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| Title: | A soft post-earthquake damage identification methodology using vibration time series |
| Author (s): | Xu, Bin Wu, Zhishen Yokoyama, Koichi Harada, Takao Chen, Genda |
| Department/Lab Affiliations: | Center for Infrastructure Engineering Studies Civil, Architectural & Environmental Engineering Natural Hazard Mitigation Institute (NHMI) University Transportation Center |
| Keywords: | emulator neural network (ENN) multi-storey shear building parametric evaluation neural network (PENN) root mean square structural state space equation |
| Subject Terms: | Neural circuitry. Neural networks (Computer science) Parametric devices. Smart structures. Structural dynamics. Vibration. |
| Issue Date: | 2005-06 |
| Publisher: | Institute of Physics |
| Citation: | Xu, Bin., Wu, Zhishen., Yokoyama, Koichi., Harada, Takao., and Chen, Genda. "A Soft Post-Earthquake Damage Identification Methodology Using Vibration Time Series", Smart Materials and Structures, vol. 14, no. 3, 2005. |
| Abstract: | A neural-network-based post-earthquake damage identification methodology for smart structures with the direct use of vibration measurements is developed. Two neural networks are constructed to facilitate the process of post-earthquake damage identification. The rationality of the proposed methodology is explained and the theory basis for the construction of an emulator neural network (ENN) and a parametric evaluation neural network (PENN) are described according to the discrete time solution of the structural state space equation. An evaluation index called the root mean square of the prediction difference vector (RMSPDV) is presented to evaluate the condition of different associated structures. Based on the trained ENN, which is a non-parametric model of the object structure in a healthy state, and the PENN that describes the relation between structural parameters and the components of the corresponding RMSPDVs, the inter-storey stiffness of the damaged object structure is identified. The accuracy, sensibility and efficacy of the proposed strategy for different ground excitations are also examined using a multi-storey shear building structure by numerical simulations. Since the methodology does not require the extraction of structural dynamic characteristics such as frequencies and mode shapes from measurements, it has the potential of being a practical tool for health monitoring of smart engineering structures. |
| Type: | Article - Journal text |
| In Title: | Smart Materials and Structures |
| Copyright Notice: | Pre-print: author can archive; Post-print: author can archive; This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. FULL COPYRIGHT INFORMATION: |
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| title | A soft post-earthquake damage identification methodology using vibration time series |
| contributor.author | Xu, Bin |
| contributor.author | Wu, Zhishen |
| contributor.author | Yokoyama, Koichi |
| contributor.author | Harada, Takao |
| contributor.author | Chen, Genda |
| contributor.deptlab | Center for Infrastructure Engineering Studies |
| contributor.deptlab | Civil, Architectural & Environmental Engineering |
| contributor.deptlab | Natural Hazard Mitigation Institute (NHMI) |
| contributor.deptlab | University Transportation Center |
| subject | emulator neural network (ENN) |
| subject | multi-storey shear building |
| subject | parametric evaluation neural network (PENN) |
| subject | root mean square |
| subject | structural state space equation |
| subject.LCSH | Neural circuitry. |
| subject.LCSH | Neural networks (Computer science) |
| subject.LCSH | Parametric devices. |
| subject.LCSH | Smart structures. |
| subject.LCSH | Structural dynamics. |
| subject.LCSH | Vibration. |
| date.issued | 2005-06 |
| publisher | Institute of Physics |
| identifier.citation | Xu, Bin., Wu, Zhishen., Yokoyama, Koichi., Harada, Takao., and Chen, Genda. "A Soft Post-Earthquake Damage Identification Methodology Using Vibration Time Series", Smart Materials and Structures, vol. 14, no. 3, 2005. |
| identifier.pub.URI | |
| description.abstract | A neural-network-based post-earthquake damage identification methodology for smart structures with the direct use of vibration measurements is developed. Two neural networks are constructed to facilitate the process of post-earthquake damage identification. The rationality of the proposed methodology is explained and the theory basis for the construction of an emulator neural network (ENN) and a parametric evaluation neural network (PENN) are described according to the discrete time solution of the structural state space equation. An evaluation index called the root mean square of the prediction difference vector (RMSPDV) is presented to evaluate the condition of different associated structures. Based on the trained ENN, which is a non-parametric model of the object structure in a healthy state, and the PENN that describes the relation between structural parameters and the components of the corresponding RMSPDVs, the inter-storey stiffness of the damaged object structure is identified. The accuracy, sensibility and efficacy of the proposed strategy for different ground excitations are also examined using a multi-storey shear building structure by numerical simulations. Since the methodology does not require the extraction of structural dynamic characteristics such as frequencies and mode shapes from measurements, it has the potential of being a practical tool for health monitoring of smart engineering structures. |
| type | Article - Journal |
| type.DCMIType | text |
| rights | Pre-print: author can archive; Post-print: author can archive; |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. |
| rights.URI | |
| relation.isPartOf | Smart Materials and Structures |
| date.available | 2008-06-17T21:12:45Z |
| identifier.persist.URI |