Proposal of the evaluation function for the optimal selection of measurement location in inverse-numerical acoustic analysis

Noise reduction of industrial products has been required for dealing with noise problem and satisfying comfortable living space. To reduce noise of the products, we need to identify surface that radiates the noise, and take measure against the noise. As a method to identify sound source, inverse-num...

Full description

Bibliographic Details
Main Authors: Masahiro AKEI, Nobutaka TSUJIUCHI, Daisuke KUBOTA, Akihito ITO, Takayuki YAMAUCHI
Format: Article
Language:Japanese
Published: The Japan Society of Mechanical Engineers 2016-05-01
Series:Nihon Kikai Gakkai ronbunshu
Subjects:
Online Access:https://www.jstage.jst.go.jp/article/transjsme/82/837/82_15-00646/_pdf/-char/en
Description
Summary:Noise reduction of industrial products has been required for dealing with noise problem and satisfying comfortable living space. To reduce noise of the products, we need to identify surface that radiates the noise, and take measure against the noise. As a method to identify sound source, inverse-numerical acoustic analysis (INA) has been proposed. INA is a method that identifies surface vibration of the sound source by using acoustic transfer functions and actual sound pressures which are measured at field points located near the sound source. In the INA, the measured sound pressures are used as the input data. For measuring sound pressures, we need to decide the arrangement of the field points, namely the number of microphones and its positions. The increase of field points leads to longer test and analysis time. Therefore, guidelines for the field point arrangement are needed to carry out the INA efficiently. In this study, we focused on the standard deviations of distance between sound source elements and field points, and proposed new evaluation function for optimal selection of the field points based on the standard deviations. The effectiveness of the new evaluation function had been verified by using plate model. As a result, we confirmed that the selection of optimal field point arrangement was achieved by using two guidelines, which are condition number and the new evaluation function we proposed.
ISSN:2187-9761