The digital transformation is bringing about far-reaching changes in all areas of society. In the fusion of BIM, the optimized planning, execution and management of facilities, buildings and infrastructure, with structural health monitoring (SHM), a digital twin acts as a central element of efficient data organization.

The objective of this project is a method that realizes automated data-driven modelling based on the H2/H-infinity standard and methods of system identification coupled with machine learning. This enables a condition analysis as a digital twin over the service life of the real twin, the building, which is incorporated into an SHM/BIM concept. Based on process-oriented cooperative systems, special physically interpretable indicators are able to automatically display and localize structural changes.

The numerical method works with stochastic multi-correlated output-only measurement data with special consideration and classification of environmental and operating conditions. The automatically generated parameterized stochastic process models of the system and filter theory enable a prediction of future damage states of the investigated structure. This provides the building owner with a set of tools for the predictive planning of maintenance measures on structures with high economic benefits.

Highlights and Milestones of ADMO (DFG-SPP100+ C03/E03) from 2022 to 2025

Automatic data-driven modeling and H2/H-infinity -norm-based dimension reduction of process-oriented and cooperative systems for SHM condition analysis with methods of system identification and machine learning on exposed structures

Theory of methods

• 2022-2024 Development, verification and publication of Autonomous Model Order Selection (AMOS) [2] [3_Conf]
• 2022-2024 Normalization to ideal input covariance and state space normalization leads to a positive definite system identification with the method State Projection Estimation Error (SP2E) [5]
• 2024-2025 Combination of AMOS and SP2E enables continuous monitoring for damage localization [3] [4] [7_Conf]
• 2024-2025 Localization of damage through influence lines based on inclinometers

Verification of the methods with real experiments of multi-correlated processes

• 2022-2023 Laboratory measurements: Stiffness and mass changes can be clearly localized [1] [2_Conf] [5_Conf] [7_Conf]
• 2023-2024 Field measurements: Mass changes can be clearly loclaized even under Environmental and Operational Conditions (EOC) [1] [5] [2_Conf] [5_Conf]
• 2022-2024 Large-scale experiment Flossgraben Bridge under operation: Mass changes can be clearly localized [6] [1_Conf] [4_Conf] [5_Conf] [6_Conf]
• 2024-2025 Laboratory measurements using inclinometers enable loclization of stiffness changes
• 2025 Measurements at IDA-KI Bridge [4]

Zugehörige Publikationen

Peer-Reviewed Journal Paper

[1] Rohrer, M., Moeller, M., & Lenzen, A. (2024). A Testing Field for Studies of Environmental and Operational Effects in Structural Damage Localization of Mechanical Structures. Structural Control and Health Monitoring Wiley, 2024(1), 3970794. DOI: https://doi.org/10.1155/2024/3970794

[2] Moeller, Max, and Armin Lenzen. "Autonomous Energy-Based Model Order Selection in Parameter State Space Identification Via Cross Gramian and Symmetrizer."; Mechanical Systems and Signal Processing 228(2025): 112452; DOI: 10.1016/j.ymssp.2025.112452

[3] Becks et. al. (2024). Neuartige Konzepte für die Zustandsüberwachung und -analyse von Brückenbauwerken – Einblicke in das Forschungsvorhaben SPP100+. Bauingenieur, BD. 99 (2024) Nr. 10. DOI: https://doi.org/10.37544/0005-6650-2024-10-63

[4] Rohrer et. al. (2025). Experimental Studies on Multi-Scale Data-Driven Methods within the Framework of Structural Health Monitoring.Civil Engineering Design Wiley. DOI: https://doi.org/10.1002/cend.202400036

[5] Rohrer, Maximilian, and Lenzen, Armin. “An Experimental Validation of Damage Localization with SP2E under the Influence of EOC”Mechanical Systems and Signal Processing. Submitted January 2025, under review.

[6] Lenzen, Armin et. al. “Experimental fault localization at the seven span Flossgraben Bridge under operation by output-only system parameter identification based on subspaces and H-infinity-optimization” Structural Control and Health Monitoring. Submitted March 2025, under review.

Konferenzen und andere Veröffentlichungen

[1_Conf] A. Lenzen, M. Moeller and M. Rohrer, „Monitoring an der Floßgrabenbrücke in Zeitz-Experimente zur Systemidentifikation,“ in Berichte der Fachtagung "Baustatik - Baupraxis 15", 04. und 05. März 2024, Hamburg, 2024. (peer reviewed) ISBN: 978-3-00-077808-7. S. 491-498

[2_Conf] Maximilian Rohrer, Max Moeller, Armin Lenzen:  “Experimental vibration-based output-only damage localization of mechanical systems.” EWSHM 2024, 11th European Workshop on Structural Health Monitoring, Potsdam, Germany, June 10-13, 2024. DOI: https://doi.org/10.58286/29613

[3_Conf] Max Moeller, Maximilian Rohrer, Armin Lenzen: “System Identification based on the Cross Gramian.” EWSHM 2024, 11th European Workshop on Structural Health Monitoring, Potsdam, Germany, June 10-13, 2024. DOI: https://doi.org/10.58286/29618

[4_Conf] Rohrer, M., Moeller, M., & Lenzen, A. (2024). System identification and monitoring of bridge structures. Special Issue of Procedia Structural Integrity, SMAR 2024 Proceedings. (peer reviewed) DOI: https://doi.org/10.1016/j.prostr.2024.09.194

[5_Conf] Armin Lenzen, Max Moeller, Maximilian Rohrer (2024). Schadenserkennung an Baukonstruktionen mit intelligenten Methoden der Systemidentifikation. Informatik Festival 2024, Wiesbaden, Germany, September 24-26, 2024. (peer reviewed)
 DOI: https://doi.org/10.18420/inf2024_151

[6_Conf] Rohrer, Maximilian, and Lenzen, Armin. „Systemidentifikation und Zustandsüberwachung der Floßgrabenbrücke“ 8. VDI Fachtagung Baudynamik 25, 2025. DOI: https://doi.org/10.51202/9783181024478-201

[7_Conf] Moeller, Max, and Lenzen, Armin. „Langzeitüberwachung mittels autonomoer Systemidentifikation“ 8. VDI Fachtagung Baudynamik 25, 2025. DOI: https://doi.org/10.51202/9783181024478-201

To Publications