This paper shows input-output analysis of a neural oscillator swarm stimulated by earthquake-induced acceleration responses of a structure. We have proposed a new active mass damper system consisting of a neural oscillator and a position controller. However, the proposed system has not adapted successfully to parameter changes of the structure. Recent studies in biology have demonstrated that multiple oscillators have hierarchical network structures to ensure adaptation to environmental changes. To improve the robust performance of the proposed system by constructing of hierarchical network of neural oscillators, there is a need for a better understanding of nature of different neural oscillators. This research addressed this need by visualizing output of swarm of neural oscillators, whose natural frequencies and input gains are different. The numerical information of output is visualized by grayscale, and the relation of output of different neural oscillators is considered when input is the same. As a result, the research provides new information that predicts the instant center frequency of a structure excited by earthquakes.
Hideya Tokumura, Daisuke Iba, Jyunichi Hongu, Sohei Shima, and Ichiro Moriwaki, "Output analysis of swarm of neural oscillators stimulated by earthquake-induced acceleration responses of a structure ," Proc. SPIE 10598, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018, 105982T (Presented at SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring: March 08, 2018; Published: 27 March 2018); https://doi.org/10.1117/12.2296522.
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