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Damage Detection for Structural Health Monitoring of Bridges as a Knowledge Discovery in Databases Process

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Data Mining in Structural Dynamic Analysis

Abstract

The structural health monitoring (SHM) field is concerned with the increasing demand for improved and more continuous condition assessment of engineering infrastructures to better face the challenges presented by modern societies. Thus, the applicability of computer science techniques for SHM applications has attracted the attention of researchers and practitioners in the last few years, especially to detect damage in structures under operational and environmental conditions. In the SHM for bridges, the damage detection can be seen as the end of a process to extract knowledge regarding the structural state condition from vibration response measurements. In that sense, the damage detection has some similarities with the Knowledge Discovery in Databases (KDD) process. Therefore, this chapter intends to pose damage detection in bridges in the context of the KDD process, where data transformation and data mining play major roles. The applicability of the KDD for damage detection is evaluated on the well-known monitoring data sets from the Z-24 Bridge, where several damage scenarios were carried out under severe operational and environmental effects.

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Author information

Authors and Affiliations

  1. Applied Electromagnetism Laboratory, Universidade Federal do Pará, R. Augusto Corrêa, Guamá 01, Belém, Pará, 66075-110, Brazil

    Moisés Silva

  2. Faculty of Computing and Electrical Engineering, Universidade Federal do Sul e Sudeste do Pará, F. 17, Q. 4, L. E., Marabá, Pará, 68505-080, Brazil

    Adam Santos

  3. Faculty of Engineering, Universidade Lusófona de Humanidades e Tecnologias, Campo Grande 376, 1749-024, Lisbon, Portugal

    Elói Figueiredo

  4. CONSTRUCT—Institute of R&D in Structures and Construction, R. Dr. Roberto Frias s/n, 4200-465, Porto, Portugal

    Elói Figueiredo

Authors
  1. Moisés Silva
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  2. Adam Santos
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  3. Elói Figueiredo
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Corresponding author

Correspondence to Elói Figueiredo .

Editor information

Editors and Affiliations

  1. Department of Civil and Environmental Engineering, National University of Singapore, Singapore, Singapore

    Yun Lai Zhou

  2. Faculty of Engineering and Architecture, Ghent University, Laboratory Soete, Ghent, Belgium

    Magd Abdel Wahab

  3. Department of Mechanical Engineering, Technical University Of Lisbon, Lisbon, Portugal

    Nuno M. M. Maia

  4. Engineering Research Center of Railway Environment Vibration and Noise, Ministry of Education, East China Jiaotong University, Nanchang, China

    Linya Liu

  5. Faculty of Engineering, Lusófona University, Lisbon, Portugal

    Elói Figueiredo

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Silva, M., Santos, A., Figueiredo, E. (2019). Damage Detection for Structural Health Monitoring of Bridges as a Knowledge Discovery in Databases Process. In: Zhou, Y., Wahab, M., Maia, N., Liu, L., Figueiredo, E. (eds) Data Mining in Structural Dynamic Analysis. Springer, Singapore. https://doi.org/10.1007/978-981-15-0501-0_1

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  • DOI: https://doi.org/10.1007/978-981-15-0501-0_1

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