Stiffness Separation Method for Damage Identification of Steel Truss Bridge: Exploring Diverse Separation Interfaces

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Publicado en:Structural Control and Health Monitoring (Online) vol. 2025, no. 1 (2025)
Autor principal: Xiao, Feng
Otros Autores: Tian, Geng, Mao, Yuxue, Xiang, Yujiang
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John Wiley & Sons, Inc.
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024 7 |a 10.1155/stc/1827097  |2 doi 
035 |a 3271171039 
045 2 |b d20250101  |b d20251231 
084 |a 239329  |2 nlm 
100 1 |a Xiao, Feng  |u School of Safety Science and Engineering, , Nanjing University of Science and Technology, , Nanjing, , , Jiangsu, China, <url href="http://njust.edu.cn">njust.edu.cn</url> 
245 1 |a Stiffness Separation Method for Damage Identification of Steel Truss Bridge: Exploring Diverse Separation Interfaces 
260 |b John Wiley & Sons, Inc.  |c 2025 
513 |a Journal Article 
520 3 |a Effective identification and quantification of bridge damage are critical for ensuring infrastructure safety and longevity. This study introduces a damage identification approach for steel truss bridges based on the stiffness separation method. This method simplifies large‐scale problems by partitioning structures into substructures through separation interfaces. To enhance interface adaptability, the method conducts distinct analyses of nodes and members and a combined analysis involving both. A case study of the New Yellow River Bridge validated the effectiveness of the proposed method. Furthermore, a comparative analysis of the Nelder–Mead (NM) simplex and Interior Point (IP) methods was performed across various damage and separation scenarios. The findings confirm the accuracy and efficiency of the proposed method for damage detection, highlighting its importance for maintaining the safety of large bridge structures. 
653 |a Steel bridges 
653 |a Comparative analysis 
653 |a Truss bridges 
653 |a Bridge maintenance 
653 |a Identification 
653 |a Stiffness 
653 |a Separation 
653 |a Sensors 
653 |a Effectiveness 
653 |a Damage detection 
653 |a Localization 
653 |a Data compression 
653 |a Interfaces 
653 |a Parameter estimation 
653 |a Steel structures 
653 |a Environmental 
700 1 |a Tian, Geng  |u School of Safety Science and Engineering, , Nanjing University of Science and Technology, , Nanjing, , , Jiangsu, China, <url href="http://njust.edu.cn">njust.edu.cn</url> 
700 1 |a Mao, Yuxue  |u School of Safety Science and Engineering, , Nanjing University of Science and Technology, , Nanjing, , , Jiangsu, China, <url href="http://njust.edu.cn">njust.edu.cn</url> 
700 1 |a Xiang, Yujiang  |u Mechanical and Aerospace Engineering, , Oklahoma State University, , Stillwater, , , Oklahoma, USA, <url href="http://okstate.edu">okstate.edu</url> 
773 0 |t Structural Control and Health Monitoring (Online)  |g vol. 2025, no. 1 (2025) 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3271171039/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3271171039/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3271171039/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch