TU Dresden INSTITUT FÜR MASSIVBAU

Subproject C03

ADMO - Automatic data-driven modeling and H_2/H_∞- 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

The digital change is causing profound changes in all areas of society. In the fusion of BIM, the optimized planning, execution and management of plants, buildings and infrastructures, with Structural Health Monitoring (SHM) a digital twin functions as a central element of an efficient data organization.

The aim of this project is a method that realizes automated data-driven modeling based on the H2/H-infinite norm and methods of system identification coupled with machine learning. This enables a condition monitoring 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.

Figure 1: Aims of the research project within SPP100+
Figure 1: Aims of the research project within SPP100+
Figure 2: Overview of the overall concept
Figure 2: Overview of the overall concept

The numerical method works with stochastic multi-correlated output-only measurement data, with special consideration and classification of environmental and operational conditions. The automatically generated parameterized stochastic process models of the system and filter theory enables a prediction of future damage states on the examined structure. This gives the public authority a set of tools for 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∞-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 localized even under Environmental and Operational Conditions (EOC) [1] [5] [2_Conf] [5_Conf]
  • 2023-2024 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 localization of stiffness changes
  • 2025 Measurements at IDA-KI Bridge [4]

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 Lenzen, Armin, Autonomous Energy-Based Model Order Selection in Parameter State Space Identification Via Cross Gramian and Symmetrizer. Mechanical Systems and Signal Processing Elsevier. (Preprint) DOI: https://dx.doi.org/10.2139/ssrn.4965431
  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: doi.org10.37544/0005-6650-2024-10-63
  4. Rohrer et. al. (2025) Experimental Studies on Multi-Scale Data-Driven Methods within the Framework of Strucural Health Monitoring. Civil Engineering Design Wiley. DOI: 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.

Conferences and other publications

  1. 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. 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. 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. 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: doi.org/10.1016/j.prostr.2024.09.194
  5. 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: doi.org/10.18420/inf2024_151
  6. Rohrer, Maximilian, and Lenzen, Armin. „Systemidentifikation und Zustandsüberwachung der Floßgrabenbrücke“ 8. VDI Fachtagung Baudynamik 25, 2025. DOI: doi.org/10.51202/9783181024478-201
  7. Moeller, Max, and Lenzen, Armin. „Langzeitüberwachung mittels autonomoer Systemidentifikation“ 8. VDI Fachtagung Baudynamik 25, 2025. DOI: doi.org/10.51202/9783181024478-201

Contact

[Translate to English:]
Prof. Dr.-Ing Armin Lenzen
HTWK-Leipzig
Project leader
M.Sc. Max Moeller
HTWK-Leipzig
Research associate
M.Sc. Maximilian Rohrer
HTWK-Leipzig
Research associate

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 Lenzen, Armin, Autonomous Energy-Based Model Order Selection in Parameter State Space Identification Via Cross Gramian and Symmetrizer. Mechanical Systems and Signal Processing Elsevier. (Preprint) DOI: https://dx.doi.org/10.2139/ssrn.4965431

  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: doi.org10.37544/0005-6650-2024-10-63

  4. Rohrer et. al. (2025) Experimental Studies on Multi-Scale Data-Driven Methods within the Framework of Strucural Health Monitoring. Civil Engineering Design Wiley. DOI: 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.

Konferenz und andere VÖ

  1. 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. 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. 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. 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: doi.org/10.1016/j.prostr.2024.09.194

  5. 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: doi.org/10.18420/inf2024_151

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

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