Fault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis

Fengshou Gu, Xiange Tian, Zhi Chen, Tie Wang, Ibrahim.A.M Rehab, Andrew Ball

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Faults in rolling element bearing are among the main causes of breakdown in rotating machines. Vibration is an effective technique for machine condition monitoring. Vibration signals from a defective bearing with a localized fault contain a series of impulsive responses, which result from the impacts of the defective part(s) with other elements. Most researches carried out have focused on fault location identification. However, limited work has been reported for fault severity estimation, which is critical to make decision for maintenance actions. To improve current diagnostic capability, this paper pays more attention to bearing fault severity diagnosis. It models the vibration sources from bearing defects as an impact process with constant size but three different lengths corresponding to outer race fault, inner race fault and roller fault, respectively. Then an experimental study was followed to evaluate this model. Moreover, the conventional envelope analysis of the measured vibration signals from the tested faulty bearings is optimized by spectral kurtosis (SK) for automatic and reliable fault detection and fault category diagnosis. In the meantime, the diagnostic parameters for fault severity estimation: root mean squared (RMS) values and kurtosis amplitude are developed based on the model results and subsequently evaluated to be agreed vigorously with tested fault cases.
LanguageEnglish
Title of host publicationProceedings of International Conference on Advances in Civil, Structural and Mechanical Engineering
PublisherInstitute of Research Engineers and Doctors
Pages20-24
Number of pages5
ISBN (Electronic)9789810788599
Publication statusPublished - 2014
EventInternational Conference on Advances in Civil, Structural and Mechanical Engineering - Bangkok, Thailand
Duration: 4 Jan 20145 Jan 2014

Conference

ConferenceInternational Conference on Advances in Civil, Structural and Mechanical Engineering
Abbreviated titleACSME 2014
CountryThailand
CityBangkok
Period4/01/145/01/14

Fingerprint

Bearings (structural)
Failure analysis
Electric fault location
Condition monitoring
Fault detection
Defects

Cite this

Gu, F., Tian, X., Chen, Z., Wang, T., Rehab, I. A. M., & Ball, A. (2014). Fault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis. In Proceedings of International Conference on Advances in Civil, Structural and Mechanical Engineering (pp. 20-24). [9] Institute of Research Engineers and Doctors.
Gu, Fengshou ; Tian, Xiange ; Chen, Zhi ; Wang, Tie ; Rehab, Ibrahim.A.M ; Ball, Andrew. / Fault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis. Proceedings of International Conference on Advances in Civil, Structural and Mechanical Engineering. Institute of Research Engineers and Doctors, 2014. pp. 20-24
@inproceedings{cc989f052a2346b88160f511ba40772d,
title = "Fault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis",
abstract = "Faults in rolling element bearing are among the main causes of breakdown in rotating machines. Vibration is an effective technique for machine condition monitoring. Vibration signals from a defective bearing with a localized fault contain a series of impulsive responses, which result from the impacts of the defective part(s) with other elements. Most researches carried out have focused on fault location identification. However, limited work has been reported for fault severity estimation, which is critical to make decision for maintenance actions. To improve current diagnostic capability, this paper pays more attention to bearing fault severity diagnosis. It models the vibration sources from bearing defects as an impact process with constant size but three different lengths corresponding to outer race fault, inner race fault and roller fault, respectively. Then an experimental study was followed to evaluate this model. Moreover, the conventional envelope analysis of the measured vibration signals from the tested faulty bearings is optimized by spectral kurtosis (SK) for automatic and reliable fault detection and fault category diagnosis. In the meantime, the diagnostic parameters for fault severity estimation: root mean squared (RMS) values and kurtosis amplitude are developed based on the model results and subsequently evaluated to be agreed vigorously with tested fault cases.",
keywords = "kurtogram, Envelope analysis, Bearing fault diagnosis, elastic deformation, geometry deformation",
author = "Fengshou Gu and Xiange Tian and Zhi Chen and Tie Wang and Ibrahim.A.M Rehab and Andrew Ball",
note = "DOI: 10.3850/978-981-07-8859-9_32 supplied by website/publisher no longer works HN 07/08/2017",
year = "2014",
language = "English",
pages = "20--24",
booktitle = "Proceedings of International Conference on Advances in Civil, Structural and Mechanical Engineering",
publisher = "Institute of Research Engineers and Doctors",

}

Gu, F, Tian, X, Chen, Z, Wang, T, Rehab, IAM & Ball, A 2014, Fault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis. in Proceedings of International Conference on Advances in Civil, Structural and Mechanical Engineering., 9, Institute of Research Engineers and Doctors, pp. 20-24, International Conference on Advances in Civil, Structural and Mechanical Engineering, Bangkok, Thailand, 4/01/14.

Fault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis. / Gu, Fengshou; Tian, Xiange; Chen, Zhi; Wang, Tie; Rehab, Ibrahim.A.M; Ball, Andrew.

Proceedings of International Conference on Advances in Civil, Structural and Mechanical Engineering. Institute of Research Engineers and Doctors, 2014. p. 20-24 9.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Fault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis

AU - Gu, Fengshou

AU - Tian, Xiange

AU - Chen, Zhi

AU - Wang, Tie

AU - Rehab, Ibrahim.A.M

AU - Ball, Andrew

N1 - DOI: 10.3850/978-981-07-8859-9_32 supplied by website/publisher no longer works HN 07/08/2017

PY - 2014

Y1 - 2014

N2 - Faults in rolling element bearing are among the main causes of breakdown in rotating machines. Vibration is an effective technique for machine condition monitoring. Vibration signals from a defective bearing with a localized fault contain a series of impulsive responses, which result from the impacts of the defective part(s) with other elements. Most researches carried out have focused on fault location identification. However, limited work has been reported for fault severity estimation, which is critical to make decision for maintenance actions. To improve current diagnostic capability, this paper pays more attention to bearing fault severity diagnosis. It models the vibration sources from bearing defects as an impact process with constant size but three different lengths corresponding to outer race fault, inner race fault and roller fault, respectively. Then an experimental study was followed to evaluate this model. Moreover, the conventional envelope analysis of the measured vibration signals from the tested faulty bearings is optimized by spectral kurtosis (SK) for automatic and reliable fault detection and fault category diagnosis. In the meantime, the diagnostic parameters for fault severity estimation: root mean squared (RMS) values and kurtosis amplitude are developed based on the model results and subsequently evaluated to be agreed vigorously with tested fault cases.

AB - Faults in rolling element bearing are among the main causes of breakdown in rotating machines. Vibration is an effective technique for machine condition monitoring. Vibration signals from a defective bearing with a localized fault contain a series of impulsive responses, which result from the impacts of the defective part(s) with other elements. Most researches carried out have focused on fault location identification. However, limited work has been reported for fault severity estimation, which is critical to make decision for maintenance actions. To improve current diagnostic capability, this paper pays more attention to bearing fault severity diagnosis. It models the vibration sources from bearing defects as an impact process with constant size but three different lengths corresponding to outer race fault, inner race fault and roller fault, respectively. Then an experimental study was followed to evaluate this model. Moreover, the conventional envelope analysis of the measured vibration signals from the tested faulty bearings is optimized by spectral kurtosis (SK) for automatic and reliable fault detection and fault category diagnosis. In the meantime, the diagnostic parameters for fault severity estimation: root mean squared (RMS) values and kurtosis amplitude are developed based on the model results and subsequently evaluated to be agreed vigorously with tested fault cases.

KW - kurtogram

KW - Envelope analysis

KW - Bearing fault diagnosis

KW - elastic deformation

KW - geometry deformation

UR - http://seekdl.org/conferences_page_papers.php?confid=116

M3 - Conference contribution

SP - 20

EP - 24

BT - Proceedings of International Conference on Advances in Civil, Structural and Mechanical Engineering

PB - Institute of Research Engineers and Doctors

ER -

Gu F, Tian X, Chen Z, Wang T, Rehab IAM, Ball A. Fault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis. In Proceedings of International Conference on Advances in Civil, Structural and Mechanical Engineering. Institute of Research Engineers and Doctors. 2014. p. 20-24. 9