Physical Reservoir-Based Health Monitoring of a Structure with Nonlinear Attachments

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Published Sep 4, 2023
Arata Masuda Konosuke Takashima

Abstract

The purpose of this work is to discuss the possibility of the concept of physical reservoir computing (PRC) in the field of structural health monitoring (SHM) by regarding the target structure of SHM as the physical reservoir. To this end, the dynamics of the structure, which is assumed extrinsically linear, is tailored to be strongly nonlinear by installing nonlinear attachments. Our purpose is then to detect the change occurred in this augmented physical reservoir. As one possible methodology to achieve this, we propose in this study to train the output layer to learn a specific nonlinear mapping of the input so that the increase of the error may indicate the change of the reservoir. Numerical experiments are presented to examine the validity of the proposed concept.

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Keywords

physical reservoir computing, structural health monitoring, damage detection, nonlinear dynamics

References
Caluwaerts, K., D’Haene, M., Verstraeten, D., & Schrauwen, B. (2013). Locomotion without a brain: physical reservoir computing in tensegrity structures. Artificial life, 19(1), 35–66.

Coulombe, J. C., York, M. C., & Sylvestre, J. (2017). Computing with networks of nonlinear mechanical oscillators. PloS One, 12(6), e0178663.

Farrar, C. R., & Worden, K. (2007). An introduction to structural health monitoring. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 365(1851), 303–315.

Hauser, H., Ijspeert, A. J., Fuchslin, R. M., Pfeifer, R., & ¨ Maass, W. (2011). Towards a theoretical foundation for morphological computation with compliant bodies. Biological cybernetics, 105, 355–370.

Masuda, A., Takashima, K., & Sakai, R. (2023). Physical reservoir-based structural health monitoring: a preliminary study. In Active and passive smart structures and integrated systems xvii (Vol. 12483, pp. 330–336).

Nakajima, K., Hauser, H., Li, T., & Pfeifer, R. (2015). Information processing via physical soft body. Scientific reports, 5(1), 10487.

Tanaka, G., Yamane, T., Heroux, J. B., Nakane, R., ´ Kanazawa, N., Takeda, S., . . . Hirose, A. (2019). Recent advances in physical reservoir computing: A review. Neural Networks, 115, 100–123.
Section
Regular Session Papers