Detection of machine soft foot with vibration analysis

Faris Elasha, C. Ruiz-Carcel, D. Mba, V. H. Jaramillo, J. R. Ottewill

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Soft foot is considered to be one of the main causes of vibration problems in rotating machinery. However, there have been relatively limited research efforts to develop robust diagnosis tools for the early detection of such problems, particularly in scenarios where the operational vibration background noise of the machine is high. All previous studies have utilised the Fourier spectrum to diagnose soft foot symptoms. The present study is aimed at developing a series of signal processing techniques to reduce the effect of vibration background noise whilst extracting the fault feature. Three signal processing techniques were applied: adaptive filter, spectral kurtosis and envelope analysis. All three techniques were applied to measured vibration signals acquired from a motor-compressor test-rig. In conclusion, it is shown that the techniques detected motor soft foot more effectively than the conventional spectral method.
Original languageEnglish
Pages (from-to)622-626
JournalInsight - Non-Destructive Testing and Condition Monitoring
Volume56
Issue number11
DOIs
Publication statusPublished - 1 Nov 2014
Externally publishedYes

Fingerprint

Vibration analysis
Signal processing
Rotating machinery
Adaptive filters
Compressors

Bibliographical note

The full text is currently unavailable on the repository.

Cite this

Detection of machine soft foot with vibration analysis. / Elasha, Faris; Ruiz-Carcel, C.; Mba, D.; Jaramillo, V. H.; Ottewill, J. R.

In: Insight - Non-Destructive Testing and Condition Monitoring, Vol. 56, No. 11, 01.11.2014, p. 622-626.

Research output: Contribution to journalArticle

Elasha, Faris ; Ruiz-Carcel, C. ; Mba, D. ; Jaramillo, V. H. ; Ottewill, J. R. / Detection of machine soft foot with vibration analysis. In: Insight - Non-Destructive Testing and Condition Monitoring. 2014 ; Vol. 56, No. 11. pp. 622-626.
@article{e58a10b3d11d49e88caf804d53fc74e0,
title = "Detection of machine soft foot with vibration analysis",
abstract = "Soft foot is considered to be one of the main causes of vibration problems in rotating machinery. However, there have been relatively limited research efforts to develop robust diagnosis tools for the early detection of such problems, particularly in scenarios where the operational vibration background noise of the machine is high. All previous studies have utilised the Fourier spectrum to diagnose soft foot symptoms. The present study is aimed at developing a series of signal processing techniques to reduce the effect of vibration background noise whilst extracting the fault feature. Three signal processing techniques were applied: adaptive filter, spectral kurtosis and envelope analysis. All three techniques were applied to measured vibration signals acquired from a motor-compressor test-rig. In conclusion, it is shown that the techniques detected motor soft foot more effectively than the conventional spectral method.",
author = "Faris Elasha and C. Ruiz-Carcel and D. Mba and Jaramillo, {V. H.} and Ottewill, {J. R.}",
note = "The full text is currently unavailable on the repository.",
year = "2014",
month = "11",
day = "1",
doi = "10.1784/insi.2014.56.11.622",
language = "English",
volume = "56",
pages = "622--626",
journal = "Insight: Non-Destructive Testing and Condition Monitoring",
issn = "1354-2575",
publisher = "British Institute of Non-destructive Testing",
number = "11",

}

TY - JOUR

T1 - Detection of machine soft foot with vibration analysis

AU - Elasha, Faris

AU - Ruiz-Carcel, C.

AU - Mba, D.

AU - Jaramillo, V. H.

AU - Ottewill, J. R.

N1 - The full text is currently unavailable on the repository.

PY - 2014/11/1

Y1 - 2014/11/1

N2 - Soft foot is considered to be one of the main causes of vibration problems in rotating machinery. However, there have been relatively limited research efforts to develop robust diagnosis tools for the early detection of such problems, particularly in scenarios where the operational vibration background noise of the machine is high. All previous studies have utilised the Fourier spectrum to diagnose soft foot symptoms. The present study is aimed at developing a series of signal processing techniques to reduce the effect of vibration background noise whilst extracting the fault feature. Three signal processing techniques were applied: adaptive filter, spectral kurtosis and envelope analysis. All three techniques were applied to measured vibration signals acquired from a motor-compressor test-rig. In conclusion, it is shown that the techniques detected motor soft foot more effectively than the conventional spectral method.

AB - Soft foot is considered to be one of the main causes of vibration problems in rotating machinery. However, there have been relatively limited research efforts to develop robust diagnosis tools for the early detection of such problems, particularly in scenarios where the operational vibration background noise of the machine is high. All previous studies have utilised the Fourier spectrum to diagnose soft foot symptoms. The present study is aimed at developing a series of signal processing techniques to reduce the effect of vibration background noise whilst extracting the fault feature. Three signal processing techniques were applied: adaptive filter, spectral kurtosis and envelope analysis. All three techniques were applied to measured vibration signals acquired from a motor-compressor test-rig. In conclusion, it is shown that the techniques detected motor soft foot more effectively than the conventional spectral method.

U2 - 10.1784/insi.2014.56.11.622

DO - 10.1784/insi.2014.56.11.622

M3 - Article

VL - 56

SP - 622

EP - 626

JO - Insight: Non-Destructive Testing and Condition Monitoring

JF - Insight: Non-Destructive Testing and Condition Monitoring

SN - 1354-2575

IS - 11

ER -