Continuous wavelet transform technique for fault signal diagnosis of internal combustion engines

Jian-Da Wu, Jien Chen Chen

Research output: Contribution to journalArticle

124 Citations (Scopus)

Abstract

A fault signal diagnosis technique for internal combustion engines that uses a continuous wavelet transform algorithm is presented in this paper. The use of mechanical vibration and acoustic emission signals for fault diagnosis in rotating machinery has grown significantly due to advances in the progress of digital signal processing algorithms and implementation techniques. The conventional diagnosis technology using acoustic and vibration signals already exists in the form of techniques applying the time and frequency domain of signals, and analyzing the difference of signals in the spectrum. Unfortunately, in some applications the performance is limited, such as when a smearing problem arises at various rates of engine revolution, or when the signals caused by a damaged element are buried in broadband background noise. In the present study, a continuous wavelet transform technique for the fault signal diagnosis is proposed. In the experimental work, the proposed continuous wavelet algorithm was used for fault signal diagnosis in an internal combustion engine and its cooling system. The experimental results indicated that the proposed continuous wavelet transform technique is effective in fault signal diagnosis for both experimental cases. Furthermore, a characteristic analysis and experimental comparison of the vibration signal and acoustic emission signal analysis with the proposed algorithm are also presented in this report.

Original languageEnglish
Pages (from-to)304-311
Number of pages8
JournalNDT and E International
Volume39
Issue number4
DOIs
Publication statusPublished - 2006 Jun 1

Fingerprint

internal combustion engines
Internal combustion engines
wavelet analysis
Wavelet transforms
Vibrations (mechanical)
Acoustic emissions
Rotating machinery
Signal analysis
acoustic emission
Digital signal processing
Cooling systems
vibration
Failure analysis
Acoustics
Engines
signal analysis
cooling systems
machinery
background noise
engines

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Condensed Matter Physics
  • Mechanical Engineering

Cite this

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abstract = "A fault signal diagnosis technique for internal combustion engines that uses a continuous wavelet transform algorithm is presented in this paper. The use of mechanical vibration and acoustic emission signals for fault diagnosis in rotating machinery has grown significantly due to advances in the progress of digital signal processing algorithms and implementation techniques. The conventional diagnosis technology using acoustic and vibration signals already exists in the form of techniques applying the time and frequency domain of signals, and analyzing the difference of signals in the spectrum. Unfortunately, in some applications the performance is limited, such as when a smearing problem arises at various rates of engine revolution, or when the signals caused by a damaged element are buried in broadband background noise. In the present study, a continuous wavelet transform technique for the fault signal diagnosis is proposed. In the experimental work, the proposed continuous wavelet algorithm was used for fault signal diagnosis in an internal combustion engine and its cooling system. The experimental results indicated that the proposed continuous wavelet transform technique is effective in fault signal diagnosis for both experimental cases. Furthermore, a characteristic analysis and experimental comparison of the vibration signal and acoustic emission signal analysis with the proposed algorithm are also presented in this report.",
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Continuous wavelet transform technique for fault signal diagnosis of internal combustion engines. / Wu, Jian-Da; Chen, Jien Chen.

In: NDT and E International, Vol. 39, No. 4, 01.06.2006, p. 304-311.

Research output: Contribution to journalArticle

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