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

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

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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 languageEnglish
Article number8039228
Pages (from-to)4376-4384
Number of pages9
JournalIEEE Transactions on Industrial Informatics
Issue number10
Publication statusPublished - 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:

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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