The fault detection and severity diagnosis of rolling element bearings using modulation signal bispectrum

Ibrahim Rehab, Xiange Tian, Fengshou Gu, Andrew Ball

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

5 Citations (Scopus)

Abstract

The rolling element bearing is a key part in many mechanical equipment. The accurate and timely diagnosis of its faults is critical for predictive maintenance. 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 and inevitable noise. 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 presents a new approach to detection and diagnosis of bearing fault severity based on vibration analysis using modulation signal bispectrum (MSB). 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. The results shows that MSB has a better and reliable performance in extract small changes from the faulty bearing for accurate fault detection and diagnosis for different bearing fault severity.

Original languageEnglish
Title of host publication11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014
PublisherBritish Institute of Non-Destructive Testing
Publication statusPublished - 2014
Event11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies - Manchester, United Kingdom
Duration: 10 Jun 201412 Jun 2014
Conference number: 11

Conference

Conference11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies
Abbreviated titleCM / MFPT 2014
CountryUnited Kingdom
CityManchester
Period10/06/1412/06/14

Fingerprint

Bearings (structural)
Fault detection
Modulation
Electric fault location
Vibration analysis
Failure analysis
Defects

Cite this

Rehab, I., Tian, X., Gu, F., & Ball, A. (2014). The fault detection and severity diagnosis of rolling element bearings using modulation signal bispectrum. In 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014 British Institute of Non-Destructive Testing.
Rehab, Ibrahim ; Tian, Xiange ; Gu, Fengshou ; Ball, Andrew. / The fault detection and severity diagnosis of rolling element bearings using modulation signal bispectrum. 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014. British Institute of Non-Destructive Testing, 2014.
@inproceedings{079d42d6ed854cceafb294b714358dbd,
title = "The fault detection and severity diagnosis of rolling element bearings using modulation signal bispectrum",
abstract = "The rolling element bearing is a key part in many mechanical equipment. The accurate and timely diagnosis of its faults is critical for predictive maintenance. 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 and inevitable noise. 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 presents a new approach to detection and diagnosis of bearing fault severity based on vibration analysis using modulation signal bispectrum (MSB). 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. The results shows that MSB has a better and reliable performance in extract small changes from the faulty bearing for accurate fault detection and diagnosis for different bearing fault severity.",
author = "Ibrahim Rehab and Xiange Tian and Fengshou Gu and Andrew Ball",
year = "2014",
language = "English",
booktitle = "11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014",
publisher = "British Institute of Non-Destructive Testing",

}

Rehab, I, Tian, X, Gu, F & Ball, A 2014, The fault detection and severity diagnosis of rolling element bearings using modulation signal bispectrum. in 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014. British Institute of Non-Destructive Testing, 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, United Kingdom, 10/06/14.

The fault detection and severity diagnosis of rolling element bearings using modulation signal bispectrum. / Rehab, Ibrahim; Tian, Xiange; Gu, Fengshou; Ball, Andrew.

11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014. British Institute of Non-Destructive Testing, 2014.

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

TY - GEN

T1 - The fault detection and severity diagnosis of rolling element bearings using modulation signal bispectrum

AU - Rehab, Ibrahim

AU - Tian, Xiange

AU - Gu, Fengshou

AU - Ball, Andrew

PY - 2014

Y1 - 2014

N2 - The rolling element bearing is a key part in many mechanical equipment. The accurate and timely diagnosis of its faults is critical for predictive maintenance. 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 and inevitable noise. 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 presents a new approach to detection and diagnosis of bearing fault severity based on vibration analysis using modulation signal bispectrum (MSB). 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. The results shows that MSB has a better and reliable performance in extract small changes from the faulty bearing for accurate fault detection and diagnosis for different bearing fault severity.

AB - The rolling element bearing is a key part in many mechanical equipment. The accurate and timely diagnosis of its faults is critical for predictive maintenance. 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 and inevitable noise. 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 presents a new approach to detection and diagnosis of bearing fault severity based on vibration analysis using modulation signal bispectrum (MSB). 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. The results shows that MSB has a better and reliable performance in extract small changes from the faulty bearing for accurate fault detection and diagnosis for different bearing fault severity.

UR - http://www.scopus.com/inward/record.url?scp=84918588970&partnerID=8YFLogxK

M3 - Conference contribution

BT - 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014

PB - British Institute of Non-Destructive Testing

ER -

Rehab I, Tian X, Gu F, Ball A. The fault detection and severity diagnosis of rolling element bearings using modulation signal bispectrum. In 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014. British Institute of Non-Destructive Testing. 2014