An approach for the construction of entropy measure and energy map in machine fault diagnosis

Reza Tafreshi, F. Sassani, H. Ahmadi, G. Dumont

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

This paper presents a novel wavelet-based methodology for feature extraction and classification. To compare the performance of the proposed approach with major existing methods, a number of sets of real-world machine data acquired by mounting accelerometer sensors on the cylinder head of an engine have been extensively tested. The developed method not only bypasses the demerits of the previous techniques but also demonstrates superior performance.

Original languageEnglish
Pages (from-to)245011-245017
Number of pages7
JournalJournal of Vibration and Acoustics, Transactions of the ASME
Volume131
Issue number2
DOIs
Publication statusPublished - Apr 2009

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Cylinder heads
Mountings
Accelerometers
Failure analysis
Feature extraction
Entropy
entropy
Engines
bypasses
Sensors
accelerometers
mounting
pattern recognition
engines
methodology
energy
sensors

ASJC Scopus subject areas

  • Mechanics of Materials
  • Acoustics and Ultrasonics
  • Mechanical Engineering

Cite this

An approach for the construction of entropy measure and energy map in machine fault diagnosis. / Tafreshi, Reza; Sassani, F.; Ahmadi, H.; Dumont, G.

In: Journal of Vibration and Acoustics, Transactions of the ASME, Vol. 131, No. 2, 04.2009, p. 245011-245017.

Research output: Contribution to journalArticle

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