Analysis of acoustic performance of glass fiber felts after water absorption and their estimation results by artificial neural network

被引：13

作者：

Wang, Fei ^{[1
,2
]}

Chen, Zhaofeng ^{[1
,2
]}

Wu, Cao ^{[1
,2
]}

Yang, Yong ^{[3
]}

Zhang, Duanyin ^{[1
,2
]}

Li, Shun ^{[1
,2
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Coll Mat Sci & Technol, Int Lab Insulat & Energy Efficiency Mat, Nanjing, Jiangsu, Peoples R China

[2] Suqian NUAA Inst Adv Mat & Equipment Mfg Co Ltd, Suqian, Peoples R China

[3] Soochow Univ, Coll Text & Clothing Engn, Suzhou, Peoples R China

来源：

JOURNAL OF THE TEXTILE INSTITUTE | 2020年 / 111卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Glass fiber felts; acoustic performance; artificial neural network; SOUND INSULATION; PREDICTION; SEQUENCE; POROSITY;

D O I：

10.1080/00405000.2019.1678559

中图分类号：

TB3 [工程材料学]; TS1 [纺织工业、染整工业];

学科分类号：

0805 ; 080502 ; 0821 ;

摘要：

The acoustic performance of glass fiber felts after water absorption was researched in the paper. The effects of sound frequency and moisture content on the sound transmission loss (STL) and sound absorption coefficient (SAC) were analyzed. In addition, two types of artificial neural networks (ANN) were established to estimate the acoustic performance. In the first ANN model, the sound frequency and moisture content were chosen as input parameters to predict the STL and SAC values. In another model, the output parameters were replaced by the ratios of STL and SAC to areal density. In order to evaluate the accuracy of the two models, the mean relative error and correlation coefficient were calculated respectively. It has been proved that the predicted values resulted from ANN models fit well with the measured values.

引用

页码：1008 / 1016

页数：9

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