Cross Correlation for Condition Monitoring of Variable Load and Speed Gearboxes
The ability to identify incipient faults at an early stage in the operation of machinery has been demonstrated to provide substantial value to industry. These benefits for automated, in situ, and online monitoring of machinery, structures, and systems subject to varying operating conditions are diff...
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Published in | Journal of Industrial Mathematics Vol. 2014; pp. 1 - 10 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Hindawi Publishing Corporation
22.12.2014
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Online Access | Get full text |
ISSN | 2314-8853 2314-6117 |
DOI | 10.1155/2014/543056 |
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Abstract | The ability to identify incipient faults at an early stage in the operation of machinery has been demonstrated to provide substantial value to industry. These benefits for automated, in situ, and online monitoring of machinery, structures, and systems subject to varying operating conditions are difficult to achieve at present when they are run in operationally constrained environments that demand uninterrupted operation in this mode. This work focuses on developing a simple algorithm for this problem class; novelty detection is deployed on feature vectors generated from the cross correlation of vibration signals from sensors mounted on disparate locations in a power train. The behavior of these signals in a gearbox subject to varying load and speed is expected to remain in a commensurate state until a change in some physical aspect of the mechanical components, presumed to be indicative of gearbox failure. Cross correlation will be demonstrated to generate excellent classification results for a gearbox subject to independently changing load and speed. It eliminates the need to analyze the highly complex dynamics of this system; it generalizes well across untaught ranges of load and speed; it eliminates the need to identify and measure all predominant time-varying parameters; it is simple and computationally inexpensive. |
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AbstractList | The ability to identify incipient faults at an early stage in the operation of machinery has been demonstrated to provide substantial value to industry. These benefits for automated, in situ, and online monitoring of machinery, structures, and systems subject to varying operating conditions are difficult to achieve at present when they are run in operationally constrained environments that demand uninterrupted operation in this mode. This work focuses on developing a simple algorithm for this problem class; novelty detection is deployed on feature vectors generated from the cross correlation of vibration signals from sensors mounted on disparate locations in a power train. The behavior of these signals in a gearbox subject to varying load and speed is expected to remain in a commensurate state until a change in some physical aspect of the mechanical components, presumed to be indicative of gearbox failure. Cross correlation will be demonstrated to generate excellent classification results for a gearbox subject to independently changing load and speed. It eliminates the need to analyze the highly complex dynamics of this system; it generalizes well across untaught ranges of load and speed; it eliminates the need to identify and measure all predominant time-varying parameters; it is simple and computationally inexpensive. |
Author | Timusk, Markus McBain, Jordan |
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Cites_doi | 10.1017/cbo9780511618888 10.1006/jsvi.2002.5148 10.1006/jsvi.1998.2161 10.1109/tdei.2011.5739458 10.1016/j.jsv.2004.05.015 10.1016/s0167-8655(99)00087-2 10.1016/s0149-1970(03)00036-2 10.1784/204764212804729723 10.1016/j.sigpro.2003.07.019 10.1016/j.ymssp.2010.03.015 10.1016/j.buildenv.2011.01.017 10.1016/j.ymssp.2008.01.013 10.1080/00207179608921851 10.2514/3.24026 10.1016/j.sigpro.2003.07.018 10.1145/380995.380999 10.1016/j.jsv.2007.08.023 10.1016/j.asoc.2004.11.002 10.1016/j.jsv.2009.07.025 |
ContentType | Journal Article |
Copyright | Copyright © 2014 Jordan McBain and Markus Timusk. |
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An integrated flexible platform for development of fault detection systems and duty cycle simulation Proceedings of the 23rd International Congress on Condition Monitoring and Diagnostic Engineering Management (COMADEM '10) July 2010 373 376 2-s2.0-77956330222 – volume: 2 start-page: 32 issue: 2 year: 2012 end-page: 39 ident: 26 article-title: System identification for fault detection in variable speed and load machinery – volume: 5 start-page: 29 issue: 2 year: 2002 end-page: 40 ident: 30 article-title: Fault detection and diagnosis in variable speed machines – volume: 223 start-page: 529 issue: 4 year: 1999 end-page: 541 ident: 10 article-title: The application of correlation dimension in gearbox condition monitoring – volume: 24 start-page: 2972 issue: 8 year: 2010 end-page: 2984 ident: 5 article-title: Fault detection in non-Gaussian vibration systems using dynamic statistical-based approaches – volume: 311 start-page: 109 issue: 1-2 year: 2008 end-page: 132 ident: 18 article-title: Vibration and current transient monitoring for gearbox fault detection using multiresolution Fourier transform – reference: Timusk M. 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Snippet | The ability to identify incipient faults at an early stage in the operation of machinery has been demonstrated to provide substantial value to industry. These... |
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Title | Cross Correlation for Condition Monitoring of Variable Load and Speed Gearboxes |
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