Experimental and simulation research on the difference in motion technology levels based on nonlinear characteristics

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Abstract

Wearable and movable lodged health monitoring gadgets, micro-sensors, human system locating gadgets, and other gadgets started to appear as low-power communication mechanisms and microelectronics mechanisms grew in popularity. More people are interested in energy capture technology, which turns the energy created by motion technology into electric energy. To understand the difference in motor skill levels, a nonlinear feature-oriented method was proposed. A bi-stable magnetic-coupled piezoelectric cantilever was designed to detect the horizontal difference of motion technology. The horizontal difference was increased by the acceleration generated by the oscillation of the leg and the impression betwixt the leg and the ground during the movement. Based on the Hamiltonian principle and motion technique signal, a nonlinear dynamic model for energy capture in motion technique is established. According to the shaking features of human leg motion, a moveable nonlinear shaking energy-gaining system was the layout, which realized the dynamic characteristics of straight, nonlinear, mono-stable, and bi-stable. The experimental outcome shows that nonlinearity can effectively detect the difference of motion techniques. The experimental results of different human movement states confirm the benefits of the uncertain bi-stable human power capture mechanism and the effectiveness of the electromechanical combining design established. The nonlinear mono-stable beam moves in the same way as the straight mono-stable beam in the assessment, but owing to its higher stiffness, its frequency concentration range (13.85 Hz) is moved to the right compared to the linear mono-stable beam, and the displacement of the cantilever beam is reduced. If the velocity is 8 km/h, the mean energy of the bi-stable method extends to the utmost value of 23.2 μW. It is proved that the nonlinear method can understand the difference in the level of motion technique effectively.

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Liang, G., Fu, H., Ganapathy, S., Bhola, J., Doddawad, V. G., Athawale, S. V., & Bhatia, K. K. (2022). Experimental and simulation research on the difference in motion technology levels based on nonlinear characteristics. Nonlinear Engineering, 11(1), 629–636. https://doi.org/10.1515/nleng-2022-0204

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