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The geometric mean is a superior frequency response averaging method for human body vibration

journal contribution
posted on 2024-11-02, 14:08 authored by Mohammad AtapourfardMohammad Atapourfard, Jianchun Yao, Kazuhito Kato, John DavyJohn Davy
The frequency response data of human body vibration are often used for standardisation, design of transport vehicles and occupational health and safety measures. This article shows that the commonly used methods of averaging frequency response spectra, such as arithmetic averaging in the complex or magnitude domain and median averaging, are not as suitable as the less commonly used geometric averaging in the complex domain. This is because it is necessary to minimise the deviation of the measured values about the mean value and to minimise the bias from the true mean value due to noise, distortion and nonlinearity. Practitioner summary: For averaging frequency response spectra, it is necessary to minimise the bias from the true mean value. This research shows that the commonly used averaging methods, such as arithmetic averaging in the complex or magnitude domain and the median, are not as suitable as geometric averaging in the complex domain. Abbreviations: H1 Estimator: frequency response function estimation method using the cross-spectrum of the output with the input divided by the auto-spectrum of the input; ISO: International Organization for Standardization; NHK: Nippon Hatsujo Kabushiki Kaisha; PCB: PCB Group ("PCB" is abbreviation for "PicoCoulomB"); RMIT: Royal Melbourne Institute of Technology; r.m.s.: root mean square.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1080/00140139.2020.1820584
  2. 2.
    ISSN - Is published in 13665847

Journal

Ergonomics

Volume

64

Issue

2

Start page

273

End page

283

Total pages

11

Publisher

Taylor & Francis

Place published

United Kingdom

Language

English

Copyright

© 2020 Informa UK Limited, trading as Taylor & Francis Group.

Former Identifier

2006101707

Esploro creation date

2021-04-21

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