Damage detection and monitoring in heritage masonry structures: Systematic review

Abstract

Masonry structures dominate cultural heritage sites worldwide. Public authorities ought to preserve and safeguard such structures for future generations. However, precise evaluation of the current condition of such historical inheritance is crucial to appraise the need for adequate restoration and preservation work. Yet, ambiguity related to the absence of design and construction information and lack of data on the materials used makes this task a daunting challenge. Therefore, there has been considerable research into developing pertinent methodologies and technologies. Evaluating the safety of such heritage masonry structures typically requires in-situ inspections and surveys, sampling and testing, and balancing data from multiple diagnosis activities to select the best strategy for conservation and protection. Despite its operational benefits, this approach is costly, laborious, requires a high degree of professional skill, is unable to unveil hidden defects, and may escalate future maintenance costs. A promising alternative solution is structural health monitoring (SHM) systems. Accordingly, this paper systematically reviews damage detection and SHM techniques for masonry structures. The different measurement methods for SHM are classified into sensor-based and remote sensing methods, while the analyses methods are divided into signal and image processing techniques, artificial intelligence, and numerical techniques. The advantages and disadvantages of the various methods are discussed and compared. The related knowledge gaps are identified, recommendations for best practice are formulated, and the need for future research is identified.