An Innovation of Evaluation and Design of Vehicle Acceleration Sound Based on EEG Signals

作     者：Liping Xie XinYou Lin Wan Chen Zhien Liu Yawei Zhu Liping Xie;XinYou Lin;Wan Chen;Zhien Liu;Yawei Zhu

作者机构：College of Mechanical Engineering&AutomationFuzhou UniversityFuzhou 350108China Hubei Collaborative Innovation Center for Automotive Components TechnologyWuhan University of TechnologyWuhan 430070China 

出 版 物：《Journal of Bionic Engineering》 (仿生工程学报（英文版）)

年 卷 期：2024年第21卷第1期

页      面：344-361页

核心收录：

学科分类：08[工学] 09[农学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0901[农学-作物学] 0836[工学-生物工程] 0811[工学-控制科学与工程] 090102[农学-作物遗传育种] 

基　　金：supported by the National Natural Science Foundation of China(No.52272389) the National Natural Science Foundation of China(No.52175111) 

主　　题：EEG signal Brain activity analysis Vehicle sound design Adaptive genetic algorithm-Elman model 

摘      要：There is a bottleneck in the design of vehicle sound that the subjective perception of sound quality that combines multiple psychological factors fails to be accurately and objectively ***,EEG signals are introduced in this paper to investigate the evaluation and design method of vehicle acceleration sound with powerful sound ***,the experiment of EEG acquisition and subjective evaluation under the stimulation of powerful vehicle sounds is conducted,respectively,then three physiological EEG features of PSD_β,PSD_γand DE are constructed to evaluate the vehicle sounds based on the correlation analysis ***,the Adaptive Genetic Algorithm(AGA)is proposed to optimize the Elman model,where an intelligent model(AGA–Elman)is constructed to objectively predicate the perception of subjects for the vehicle sounds with powerful sound *** results demonstrate that the error of the constructed AGA–Elman model is only 2.88%,which outperforms than the traditional BP and Elman model;Finally,two vehicle acceleration sounds(Design1 and Design2)are designed based on the constructed AGA–Elman model from the perspective of order modulation and frequency modulation,which provide the acoustic theoretical guidance for the design of vehicle sound incorporating the EEG signals.