Bevel Gearbox Fault Diagnosis using Vibration Measurements

The use of vibration measurementanalysis has been proven to be effective for gearbox fault diagnosis. However, the complexity of vibration signals observed from a gearbox makes it difficult to accurately detectfaults in the gearbox. This work is based on a comparative studyof several time-frequency...

Full description

Bibliographic Details
Main Authors: Hartono Dennis, Halim Dunant, Widodo Achmad, Roberts GethinWyn
Format: Article
Language:English
Published: EDP Sciences 2016-01-01
Series:MATEC Web of Conferences
Online Access:http://dx.doi.org/10.1051/matecconf/20165906002
id doaj-59ba3e0de2074168a337113ca993f9d4
record_format Article
spelling doaj-59ba3e0de2074168a337113ca993f9d42021-02-02T01:03:25ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01590600210.1051/matecconf/20165906002matecconf_icfst2016_06002Bevel Gearbox Fault Diagnosis using Vibration MeasurementsHartono Dennis0Halim Dunant1Widodo Achmad2Roberts GethinWyn3Department of Mechanical, Materials and Manufacturing Engineering, The University of Nottingham Ningbo ChinaDepartment of Mechanical, Materials and Manufacturing Engineering, The University of Nottingham Ningbo ChinaDepartment of Mechanical Engineering, Diponegoro UniversityDepartment of Civil Engineering,The University of Nottingham Ningbo ChinaThe use of vibration measurementanalysis has been proven to be effective for gearbox fault diagnosis. However, the complexity of vibration signals observed from a gearbox makes it difficult to accurately detectfaults in the gearbox. This work is based on a comparative studyof several time-frequency signal processing methods that can be used to extract information from transient vibration signals containing useful diagnostic information. Experiments were performed on a bevel gearbox test rig using vibration measurements obtained from accelerometers. Initially, thediscrete wavelet transform was implementedfor vibration signal analysis to extract the frequency content of signal from the relevant frequency region. Several time-frequency signal processing methods werethen incorporated to extract the fault features of vibration signals and their diagnostic performances were compared. It was shown thatthe Short Time Fourier Transform (STFT) could not offer a good time resolution to detect the periodicity of the faulty gear tooth due the difficulty in choosing an appropriate window length to capture the impulse signal. The Continuous Wavelet Transform (CWT), on the other hand, was suitable to detection of vibration transients generated by localized fault from a gearbox due to its multi-scale property. However, both methods still require a thorough visual inspection. In contrast, it was shown from the experiments that the diagnostic method using the Cepstrumanalysis could provide a direct indication of the faulty tooth without the need of a thorough visual inspection as required by CWT and STFT.http://dx.doi.org/10.1051/matecconf/20165906002
collection DOAJ
language English
format Article
sources DOAJ
author Hartono Dennis
Halim Dunant
Widodo Achmad
Roberts GethinWyn
spellingShingle Hartono Dennis
Halim Dunant
Widodo Achmad
Roberts GethinWyn
Bevel Gearbox Fault Diagnosis using Vibration Measurements
MATEC Web of Conferences
author_facet Hartono Dennis
Halim Dunant
Widodo Achmad
Roberts GethinWyn
author_sort Hartono Dennis
title Bevel Gearbox Fault Diagnosis using Vibration Measurements
title_short Bevel Gearbox Fault Diagnosis using Vibration Measurements
title_full Bevel Gearbox Fault Diagnosis using Vibration Measurements
title_fullStr Bevel Gearbox Fault Diagnosis using Vibration Measurements
title_full_unstemmed Bevel Gearbox Fault Diagnosis using Vibration Measurements
title_sort bevel gearbox fault diagnosis using vibration measurements
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2016-01-01
description The use of vibration measurementanalysis has been proven to be effective for gearbox fault diagnosis. However, the complexity of vibration signals observed from a gearbox makes it difficult to accurately detectfaults in the gearbox. This work is based on a comparative studyof several time-frequency signal processing methods that can be used to extract information from transient vibration signals containing useful diagnostic information. Experiments were performed on a bevel gearbox test rig using vibration measurements obtained from accelerometers. Initially, thediscrete wavelet transform was implementedfor vibration signal analysis to extract the frequency content of signal from the relevant frequency region. Several time-frequency signal processing methods werethen incorporated to extract the fault features of vibration signals and their diagnostic performances were compared. It was shown thatthe Short Time Fourier Transform (STFT) could not offer a good time resolution to detect the periodicity of the faulty gear tooth due the difficulty in choosing an appropriate window length to capture the impulse signal. The Continuous Wavelet Transform (CWT), on the other hand, was suitable to detection of vibration transients generated by localized fault from a gearbox due to its multi-scale property. However, both methods still require a thorough visual inspection. In contrast, it was shown from the experiments that the diagnostic method using the Cepstrumanalysis could provide a direct indication of the faulty tooth without the need of a thorough visual inspection as required by CWT and STFT.
url http://dx.doi.org/10.1051/matecconf/20165906002
work_keys_str_mv AT hartonodennis bevelgearboxfaultdiagnosisusingvibrationmeasurements
AT halimdunant bevelgearboxfaultdiagnosisusingvibrationmeasurements
AT widodoachmad bevelgearboxfaultdiagnosisusingvibrationmeasurements
AT robertsgethinwyn bevelgearboxfaultdiagnosisusingvibrationmeasurements
_version_ 1724312387256844288