Vibration based fault detection and identification in an aircraft skeleton structure via a stochastic functional model based method
The problem of vibration based fault detection, identification (localization) and estimation in a scale aircraft skeleton structure is considered via a stochastic functional model based method (FMBM). The method is based on the novel class of stochastic Functionally Pooled models, which are capable...
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| Published in | Mechanical systems and signal processing Vol. 22; no. 3; pp. 557 - 573 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
London
Elsevier Ltd
01.04.2008
Elsevier |
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| Abstract | The problem of vibration based fault detection, identification (localization) and estimation in a scale aircraft skeleton structure is considered via a stochastic functional model based method (FMBM). The method is based on the novel class of stochastic Functionally Pooled models, which are capable of accurately representing the structure in a faulty state for the state's continuum of fault magnitudes, as well as interval estimation and formal statistical hypothesis testing procedures. The faults considered consist of small masses attached to the structure. The method is capable of operating even on single-excitation single-response signals, and is shown to achieve effective fault detection and identification, as well as remarkable accuracy in estimating the exact fault magnitude. This is so even for “unmodelled” faults, or faults monitored by remote sensors. |
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| AbstractList | The problem of vibration based fault detection, identification (localization) and estimation in a scale aircraft skeleton structure is considered via a stochastic functional model based method (FMBM). The method is based on the novel class of stochastic Functionally Pooled models, which are capable of accurately representing the structure in a faulty state for the state's continuum of fault magnitudes, as well as interval estimation and formal statistical hypothesis testing procedures. The faults considered consist of small masses attached to the structure. The method is capable of operating even on single-excitation single-response signals, and is shown to achieve effective fault detection and identification, as well as remarkable accuracy in estimating the exact fault magnitude. This is so even for 'unmodelled' faults, or faults monitored by remote sensors. |
| Author | Sakellariou, J.S. Fassois, S.D. |
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| Keywords | Fault estimation Fault detection Fault identification (localization) Statistical methods Vibration based methods Aircraft skeleton structure Functionally pooled models Vibration Probabilistic approach Statistical estimation Stochastic method Telemetry Modeling Remote sensing Statistical method Statistical test Added mass Signal processing Skeleton Localization Aircraft Defect detection Non contact measurement |
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| SubjectTerms | Aircraft skeleton structure Exact sciences and technology Fault detection Fault estimation Fault identification (localization) Functionally pooled models Fundamental areas of phenomenology (including applications) Measurement and testing methods Physics Solid mechanics Statistical methods Structural and continuum mechanics Vibration based methods Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...) |
| Title | Vibration based fault detection and identification in an aircraft skeleton structure via a stochastic functional model based method |
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