Identification of biomechanical nonlinearity in whole-body vibration using a reverse path multi-input-single-output method
Identification of biomechanical nonlinearity in whole-body vibration using a reverse path multi-input-single-output method
The study implements a classic signal analysis technique, typically applied to structural dynamics, to examine the nonlinear characteristics seen in the apparent mass of a recumbent person during whole-body horizontal random vibration. The nonlinearity in the present context refers to the amount of ‘output’ that is not correlated or coherent to the ‘input’, usually indicated by values of the coherence function that are less than unity. The analysis is based on the longitudinal horizontal inline and vertical cross-axis apparent mass of twelve human subjects exposed to 0.25–20 Hz random acceleration vibration at 0.125 and 1.0 ms-2 r.m.s. The conditioned reverse path frequency response functions (FRF) reveal that the uncorrelated ‘linear’ relationship between physical input (acceleration) and outputs (inline and cross-axis forces) has much greater variation around the primary resonance frequency between 0.5 and 5 Hz. By reversing the input and outputs of the physical system, it is possible to assemble additional mathematical inputs from the physical output forces and mathematical constructs (e.g. square root of inline force). Depending on the specific construct, this can improve the summed multiple coherence at frequencies where the response magnitude is low. In the present case this is between 6 and 20 Hz. The statistical measures of the response force time histories of each of the twelve subjects indicate that there are potential anatomical ‘end-stops’ for the sprung mass in the inline axis. No previous study has applied this reverse path multi-input-single-output approach to human vibration kinematic and kinetic data before. The implementation demonstrated in the present study will allow new and existing data to be examined using this different analytical tool.
337-351
Huang, Ya
1d6f90c0-4516-45ab-bd7a-7c86c119ee4b
Ferguson, Neil
8cb67e30-48e2-491c-9390-d444fa786ac8
14 April 2018
Huang, Ya
1d6f90c0-4516-45ab-bd7a-7c86c119ee4b
Ferguson, Neil
8cb67e30-48e2-491c-9390-d444fa786ac8
Huang, Ya and Ferguson, Neil
(2018)
Identification of biomechanical nonlinearity in whole-body vibration using a reverse path multi-input-single-output method.
Journal of Sound and Vibration, 419, .
(doi:10.1016/j.jsv.2018.01.002).
Abstract
The study implements a classic signal analysis technique, typically applied to structural dynamics, to examine the nonlinear characteristics seen in the apparent mass of a recumbent person during whole-body horizontal random vibration. The nonlinearity in the present context refers to the amount of ‘output’ that is not correlated or coherent to the ‘input’, usually indicated by values of the coherence function that are less than unity. The analysis is based on the longitudinal horizontal inline and vertical cross-axis apparent mass of twelve human subjects exposed to 0.25–20 Hz random acceleration vibration at 0.125 and 1.0 ms-2 r.m.s. The conditioned reverse path frequency response functions (FRF) reveal that the uncorrelated ‘linear’ relationship between physical input (acceleration) and outputs (inline and cross-axis forces) has much greater variation around the primary resonance frequency between 0.5 and 5 Hz. By reversing the input and outputs of the physical system, it is possible to assemble additional mathematical inputs from the physical output forces and mathematical constructs (e.g. square root of inline force). Depending on the specific construct, this can improve the summed multiple coherence at frequencies where the response magnitude is low. In the present case this is between 6 and 20 Hz. The statistical measures of the response force time histories of each of the twelve subjects indicate that there are potential anatomical ‘end-stops’ for the sprung mass in the inline axis. No previous study has applied this reverse path multi-input-single-output approach to human vibration kinematic and kinetic data before. The implementation demonstrated in the present study will allow new and existing data to be examined using this different analytical tool.
Text
JSV-D-17-01406 accepted version
- Accepted Manuscript
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Accepted/In Press date: 4 January 2018
e-pub ahead of print date: 12 February 2018
Published date: 14 April 2018
Identifiers
Local EPrints ID: 416785
URI: http://eprints.soton.ac.uk/id/eprint/416785
ISSN: 0022-460X
PURE UUID: d1d67b63-b361-45d8-ba53-d4163e30d69a
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Date deposited: 10 Jan 2018 17:30
Last modified: 16 Mar 2024 06:05
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Author:
Ya Huang
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