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 journalArticle


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

All Science Journal Classification (ASJC) codes

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

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