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Integrating multivariate techniques in bridge management systems

Integrating multivariate techniques in bridge management systems The use of bridge management systems (BMS) by infrastructure stakeholders has led to the collection and retention of large quantities of data concerning the condition states of bridges throughout national and regional networks. The database for the BMS is often populated by the results of routine visual inspections, based on a prescribed scale for defining the condition state of the bridge’s individual elements, and of the bridge structure as a whole. The populating of the database also leads to the storage of large quantities of so-called metadata; which can describe the physical parameters of the bridge. The availability of this data allows the assessment of the BMS using multivariate techniques to enhance the life-cycle assessment of bridge networks, through advanced descriptive and predictive techniques applied to deteriorating network assets. Multivariate techniques such as principal component analysis have been demonstrated by the authors to be effectively applied as a descriptive tool to an existing BMS, and the results of a case study of a large dataset of bridges indicate its viability to be integrated into data-based approaches to infrastructural asset management. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Structural Integrity and Maintenance Taylor & Francis

Integrating multivariate techniques in bridge management systems

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Integrating multivariate techniques in bridge management systems

Abstract

The use of bridge management systems (BMS) by infrastructure stakeholders has led to the collection and retention of large quantities of data concerning the condition states of bridges throughout national and regional networks. The database for the BMS is often populated by the results of routine visual inspections, based on a prescribed scale for defining the condition state of the bridge’s individual elements, and of the bridge structure as a whole. The populating of the database also...
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Publisher
Taylor & Francis
Copyright
© 2017 Korea Institute for Structural Maintenance and Inspection
ISSN
2470-5322
eISSN
2470-5314
DOI
10.1080/24705314.2017.1354280
Publisher site
See Article on Publisher Site

Abstract

The use of bridge management systems (BMS) by infrastructure stakeholders has led to the collection and retention of large quantities of data concerning the condition states of bridges throughout national and regional networks. The database for the BMS is often populated by the results of routine visual inspections, based on a prescribed scale for defining the condition state of the bridge’s individual elements, and of the bridge structure as a whole. The populating of the database also leads to the storage of large quantities of so-called metadata; which can describe the physical parameters of the bridge. The availability of this data allows the assessment of the BMS using multivariate techniques to enhance the life-cycle assessment of bridge networks, through advanced descriptive and predictive techniques applied to deteriorating network assets. Multivariate techniques such as principal component analysis have been demonstrated by the authors to be effectively applied as a descriptive tool to an existing BMS, and the results of a case study of a large dataset of bridges indicate its viability to be integrated into data-based approaches to infrastructural asset management.

Journal

Journal of Structural Integrity and Maintenance – Taylor & Francis

Published: Jul 3, 2017

Keywords: Bridge management systems; Principal component analysis; multivariate analysis; condition ratings

References

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