Starting current analysis for condition monitoring of medium voltage induction motors in the steel industry

Chanseung Yang; Sang Bin Lee; Geunik Jang; Seongnam Kim; Gyukyung Jung; Junghoon Lee; Sangwook Shim; Young Kab Lim; Jinpyo Kim; Sungbong Park

doi:10.1109/IAS.2017.8101827

Starting current analysis for condition monitoring of medium voltage induction motors in the steel industry

Chanseung Yang, Sang Bin Lee, Geunik Jang, Seongnam Kim, Gyukyung Jung, Junghoon Lee, Sangwook Shim, Young Kab Lim, Jinpyo Kim, Sungbong Park

School of Electrical Engineering

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

4 Citations (Scopus)

Abstract

Failure of medium voltage (MV) induction motors is a major concern in the steel industry considering that it can cause an unplanned outage of the process resulting in significant economic consequences. Predictive maintenance based on offline and on-line testing of the induction motors is therefore critical for maintaining reliable, efficient, and safe plant operation. Many years of experience has shown that the MV induction motor failure rate can be significantly reduced with periodic motor testing, resulting in improved plant reliability and productivity. It has also been observed that false fault indications are commonly produced by commercially available test equipment, and that applying multiple types of tests can improve the reliability of testing. In this paper, the effectiveness of a new test approach based on the analysis of the motor starting current is investigated for detecting defects in the rotor cage and reactor starting. Analysis of the starting data obtained from 614 MV induction motors operating at a steel mill over the last 10+ years showed that the two types of faults were present in 45 MV motors. 7 successful case studies of rotor cage and reactor starting defects are presented to provide insight on the advantages of starting current analysis for induction motor monitoring.

Original language	English
Title of host publication	2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-9
Number of pages	9
Volume	2017-January
ISBN (Electronic)	9781509048946
DOIs	https://doi.org/10.1109/IAS.2017.8101827
Publication status	Published - 2017 Nov 8
Event	2017 IEEE Industry Applications Society Annual Meeting, IAS 2017 - Cincinnati, United States Duration: 2017 Oct 1 → 2017 Oct 5

Other

Other	2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
Country/Territory	United States
City	Cincinnati
Period	17/10/1 → 17/10/5

Keywords

Condition Monitoring
Failure Analysis
Fault Diagnosis
Induction Motors
Predictive Maintenance
Spectral Analysis
Steel Industry

ASJC Scopus subject areas

Industrial and Manufacturing Engineering
Control and Optimization
Energy Engineering and Power Technology
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/IAS.2017.8101827

Cite this

Yang, C., Lee, S. B., Jang, G., Kim, S., Jung, G., Lee, J., Shim, S., Kab Lim, Y., Kim, J., & Park, S. (2017). Starting current analysis for condition monitoring of medium voltage induction motors in the steel industry. In 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017 (Vol. 2017-January, pp. 1-9). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IAS.2017.8101827

Starting current analysis for condition monitoring of medium voltage induction motors in the steel industry. / Yang, Chanseung; Lee, Sang Bin; Jang, Geunik et al.

2017 IEEE Industry Applications Society Annual Meeting, IAS 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-9.

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

Yang, C, Lee, SB, Jang, G, Kim, S, Jung, G, Lee, J, Shim, S, Kab Lim, Y, Kim, J & Park, S 2017, Starting current analysis for condition monitoring of medium voltage induction motors in the steel industry. in 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-9, 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017, Cincinnati, United States, 17/10/1. https://doi.org/10.1109/IAS.2017.8101827

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abstract = "Failure of medium voltage (MV) induction motors is a major concern in the steel industry considering that it can cause an unplanned outage of the process resulting in significant economic consequences. Predictive maintenance based on offline and on-line testing of the induction motors is therefore critical for maintaining reliable, efficient, and safe plant operation. Many years of experience has shown that the MV induction motor failure rate can be significantly reduced with periodic motor testing, resulting in improved plant reliability and productivity. It has also been observed that false fault indications are commonly produced by commercially available test equipment, and that applying multiple types of tests can improve the reliability of testing. In this paper, the effectiveness of a new test approach based on the analysis of the motor starting current is investigated for detecting defects in the rotor cage and reactor starting. Analysis of the starting data obtained from 614 MV induction motors operating at a steel mill over the last 10+ years showed that the two types of faults were present in 45 MV motors. 7 successful case studies of rotor cage and reactor starting defects are presented to provide insight on the advantages of starting current analysis for induction motor monitoring.",

keywords = "Condition Monitoring, Failure Analysis, Fault Diagnosis, Induction Motors, Predictive Maintenance, Spectral Analysis, Steel Industry",

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AB - Failure of medium voltage (MV) induction motors is a major concern in the steel industry considering that it can cause an unplanned outage of the process resulting in significant economic consequences. Predictive maintenance based on offline and on-line testing of the induction motors is therefore critical for maintaining reliable, efficient, and safe plant operation. Many years of experience has shown that the MV induction motor failure rate can be significantly reduced with periodic motor testing, resulting in improved plant reliability and productivity. It has also been observed that false fault indications are commonly produced by commercially available test equipment, and that applying multiple types of tests can improve the reliability of testing. In this paper, the effectiveness of a new test approach based on the analysis of the motor starting current is investigated for detecting defects in the rotor cage and reactor starting. Analysis of the starting data obtained from 614 MV induction motors operating at a steel mill over the last 10+ years showed that the two types of faults were present in 45 MV motors. 7 successful case studies of rotor cage and reactor starting defects are presented to provide insight on the advantages of starting current analysis for induction motor monitoring.

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Starting current analysis for condition monitoring of medium voltage induction motors in the steel industry

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Keywords

ASJC Scopus subject areas

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