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Industrial Process Diagnosis based on Information-based Features

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preprint
posted on 2022-02-23, 02:48 authored by Dorel AiordachioaieDorel Aiordachioaie
Change detection and diagnosis based on information-based features is considered. As benchmark case study, the faults of bearings are selected. Information from the working states, including those generated by faults in bearings, are transformed and carried by the vibration’s signals, which are further processed by advanced techniques of information and signal processing, as e.g., statistical models, Renyi and Tsallis entropies, and other complexity measures.

History

Email Address of Submitting Author

Dorel.Aiordachioaie@ugal.ro

Submitting Author's Institution

Dunarea de Jos University of Galati

Submitting Author's Country

  • Romania