Study on Engine Fault Diagnosis Based on the Abnormal Sound Analysis in Transformation Domain

Li, Jun; Dong, Xisong; Song, Yaji; Song, Nuan

doi:10.1109/icdma.2013.302

Cited by 2 publications

(4 citation statements)

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“…Li Jun, Dong Xingwen, Song Yaji, and Song Nuan conduct research to extract an engine sound from an environment noise with homomorphic analysis method continued with cepstrum lines to determine the engine condition. Result of the research said that with more cepstrum lines the accuracy to recognize the engine condition will increase as well [9].…”

Section: Introductionmentioning

confidence: 99%

“…It is can be done because engine acoustic sound can relay an information regarding its condition [4][5][6][7]. As for example that using sound as source of information are underwater target recognition [8][9]. Acoustic sound that are produce by engine can be categorize as "healthy" if there are no knocking sound, rattling sound, and hunting sound [9].…”

Section: Introductionmentioning

confidence: 99%

“…As for example that using sound as source of information are underwater target recognition [8][9]. Acoustic sound that are produce by engine can be categorize as "healthy" if there are no knocking sound, rattling sound, and hunting sound [9]. Therefore engine condition can be known by using acoustic sound of the engine.…”

Section: Introductionmentioning

confidence: 99%

“…Similar research have been conducted several time using various method. Among them wavelet transform [5], [8][9][10][11] is more popular then the other. Other method such as linier prediction analysis method [4], blind source separation (BSS) method [3], homomorphic analysis method [9] and Hilbert-Huang Transform (HHT) [12] have also been used to conduct research regarding acoustic sound of the engine condition.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The condition monitoring of diesel engines using acoustic signal analysis

Prasetyo¹,

Alaydrus²

2019

IJEECS

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<span>Engine have become one of the supportive asset for many activity and work, therefore engine need attention for its condition. The easiest way to do is through the acoustic sound of the engine itself. Most of the time, the engine sounds are checked using a traditional way that may causing a debate regarding its condition. This is due to no supportive scientific basis to know about engine condition using their own acoustic sound. A value from its frequency pattern is needed as scientific basis to determine an engine condition using acoustic sound. Method of envelope extraction by hilbert transform, fast fourier transform, and correlation coefficient are used to find that value. A series of tests have been carried out on the values that have been found and the result are promising for telling engine condition, but unfortunately the values has not been able to identify type of damage that occur on the engine.</span>

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Section: Introductionmentioning

confidence: 99%