| ANALYSES ON STRUCTURAL DAMAGE IDENTIFICATION BASED ON COMBINED PARAMETERS |
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| 作者姓名： | 唐和生 薛松涛 陈镕 王远功 |
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| 作者单位： | Research Institute of Structural Engineering and Disaster Reduction，Tongji University，Research Institute of Structural Engineering and Disaster Reduction，Tongji University，Research Institute of Structural Engineering and Disaster Reduction，Tongji University，Research Institute of Structural Engineering and Disaster Reduction，Tongji University Shanghai 200092，P.R.China，Shanghai 200092，P.R.China，Department of Architecture，School of Science and Engineering，Kinki University，Osaka，Japan，Shanghai 200092，P.R.China，Shanghai 200092，P.R.China |
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| 基金项目： | theNationalNaturalScienceFoundationforDistinguishedYoungScholarof
China ( 5992 582 0 ) |
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| 摘 要： | IntroductionServiceloads,environmentalandaccidentalactionsmaycausedamagetostructures .Whenthestructuraldamageissmalloritisintheinteriorofthestructure,itsdetectioncannotbedonevisually.Inspectionofexistingbuildingsandbridgesaftercatastrophicevents,suchasearthquakesandhurricanes,aswellasundernormaloperatingconditions ,isoftentimeconsumingandcostlybecausecriticalmembersandconnectionsareconcealedundercladdingandotherarchitecturaldecorations.Formanyimportantstructures,suchashospitals,firestations,mi…
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| 关 键 词： | 损伤探测 神经网络 联合参数 揉曲性 高层建筑 |
| 收稿时间： | 6 September 2003 |
Analyses on structural damage identification based on combined parameters |
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| Tang He-sheng,Xue Song-tao,Chen Rong,Wang Yuan-gong.ANALYSES ON STRUCTURAL DAMAGE IDENTIFICATION BASED ON COMBINED PARAMETERS[J].Applied Mathematics and Mechanics(English Edition),2005,26(1):44-51. |
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| Authors: | Tang He-sheng Xue Song-tao Chen Rong Wang Yuan-gong |
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| Institution: | (1) Research Institute of Structural Engineering and Disaster Reduction, Tongji University, 200092 Shanghai, P.R. China;(2) Department of Architecture, School of Science and Engineering, Kinki University, Osaka, Japan |
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| Abstract: | The relative sensitivities of structural dynamical parameters were analyzed using a directive derivation method. The neural network is able to approximate arbitrary non-linear mapping relationship,so it is a powerful damage identification tool for unknown systems.A neural network-based approach was presented for the structural damage detection. The combined parameters were presented as the input vector of the neural network, which computed with the change rates of the several former natural frequencies (C), the change ratios of the frequencies (R), and the assurance criterions of flexibilities (A). Some numerical simulation examples, such as, cantilever and truss with different damage extends and different damage locations were analyzed.The results indicate that the combined parameters are more suitable for the input patterns of neural networks than the other parameters alone. |
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| Keywords: | damage detection neural network combined parameter flexibility |
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