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Parameter identification of sound absorption model of porous materials based on modified particle swarm optimization algorithm

Author

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  • Xiaomei Xu
  • Ping Lin

Abstract

Porous materials have been widely used in the field of noise control. The non-acoustical parameters involved in the sound absorption model have an important effect on the sound absorption performance of porous materials. How to identify these non-acoustical parameters efficiently and accurately is an active research area and many researchers have devoted contributions on it. In this study, a modified particle swarm optimization algorithm is adopted to identify the non-acoustical parameters of the jute fiber felt. Firstly, the sound absorption model used to predict the sound absorption coefficient of the porous materials is introduced. Secondly, the model of non-acoustical parameter identification of porous materials is established. Then the modified particle swarm optimization algorithm is introduced and the feasibility of the algorithm applied to the parameter identification of porous materials is investigated. Finally, based on the sound absorption coefficient measured by the impedance tube the modified particle swarm optimization algorithm is adopted to identify the non-acoustical parameters involved in the sound absorption model of the jute fiber felt, and the identification performance and the computational performance of the algorithm are discussed. Research results show that compared with other identification methods the modified particle swarm optimization algorithm has higher identification accuracy and is more suitable for the identification of non-acoustical parameters of the porous materials. The sound absorption coefficient curve predicted by the modified particle swarm optimization algorithm has good consistency with the experimental curve. In the aspect of computer running time, compared with the standard particle swarm optimization algorithm, the modified particle swarm optimization algorithm takes shorter running time. When the population size is larger, modified particle swarm optimization algorithm has more advantages in the running speed. In addition, this study demonstrates that the jute fiber felt is a good acoustical green fibrous material which has excellent sound absorbing performance in a wide frequency range and the peak value of its sound absorption coefficient can reach 0.8.

Suggested Citation

  • Xiaomei Xu & Ping Lin, 2021. "Parameter identification of sound absorption model of porous materials based on modified particle swarm optimization algorithm," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-16, May.
    • Handle: RePEc:plo:pone00:0250950
    DOI: 10.1371/journal.pone.0250950
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    Cited by:

    1. Zhun Cheng & Huadong Zhou & Zhixiong Lu, 2022. "A Novel 10-Parameter Motor Efficiency Model Based on I-SA and Its Comparative Application of Energy Utilization Efficiency in Different Driving Modes for Electric Tractor," Agriculture, MDPI, vol. 12(3), pages 1-20, March.
    2. Zhun Cheng & Zhixiong Lu, 2022. "Regression-Based Correction and I-PSO-Based Optimization of HMCVT’s Speed Regulating Characteristics for Agricultural Machinery," Agriculture, MDPI, vol. 12(5), pages 1-18, April.
    3. Yuting Chen & Zhun Cheng & Yu Qian, 2022. "Research on Wet Clutch Switching Quality in the Shifting Stage of an Agricultural Tractor Transmission System," Agriculture, MDPI, vol. 12(8), pages 1-16, August.
    4. Zhun Cheng & Yuting Chen & Wenjie Li & Pengfei Zhou & Junhao Liu & Li Li & Wenjuan Chang & Yu Qian, 2022. "Optimization Design Based on I-GA and Simulation Test Verification of 5-Stage Hydraulic Mechanical Continuously Variable Transmission Used for Tractor," Agriculture, MDPI, vol. 12(6), pages 1-13, June.
    5. Cheng, Zhun, 2023. "High nonlinearity of BEV's stepped automatic transmission design objectives and its optimal solution by a novel ISA-RSA," Energy, Elsevier, vol. 282(C).

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