A Novel Damage Detection Algorithm using Time-Series Analysis-Based Blind Source Separation
In this paper, a novel damage detection algorithm is developed based on blind source separation in conjunction with time-series analysis. Blind source separation (BSS), is a powerful signal processing tool that is used to identify the modal responses and mode shapes of a vibrating structure using on...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.3233/SAV-120759 |
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| _version_ | 1832549522630246400 |
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| author | A. Sadhu B. Hazra |
| author_facet | A. Sadhu B. Hazra |
| author_sort | A. Sadhu |
| collection | DOAJ |
| description | In this paper, a novel damage detection algorithm is developed based on blind source separation in conjunction with time-series analysis. Blind source separation (BSS), is a powerful signal processing tool that is used to identify the modal responses and mode shapes of a vibrating structure using only the knowledge of responses. In the proposed method, BSS is first employed to estimate the modal response using the vibration measurements. Time-series analysis is then performed to characterize the mono-component modal responses and successively the resulting time-series models are utilized for one-step ahead prediction of the modal response. With the occurrence of newer measurements containing the signature of damaged system, a variance-based damage index is used to identify the damage instant. Once the damage instant is identified, the damaged and undamaged modal parameters of the system are estimated in an adaptive fashion. The proposed method solves classical damage detection issues including the identification of damage instant, location as well as the severity of damage. The proposed damage detection algorithm is verified using extensive numerical simulations followed by the full scale study of UCLA Factor building using the measured responses under Parkfield earthquake. |
| format | Article |
| id | doaj-art-7220af313f964152ba3e2783e69b2c46 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-7220af313f964152ba3e2783e69b2c462025-02-03T06:11:07ZengWileyShock and Vibration1070-96221875-92032013-01-0120342343810.3233/SAV-120759A Novel Damage Detection Algorithm using Time-Series Analysis-Based Blind Source SeparationA. Sadhu0B. Hazra1Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON, CanadaDepartment of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON, CanadaIn this paper, a novel damage detection algorithm is developed based on blind source separation in conjunction with time-series analysis. Blind source separation (BSS), is a powerful signal processing tool that is used to identify the modal responses and mode shapes of a vibrating structure using only the knowledge of responses. In the proposed method, BSS is first employed to estimate the modal response using the vibration measurements. Time-series analysis is then performed to characterize the mono-component modal responses and successively the resulting time-series models are utilized for one-step ahead prediction of the modal response. With the occurrence of newer measurements containing the signature of damaged system, a variance-based damage index is used to identify the damage instant. Once the damage instant is identified, the damaged and undamaged modal parameters of the system are estimated in an adaptive fashion. The proposed method solves classical damage detection issues including the identification of damage instant, location as well as the severity of damage. The proposed damage detection algorithm is verified using extensive numerical simulations followed by the full scale study of UCLA Factor building using the measured responses under Parkfield earthquake.http://dx.doi.org/10.3233/SAV-120759 |
| spellingShingle | A. Sadhu B. Hazra A Novel Damage Detection Algorithm using Time-Series Analysis-Based Blind Source Separation Shock and Vibration |
| title | A Novel Damage Detection Algorithm using Time-Series Analysis-Based Blind Source Separation |
| title_full | A Novel Damage Detection Algorithm using Time-Series Analysis-Based Blind Source Separation |
| title_fullStr | A Novel Damage Detection Algorithm using Time-Series Analysis-Based Blind Source Separation |
| title_full_unstemmed | A Novel Damage Detection Algorithm using Time-Series Analysis-Based Blind Source Separation |
| title_short | A Novel Damage Detection Algorithm using Time-Series Analysis-Based Blind Source Separation |
| title_sort | novel damage detection algorithm using time series analysis based blind source separation |
| url | http://dx.doi.org/10.3233/SAV-120759 |
| work_keys_str_mv | AT asadhu anoveldamagedetectionalgorithmusingtimeseriesanalysisbasedblindsourceseparation AT bhazra anoveldamagedetectionalgorithmusingtimeseriesanalysisbasedblindsourceseparation AT asadhu noveldamagedetectionalgorithmusingtimeseriesanalysisbasedblindsourceseparation AT bhazra noveldamagedetectionalgorithmusingtimeseriesanalysisbasedblindsourceseparation |