Options
Metaization concepts for monitoring-related information
Publikationstyp
Journal Article
Date Issued
2020-10
Sprache
English
TORE-URI
Journal
Volume
46
Article Number
101158
Citation
Advanced Engineering Informatics 46: 101158 (2020-10)
Publisher DOI
Scopus ID
In recent years, structural health monitoring (SHM) has become a widely used state-of-the-art method for analyzing and assessing the condition of civil infrastructure. SHM systems are characterized by a plethora of heterogeneous system components. For optimizing, documenting, and change tracking of SHM systems, information about SHM systems needs to be formally described on a sound basis. However, with current methods, such as ontologies, description languages or metamodels, only a small subset of information inherent to SHM systems, such as information about sensors, can formally be described. This paper presents a conceptual approach towards identifying and specifying monitoring-related information. Based on a summary review of SHM modeling approaches, metaization concepts to overcome the current limitations are discussed and a robust formalism to describe SHM systems mathematically is proposed. The review methodology is based on a three-pillar concept. First, regulations, standards, and guidelines related to SHM and, second, the current research landscape is examined to identify information required for describing SHM systems, and hierarchies of terms are proposed to categorize the findings. Third, metamodel architectures, such as SHM-related ontologies, BIM-based metamodels and description languages, are reviewed with respect to formally describe SHM systems. Being part of the third pillar, mathematical metamodeling approaches based on category theory, set theory and type theory are presented, capable to describe SHM system as well as approaches suitable to couple metamodels. As an outcome of this study, besides a comprehensive review of the above directions, a strategy towards developing a metaization concept is proposed to provide a robust formalism for SHM system descriptions, aiming to advance optimization, documentation, and change tracking of SHM systems.
Subjects
Building information modeling
Metamodeling
Semantic modeling
Structural health monitoring
Funding(s)