Rolling Mill Cycloconverter Condition Assessment by Harmonic Current via Time-Frequency Signature

Timothy Mitchell Thompkins; Do In Kim; Philip Stone; Yong June Shin

doi:10.1109/TII.2017.2753282

Rolling Mill Cycloconverter Condition Assessment by Harmonic Current via Time-Frequency Signature

Timothy Mitchell Thompkins, Do In Kim, Philip Stone, Yong June Shin

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

High-power industrial rolling mills rely heavily on the sustained operation of cycloconverters, a type of variable-frequency drive. This research proposes a methodology, which observes and diagnoses the operation of cycloconverters as either normal or abnormal by use of time-frequency signature analysis. Various features of the cycloconverter's input current in the time-frequency domain are identified and used to derive parameters that describe these two states in a quantitative manner. A reference model using the parameters is then developed, and comparisons in the time-frequency domain to real data are implemented. Based on these comparisons, a statistical decision boundary is delineated that is used to classify the health status of the cycloconverter.

Original language	English
Article number	8039228
Pages (from-to)	4376-4384
Number of pages	9
Journal	IEEE Transactions on Industrial Informatics
Volume	14
Issue number	10
DOIs	https://doi.org/10.1109/TII.2017.2753282
Publication status	Published - 2018 Oct

Bibliographical note

Funding Information:
Manuscript received July 30, 2017; accepted August 28, 2017. Date of publication September 18, 2017; date of current version October 3, 2018. This work was supported under the framework of international co-operation program managed by National Research Foundation of Korea (NRF) #2017K1A4A3013579 and by the NRF grant funded by the Ministry of Science, ICT & Future Planning #NRF-2017R1A2A1A05001022. Paper no. TII-17-1686. (Corresponding author: Yong-June Shin.) T. M. Thompkins is with Triumph Integrated Systems, Seattle, WA 98053 USA (e-mail: mitchell.thompkins@gmail.com).

Publisher Copyright:
© 2005-2012 IEEE.

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Information Systems
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TII.2017.2753282

Cite this

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title = "Rolling Mill Cycloconverter Condition Assessment by Harmonic Current via Time-Frequency Signature",

abstract = "High-power industrial rolling mills rely heavily on the sustained operation of cycloconverters, a type of variable-frequency drive. This research proposes a methodology, which observes and diagnoses the operation of cycloconverters as either normal or abnormal by use of time-frequency signature analysis. Various features of the cycloconverter's input current in the time-frequency domain are identified and used to derive parameters that describe these two states in a quantitative manner. A reference model using the parameters is then developed, and comparisons in the time-frequency domain to real data are implemented. Based on these comparisons, a statistical decision boundary is delineated that is used to classify the health status of the cycloconverter.",

author = "Thompkins, {Timothy Mitchell} and Kim, {Do In} and Philip Stone and Shin, {Yong June}",

note = "Funding Information: Manuscript received July 30, 2017; accepted August 28, 2017. Date of publication September 18, 2017; date of current version October 3, 2018. This work was supported under the framework of international co-operation program managed by National Research Foundation of Korea (NRF) #2017K1A4A3013579 and by the NRF grant funded by the Ministry of Science, ICT & Future Planning #NRF-2017R1A2A1A05001022. Paper no. TII-17-1686. (Corresponding author: Yong-June Shin.) T. M. Thompkins is with Triumph Integrated Systems, Seattle, WA 98053 USA (e-mail: mitchell.thompkins@gmail.com). Publisher Copyright: {\textcopyright} 2005-2012 IEEE.",

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AB - High-power industrial rolling mills rely heavily on the sustained operation of cycloconverters, a type of variable-frequency drive. This research proposes a methodology, which observes and diagnoses the operation of cycloconverters as either normal or abnormal by use of time-frequency signature analysis. Various features of the cycloconverter's input current in the time-frequency domain are identified and used to derive parameters that describe these two states in a quantitative manner. A reference model using the parameters is then developed, and comparisons in the time-frequency domain to real data are implemented. Based on these comparisons, a statistical decision boundary is delineated that is used to classify the health status of the cycloconverter.

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Rolling Mill Cycloconverter Condition Assessment by Harmonic Current via Time-Frequency Signature

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