quito, Ecuador, 29/05/19. https://doi.org/10.1007/978-3-030-32033-1_8

Diagnosis of Incipient Faults in Induction Motors Using MCSA and Thermal Analysis. / Oñate, William; Perez, Ramon; Caiza, Gustavo.
Advances in Emerging Trends and Technologies - Volume 2. ed. / Miguel Botto-Tobar; Joffre León-Acurio; Angela Díaz Cadena; Práxedes Montiel Díaz. Springer, 2020. p. 74-84 (Advances in Intelligent Systems and Computing; Vol. 1067).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Diagnosis of Incipient Faults in Induction Motors Using MCSA and Thermal Analysis

AU - Oñate, William

AU - Perez, Ramon

AU - Caiza, Gustavo

PY - 2020/1/1

Y1 - 2020/1/1

N2 - Induction motors are widely used at industrial level and many researches have been conducted to predict faults and ensure their continuous operation. The present study shows a fault detection system based on the Motor Current Signature Analysis (MCSA) technique which is a non-invasive method, and the Fast Fourier Transform (FFT) algorithm to perform spectral analysis on the current to detect specific components that characterize faults in different conditions such as damaged bearings, shorted winding in turns, and broken bars. The tests were conducted using a motor test bench and the results show a spectral value obtained by FFT in the frequency of 300 Hz for faults in bearings of the motors 1 and 2. Results also reveal coincidence of 96.9% and 99.46% compared to the results obtained through the theoretical equations included in the MCSA technique, representing values that are within the fault frequency bands on 1x and 2x respectively.

AB - Induction motors are widely used at industrial level and many researches have been conducted to predict faults and ensure their continuous operation. The present study shows a fault detection system based on the Motor Current Signature Analysis (MCSA) technique which is a non-invasive method, and the Fast Fourier Transform (FFT) algorithm to perform spectral analysis on the current to detect specific components that characterize faults in different conditions such as damaged bearings, shorted winding in turns, and broken bars. The tests were conducted using a motor test bench and the results show a spectral value obtained by FFT in the frequency of 300 Hz for faults in bearings of the motors 1 and 2. Results also reveal coincidence of 96.9% and 99.46% compared to the results obtained through the theoretical equations included in the MCSA technique, representing values that are within the fault frequency bands on 1x and 2x respectively.

KW - FFT

KW - Incipient faults

KW - MSCA

KW - Three-phase motor

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SN - 9783030320324

T3 - Advances in Intelligent Systems and Computing

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BT - Advances in Emerging Trends and Technologies - Volume 2

A2 - Botto-Tobar, Miguel

A2 - León-Acurio, Joffre

A2 - Díaz Cadena, Angela

A2 - Montiel Díaz, Práxedes

PB - Springer

T2 - 1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019

Y2 - 29 May 2019 through 31 May 2019

ER -

Diagnosis of Incipient Faults in Induction Motors Using MCSA and Thermal Analysis

Abstract

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Bibliographical note

Keywords

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Design of Methodologies for Fog Computing and Intelligent Controllers Based on IEC 61499

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Diagnosis of Incipient Faults in Induction Motors Using MCSA and Thermal Analysis

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Projects

Design of Methodologies for Fog Computing and Intelligent Controllers Based on IEC 61499

Cite this