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...
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Online Access: | http://dx.doi.org/10.1051/matecconf/20165906002 |
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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 |
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