Induction motor bearings diagnostic using MCSA and normalized tripple covariance

Tomasz Ciszewski, Leon Swędrowski, Len Gelman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Diagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is so important. The article provides an overview of selected methods of diagnosis of induction motor bearings, based on measurement of the supply current. The problem here is the high disturbance components level of the motor current in relation to diagnostic components. The paper presents the new approach to signal analysis solutions, based on statistical methods, which have been adapted to be used by this diagnostic system. First experimental results with use of this method are also presented, they confirm the advantages of this method.

Original languageEnglish
Title of host publicationProceedings - SDEMPED 2015
Subtitle of host publicationIEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages333-337
Number of pages5
ISBN (Electronic)9781479977437
DOIs
Publication statusPublished - 21 Oct 2015
Externally publishedYes
Event10th IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives - Guarda, Portugal
Duration: 1 Sep 20154 Sep 2015
Conference number: 10

Conference

Conference10th IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives
Abbreviated titleSDEMPED 2015
CountryPortugal
CityGuarda
Period1/09/154/09/15

Fingerprint

Bearings (structural)
Induction motors
Signal analysis
Statistical methods
Statistics
Engines
Industry

Cite this

Ciszewski, T., Swędrowski, L., & Gelman, L. (2015). Induction motor bearings diagnostic using MCSA and normalized tripple covariance. In Proceedings - SDEMPED 2015: IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (pp. 333-337). [7303711] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DEMPED.2015.7303711
Ciszewski, Tomasz ; Swędrowski, Leon ; Gelman, Len. / Induction motor bearings diagnostic using MCSA and normalized tripple covariance. Proceedings - SDEMPED 2015: IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 333-337
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abstract = "Diagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40{\%} of IM damage, therefore bearing diagnosis is so important. The article provides an overview of selected methods of diagnosis of induction motor bearings, based on measurement of the supply current. The problem here is the high disturbance components level of the motor current in relation to diagnostic components. The paper presents the new approach to signal analysis solutions, based on statistical methods, which have been adapted to be used by this diagnostic system. First experimental results with use of this method are also presented, they confirm the advantages of this method.",
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Ciszewski, T, Swędrowski, L & Gelman, L 2015, Induction motor bearings diagnostic using MCSA and normalized tripple covariance. in Proceedings - SDEMPED 2015: IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives., 7303711, Institute of Electrical and Electronics Engineers Inc., pp. 333-337, 10th IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, Guarda, Portugal, 1/09/15. https://doi.org/10.1109/DEMPED.2015.7303711

Induction motor bearings diagnostic using MCSA and normalized tripple covariance. / Ciszewski, Tomasz; Swędrowski, Leon; Gelman, Len.

Proceedings - SDEMPED 2015: IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives. Institute of Electrical and Electronics Engineers Inc., 2015. p. 333-337 7303711.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Induction motor bearings diagnostic using MCSA and normalized tripple covariance

AU - Ciszewski, Tomasz

AU - Swędrowski, Leon

AU - Gelman, Len

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N2 - Diagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is so important. The article provides an overview of selected methods of diagnosis of induction motor bearings, based on measurement of the supply current. The problem here is the high disturbance components level of the motor current in relation to diagnostic components. The paper presents the new approach to signal analysis solutions, based on statistical methods, which have been adapted to be used by this diagnostic system. First experimental results with use of this method are also presented, they confirm the advantages of this method.

AB - Diagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is so important. The article provides an overview of selected methods of diagnosis of induction motor bearings, based on measurement of the supply current. The problem here is the high disturbance components level of the motor current in relation to diagnostic components. The paper presents the new approach to signal analysis solutions, based on statistical methods, which have been adapted to be used by this diagnostic system. First experimental results with use of this method are also presented, they confirm the advantages of this method.

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Ciszewski T, Swędrowski L, Gelman L. Induction motor bearings diagnostic using MCSA and normalized tripple covariance. In Proceedings - SDEMPED 2015: IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives. Institute of Electrical and Electronics Engineers Inc. 2015. p. 333-337. 7303711 https://doi.org/10.1109/DEMPED.2015.7303711