Metaization concept for structural health monitoring

Structural health monitoring (SHM) based on decentralized sensor networks is increasingly drawing research attention. For automated structural health monitoring, interacting (wireless or tethered) sensor nodes, equipped with embedded intelligence, are spatially distributed in civil infrastructure systems. Referred to as “smart structures” or “intelligent infrastructure”, the sensor nodes are capable of autonomously collecting sensor data and, using embedded algorithms, of processing and analyzing sensor data on board in real time. Recent research projects have demonstrated that not only algorithms can be embedded into the sensor nodes; using appropriate decomposition strategies, also models can be embedded into the sensor nodes, such as hybrid, multi-coupled numerical models, which digitally represent the monitored structure in a fully decentralized manner. Thus, it can be expected that next-generation assessment of civil infrastructure is no longer either monitoring-based or model-based. Instead, a new multi-paradigm approach evolves, merging monitoring-based and model-based structural assessment.

To precisely evaluate the quality of the structural assessment, which is not sufficiently possible using current state-of-the-art methods, this research project aims at developing a metaization concept, resulting in a holistic metamodel architecture. The technological nucleus of the metamodel architecture – the metamodel – is a metalinguistic instrument to be used for holistic modeling and digital representation of structural health monitoring systems (Figure 1).  As a result, it is expected that the well-defined formalism provided by the metamodel architecture enables a lifecycle-oriented documentation and a continuous updating of all monitoring-related information. In consequence, the monitoring quality, and thus the quality of structural assessment, can substantially be enhanced. The central question related to the principle of parsimony within SHM, commonly known as “Ockham’s razors”, is to be is to be answered: How complex and resource-consuming must the models be and how simple and resource-efficient can the models be in order to meet the requirements imposed on the quality of structural assessment? To validate the proposed metaization concept, different model classes relevant to typical SHM problems will be considered in a multi-stage validation strategy, using both laboratory tests as well as sensor data taken from civil infrastructure systems in operation.

Figure 1: Metaization principle using hierarchical abstraction layers.

Project type
German Research Foundation (DFG): Research grant
Principal investigator: Prof. Smarsly

2017 - 2020

Project-related publications

  • Theiler, M., Legatiuk, D., Ibanez, S. & Smarsly, K., 2020. Metaization concepts for monitoring-related information. Advanced Engineering Informatics, 46(2020), 1011158.

  • Fitz, T., Theiler, M. & Smarsly, K., 2019. A metamodel for cyber-physical systems. Advanced Engineering Informatics, 41(2019), 100930.

  • Theiler, M. & Smarsly, K., 2018. IFC Monitor – An IFC extension for modeling structural health monitoring systems. Advanced Engineering Informatics, 37(2018), pp. 54-65. 

  • Theiler, M., Dragos, K. & Smarsly, K., 2018. Semantic description of structural health monitoring algorithms using building information modeling. In: Proceedings of the 25th International Workshop on Intelligent Computing in Engineering (EG-ICE). Lausanne, Switzerland, 06/10/2018.

  • Theiler, M. & Smarsly, K., 2018. Parametric Information Modeling of Cyber-Physical Systems based on Industry Foundation Classes. In: Proceedings of the 16th International Conference on Computing in Civil and Building Engineering (ICCCBE). Tampere, Finland, 06/05/2018.

  • Smarsly, K., Theiler, M & Dragos, K., 2017. IFC-based modeling of cyber-physical systems in civil engineering. In: Proceedings of the 24th International Workshop on Intelligent Computing in Engineering (EG-ICE). Nottingham, UK, 07/10/2017.

  • Legatiuk, D., Theiler, M., Dragos, K. & Smarsly, K., 2017. A categorical approach towards metamodeling cyber-physical systems. In: Proceedings of the 11th International Workshop on Structural Health Monitoring (IWSHM). Stanford, CA, USA, 09/12/2017.

  • Theiler, M., Dragos, K. & Smarsly, K., 2017. BIM-based design of structural health monitoring systems. In: Proceedings of the 11th International Workshop on Structural Health Monitoring (IWSHM). Stanford, CA, USA, 09/12/2017.

Professor Dr. Kay Smarsly
Bauhaus University Weimar
Computing in Civil Engineering
Coudraystraße 13 b, Room 004
99423 Weimar
E-Mail: kay.smarsly[at]