1. Human-induced force reconstruction using a non-linear electrodynamic shaker applying an iterative neural network algorithm.
- Author
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PELÁEZ-RODRÍGUEZ, César, MAGDALENO, Álvaro, SALCEDO-SANZ, Sancho, and LORENZANA, Antolín
- Subjects
GROUND reaction forces (Biomechanics) ,INERTIAL mass ,DYNAMIC loads ,ALGORITHMS ,INVERSE problems ,RETINAL blood vessels - Abstract
An iterative neural network framework is proposed in this paper for the human-induced Ground Reaction Forces (GRF) replication with an inertial electrodynamic mass actuator (APS 400). This is the first approach to the systematization of dynamic load tests on structures on a purely objective, repeatable and pedestrian-independent basis. Therefore, an inversion-free offline algorithm based on Machine Learning techniques has been applied for the first time on an electrodynamic shaker, without requiring its inverse model to tackle the inverse problem of successful force reconstruction. The proposed approach aims to obtain the optimal drive signal to minimize the error between the experimental shaker output and the reference force signal, measured with a pair of instrumented insoles (Loadsol
© ) for human bouncing at different frequencies and amplitudes. The optimal performance, stability and convergence of the system are verified through experimental tests, achieving excellent results in both time and frequency domain. [ABSTRACT FROM AUTHOR]- Published
- 2023
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