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Strain predictions at unmeasured locations of a substructure using sparse response-only vibration measurements

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Abstract

Structural health monitoring of complex structures is often limited by restricted accessibility to locations of interest within the structure and availability of operational loads. In this work, a novel output-only virtual sensing scheme is proposed. This scheme involves the implementation of the modal expansion in an augmented Kalman filter. The performance of the proposed scheme is compared with two existing methods. Method 1 relies on a finite element model updating, batch data processing, and modal expansion (MUME) procedure. Method 2 employs a recursive sequential estimation algorithm, which feeds a substructure model of the instrumented system into an augmented Kalman filter (AKF). The new scheme referred to as Method 3 (ME-AKF), implements strain estimates generated via Modal Expansion into an AKF as virtual measurements. To demonstrate the applicability of the aforementioned methods, a rollercoaster connection was instrumented with accelerometers, strain rosettes, and an optical sensor. A comparison of estimated dynamic strain response at unmeasured locations using three alternative schemes is presented. Although acceleration measurements are used indirectly for model updating, the response-only methods presented in this research use only measurements from strain rosettes for strain history predictions and require no prior knowledge of input forces. Predicted strains using all methods are shown to sufficiently predict the measured strain time histories from a control location and lie within a 95% confidence interval calculated based on modal expansion equations. In addition, the proposed ME-AKF method shows improvement in strain predictions at unmeasured locations without the necessity of batch data processing. The proposed scheme shows high potential for real-time dynamic estimation of the strain and stress state of complex structures at unmeasured locations.

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Data availability

Limited availability to strain, acceleration, and optical sensor data measured from the rollercoaster support bracket used during this research. Some data can be made available by a request to the corresponding author and upon approval from the amusement park management.

Code availability

Relevant code to this research is limited. Availability can be granted by a request to the corresponding author and upon approval from the amusement park management.

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Acknowledgements

Data required to conduct the research presented in this paper would not have been possible without the collaboration of Mike Neuzil who provided the research team access and resources to accomplish data acquisition of the rollercoaster used in this research and also accommodating the use of LiDAR for geometric mapping. In addition, the authors would like to thank Dr. Jesse D. Sipple from BDI for helpful discussions and technical advice on setup of a wireless data acquisition system using various sensor types.

Funding

The writers are grateful for the funding of this research by NSF Division of Industrial Innovation and Partnership (IIP) Grant No. IIP-1640693. PFI: AIR-TT: Real-Time Fatigue Life Prediction for Decision-making and Asset Management. Any opinions, findings, and conclusions or recommendations expressed in this research are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Tufts University, Medford, MA, 02155, USA

    Sofia Puerto Tchemodanova, Masoud Sanayei & Babak Moaveni

  2. Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zürich, Switzerland

    Konstantinos Tatsis & Eleni Chatzi

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  1. Sofia Puerto Tchemodanova
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  2. Masoud Sanayei
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Correspondence to Masoud Sanayei.

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Tchemodanova, S.P., Sanayei, M., Moaveni, B. et al. Strain predictions at unmeasured locations of a substructure using sparse response-only vibration measurements. J Civil Struct Health Monit 11, 1113–1136 (2021). https://doi.org/10.1007/s13349-021-00476-x

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