A novel approach for incipient defect detection in rolling bearings using acoustic emission technique

Juan Luis Ferrando Chacon*, Vassilios Kappatos, Wamadeva Balachandran, Tat Hean Gan

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Resumé

Bearings are critical components of rotating machinery and monitoring their condition is important to avoid catastrophic failures and reduce the machinery down-time. Acoustic emission (AE) is gaining ground as a complementary condition monitoring technique as it offers earlier fault detection compared with other more established techniques, such as vibration analysis or oil analysis. However, AE signals always include a significant level of noise reducing the potential of defect detection at early stage. For this reason, this paper proposes a novel envelope analysis method for bearing incipient defect detection. This method is able to identify localized defects in an incipient stage, in which the signal-to-noise ratio (SNR) is extremely low. This method combines Wavelet packet, for AE signal denoising, the Hilbert Transform (HT) for envelope extraction and autocorrelation function, to find patterns in the AE signal. An extensive experimental investigation was carried out in order to evaluate the performance of the proposed method under extremely low SNR, adding high level of noise to the signals. The results indicate that the proposed enhanced envelope method is able to detect incipient defects with 9 dB lower SNR than traditional envelope analysis.

OriginalsprogEngelsk
TidsskriftApplied Acoustics
Vol/bind89
Sider (fra-til)88-100
ISSN0003-682X
DOI
StatusUdgivet - 2015
Udgivet eksterntJa

Fingeraftryk

acoustic emission
envelopes
signal to noise ratios
defects
machinery
downtime
fault detection
autocorrelation
oils
vibration

Citer dette

Ferrando Chacon, Juan Luis ; Kappatos, Vassilios ; Balachandran, Wamadeva ; Gan, Tat Hean. / A novel approach for incipient defect detection in rolling bearings using acoustic emission technique. I: Applied Acoustics. 2015 ; Bind 89. s. 88-100.
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title = "A novel approach for incipient defect detection in rolling bearings using acoustic emission technique",
abstract = "Bearings are critical components of rotating machinery and monitoring their condition is important to avoid catastrophic failures and reduce the machinery down-time. Acoustic emission (AE) is gaining ground as a complementary condition monitoring technique as it offers earlier fault detection compared with other more established techniques, such as vibration analysis or oil analysis. However, AE signals always include a significant level of noise reducing the potential of defect detection at early stage. For this reason, this paper proposes a novel envelope analysis method for bearing incipient defect detection. This method is able to identify localized defects in an incipient stage, in which the signal-to-noise ratio (SNR) is extremely low. This method combines Wavelet packet, for AE signal denoising, the Hilbert Transform (HT) for envelope extraction and autocorrelation function, to find patterns in the AE signal. An extensive experimental investigation was carried out in order to evaluate the performance of the proposed method under extremely low SNR, adding high level of noise to the signals. The results indicate that the proposed enhanced envelope method is able to detect incipient defects with 9 dB lower SNR than traditional envelope analysis.",
keywords = "Acoustic emission, Bearing, Defect detection, Rotating machinery, Wavelet packet",
author = "{Ferrando Chacon}, {Juan Luis} and Vassilios Kappatos and Wamadeva Balachandran and Gan, {Tat Hean}",
year = "2015",
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language = "English",
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A novel approach for incipient defect detection in rolling bearings using acoustic emission technique. / Ferrando Chacon, Juan Luis; Kappatos, Vassilios; Balachandran, Wamadeva; Gan, Tat Hean.

I: Applied Acoustics, Bind 89, 2015, s. 88-100.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - A novel approach for incipient defect detection in rolling bearings using acoustic emission technique

AU - Ferrando Chacon, Juan Luis

AU - Kappatos, Vassilios

AU - Balachandran, Wamadeva

AU - Gan, Tat Hean

PY - 2015

Y1 - 2015

N2 - Bearings are critical components of rotating machinery and monitoring their condition is important to avoid catastrophic failures and reduce the machinery down-time. Acoustic emission (AE) is gaining ground as a complementary condition monitoring technique as it offers earlier fault detection compared with other more established techniques, such as vibration analysis or oil analysis. However, AE signals always include a significant level of noise reducing the potential of defect detection at early stage. For this reason, this paper proposes a novel envelope analysis method for bearing incipient defect detection. This method is able to identify localized defects in an incipient stage, in which the signal-to-noise ratio (SNR) is extremely low. This method combines Wavelet packet, for AE signal denoising, the Hilbert Transform (HT) for envelope extraction and autocorrelation function, to find patterns in the AE signal. An extensive experimental investigation was carried out in order to evaluate the performance of the proposed method under extremely low SNR, adding high level of noise to the signals. The results indicate that the proposed enhanced envelope method is able to detect incipient defects with 9 dB lower SNR than traditional envelope analysis.

AB - Bearings are critical components of rotating machinery and monitoring their condition is important to avoid catastrophic failures and reduce the machinery down-time. Acoustic emission (AE) is gaining ground as a complementary condition monitoring technique as it offers earlier fault detection compared with other more established techniques, such as vibration analysis or oil analysis. However, AE signals always include a significant level of noise reducing the potential of defect detection at early stage. For this reason, this paper proposes a novel envelope analysis method for bearing incipient defect detection. This method is able to identify localized defects in an incipient stage, in which the signal-to-noise ratio (SNR) is extremely low. This method combines Wavelet packet, for AE signal denoising, the Hilbert Transform (HT) for envelope extraction and autocorrelation function, to find patterns in the AE signal. An extensive experimental investigation was carried out in order to evaluate the performance of the proposed method under extremely low SNR, adding high level of noise to the signals. The results indicate that the proposed enhanced envelope method is able to detect incipient defects with 9 dB lower SNR than traditional envelope analysis.

KW - Acoustic emission

KW - Bearing

KW - Defect detection

KW - Rotating machinery

KW - Wavelet packet

U2 - 10.1016/j.apacoust.2014.09.002

DO - 10.1016/j.apacoust.2014.09.002

M3 - Journal article

AN - SCOPUS:84907714280

VL - 89

SP - 88

EP - 100

JO - Applied Acoustics

JF - Applied Acoustics

SN - 0003-682X

ER -