Gear Wear Process Monitoring Using a Sideband Estimator Based on Modulation Signal Bispectrum

Ruiliang Zhang, Xi Gu, Fengshou Gu, Tie Wang, Andrew Ball

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

As one of the most common gear failure modes, tooth wear can produce nonlinear modulation sidebands in the vibration frequency spectrum. However, limited research has been reported in monitoring the gear wear based on vibration due to the lack of tools which can effectively extract the small sidebands. In order to accurately monitor gear wear progression in a timely fashion, this paper presents a gear wear condition monitoring approach based on vibration signal analysis using the modulation signal bispectrum-based sideband estimator (MSB-SE) method. The vibration signals are collected using a run-to-failure test of gearbox under an accelerated test process. MSB analysis was performed on the vibration signals to extract the sideband information. Using a combination of the peak value of MSB-SE and the coherence of MSB-SE, the overall information of gear transmission system can be obtained. Based on the amplitude of MSB-SE peaks, a dimensionless indicator is proposed to assess the effects of gear tooth wear. The results demonstrated that the proposed indicator can be used to accurately and reliably monitor gear tooth wear and evaluate the wear severity.
Original languageEnglish
Article number274
Number of pages10
JournalApplied Sciences
Volume7
Issue number3
DOIs
Publication statusPublished - 10 Mar 2017

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Bispectrum
Process Monitoring
Process monitoring
Gears
Modulation
Wear of materials
Estimator
Vibration Signal
Gear teeth
Monitor
Vibration
Gearbox
Condition Monitoring
Signal Analysis
Frequency Spectrum
Vibration Analysis
Signal analysis
Failure Mode
Condition monitoring
Progression

Cite this

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title = "Gear Wear Process Monitoring Using a Sideband Estimator Based on Modulation Signal Bispectrum",
abstract = "As one of the most common gear failure modes, tooth wear can produce nonlinear modulation sidebands in the vibration frequency spectrum. However, limited research has been reported in monitoring the gear wear based on vibration due to the lack of tools which can effectively extract the small sidebands. In order to accurately monitor gear wear progression in a timely fashion, this paper presents a gear wear condition monitoring approach based on vibration signal analysis using the modulation signal bispectrum-based sideband estimator (MSB-SE) method. The vibration signals are collected using a run-to-failure test of gearbox under an accelerated test process. MSB analysis was performed on the vibration signals to extract the sideband information. Using a combination of the peak value of MSB-SE and the coherence of MSB-SE, the overall information of gear transmission system can be obtained. Based on the amplitude of MSB-SE peaks, a dimensionless indicator is proposed to assess the effects of gear tooth wear. The results demonstrated that the proposed indicator can be used to accurately and reliably monitor gear tooth wear and evaluate the wear severity.",
keywords = "modulation signal bispectrum, gear wear, vibration signal, sideband estimator",
author = "Ruiliang Zhang and Xi Gu and Fengshou Gu and Tie Wang and Andrew Ball",
year = "2017",
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doi = "10.3390/app7030274",
language = "English",
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journal = "Applied Sciences",
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Gear Wear Process Monitoring Using a Sideband Estimator Based on Modulation Signal Bispectrum. / Zhang, Ruiliang; Gu, Xi; Gu, Fengshou; Wang, Tie; Ball, Andrew.

In: Applied Sciences, Vol. 7, No. 3, 274, 10.03.2017.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Gear Wear Process Monitoring Using a Sideband Estimator Based on Modulation Signal Bispectrum

AU - Zhang, Ruiliang

AU - Gu, Xi

AU - Gu, Fengshou

AU - Wang, Tie

AU - Ball, Andrew

PY - 2017/3/10

Y1 - 2017/3/10

N2 - As one of the most common gear failure modes, tooth wear can produce nonlinear modulation sidebands in the vibration frequency spectrum. However, limited research has been reported in monitoring the gear wear based on vibration due to the lack of tools which can effectively extract the small sidebands. In order to accurately monitor gear wear progression in a timely fashion, this paper presents a gear wear condition monitoring approach based on vibration signal analysis using the modulation signal bispectrum-based sideband estimator (MSB-SE) method. The vibration signals are collected using a run-to-failure test of gearbox under an accelerated test process. MSB analysis was performed on the vibration signals to extract the sideband information. Using a combination of the peak value of MSB-SE and the coherence of MSB-SE, the overall information of gear transmission system can be obtained. Based on the amplitude of MSB-SE peaks, a dimensionless indicator is proposed to assess the effects of gear tooth wear. The results demonstrated that the proposed indicator can be used to accurately and reliably monitor gear tooth wear and evaluate the wear severity.

AB - As one of the most common gear failure modes, tooth wear can produce nonlinear modulation sidebands in the vibration frequency spectrum. However, limited research has been reported in monitoring the gear wear based on vibration due to the lack of tools which can effectively extract the small sidebands. In order to accurately monitor gear wear progression in a timely fashion, this paper presents a gear wear condition monitoring approach based on vibration signal analysis using the modulation signal bispectrum-based sideband estimator (MSB-SE) method. The vibration signals are collected using a run-to-failure test of gearbox under an accelerated test process. MSB analysis was performed on the vibration signals to extract the sideband information. Using a combination of the peak value of MSB-SE and the coherence of MSB-SE, the overall information of gear transmission system can be obtained. Based on the amplitude of MSB-SE peaks, a dimensionless indicator is proposed to assess the effects of gear tooth wear. The results demonstrated that the proposed indicator can be used to accurately and reliably monitor gear tooth wear and evaluate the wear severity.

KW - modulation signal bispectrum

KW - gear wear

KW - vibration signal

KW - sideband estimator

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