Development of a Structural Health Monitoring Tool for Unreinforced Masonry Structures

Developing a condition assessment method for the structural health monitoring (SHM) of unreinforced masonry (URM) structures is an utmost need to identify the remaining service life of the structure, the application of retrofitting techniques, and vulnerability assessment. However, existing methods have focused on a few parameters and not considered the significance and correlation between them. Existing methods for the condition assessment of URM structures use linguistic definitions to classify the degree of distress and lead to ambiguity and human perspective error. The SHM tool developed for this study suggested a numerical framework for evaluating and comparing the structural health of various URM structures. In this study, a new condition assessment method is developed using the fuzzy analytic hierarchy process (FAHP), which incorporates the visual inspections, crack details, structural characteristics, ground characteristics, casual characteristics, and masonry tests. Numerical thresholds were incorporated into this model to mitigate subjectivity. The viewpoints of 100 experts were gathered in matrix form, ensuring that the consistency of their opinions was maintained at less than 10%. Subsequently, FAHP was employed to calculate priority weights among the parameters, forming the basis for the development of rating equations. The developed SHM tool was applied to 12 URM structures including historical buildings, residential buildings, and office buildings in different locations.

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Publication Details

Journal
Journal of Architectural Engineering
Published
2026-02-19
DOI
https://doi.org/10.1061/jaeied.aeeng-1880
Primary Topic
Structural Health Monitoring Techniques
Type
article
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article

Development of a Structural Health Monitoring Tool for Unreinforced Masonry Structures

B. H. J. Pushpakumara, D. M. T. Dissanayake
Journal of Architectural Engineering
Structural Health Monitoring Techniques
article

Development of a Structural Health Monitoring Tool for Unreinforced Masonry Structures

B. H. J. Pushpakumara, D. M. T. Dissanayake
article en

Abstract

Developing a condition assessment method for the structural health monitoring (SHM) of unreinforced masonry (URM) structures is an utmost need to identify the remaining service life of the structure, the application of retrofitting techniques, and vulnerability assessment. However, existing methods have focused on a few parameters and not considered the significance and correlation between them. Existing methods for the condition assessment of URM structures use linguistic definitions to classify the degree of distress and lead to ambiguity and human perspective error. The SHM tool developed for this study suggested a numerical framework for evaluating and comparing the structural health of various URM structures. In this study, a new condition assessment method is developed using the fuzzy analytic hierarchy process (FAHP), which incorporates the visual inspections, crack details, structural characteristics, ground characteristics, casual characteristics, and masonry tests. Numerical thresholds were incorporated into this model to mitigate subjectivity. The viewpoints of 100 experts were gathered in matrix form, ensuring that the consistency of their opinions was maintained at less than 10%. Subsequently, FAHP was employed to calculate priority weights among the parameters, forming the basis for the development of rating equations. The developed SHM tool was applied to 12 URM structures including historical buildings, residential buildings, and office buildings in different locations.

Journal of Architectural EngineeringVol. 32(2)
General Sir John Kotelawala Defence University (LK)
Sustainable cities and communities
Openalex Percentile: Top 51%
Structural Health Monitoring Techniques
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Development of a Structural Health Monitoring Tool for Unreinforced Masonry Structures — B. H. J. Pushpakumara, D. M. T. Dissanayake · Journal of Architectural Engineering (2026) | TGRS Research Map | TGRS