摘要
针对特种车车内噪声声品质提升问题,利用极限梯度提升(XGBoost)算法建立声品质预测模型,模型预测值与实际主观评价值的平均相对误差为2.43%,分析得到客观参数对主观分数的影响权重;针对车内噪声非线性、非平稳性的特点,提出一种基于经验模态分解(Empirical Mode Decomposition,EMD)和滤波-x最小均方(Filtered-x Least Mean Square,FxLMS)算法相结合的主动控制方法,预测模型结果表明,主观分数提升2.11,提升幅度为26.6%。此方法对特种车内噪声非线性、非平稳性具有良好的控制效果,能有效改善车内声品质。
Aiming at improving the sound quality of the interior noise of special vehicles,the XGBoost algorithm is used to estab-lish a sound quality prediction model.The average relative error between the predicted value of the model and the actual subjective evaluation value is 2.43%.At the same time,according to the nonlinear and non-stationary characteristics of interior noise,an algo-rithm based on Empirical Mode Decomposition(EMD)and Filtered-x Least Mean Square(FxLMS)algorithm is proposed.Based on the active control method,the results of the prediction model show that subjective irritability is optimized by 2.11,with an improvement rate of 26.6%.This method has a good control effect on the nonlinearity and non-stationarity of special vehicle in-terior noise,and can effectively improve the interior sound quality.
作者
欧健
彭沸潭
张庆庭
覃亮
杨鄂川
OU Jian;PENG Fei-tan;ZHANG Qing-ting;QIN Liang;YANG E-chuan(School of Vehicle Engineering,Chongqing University of Technology,Chongqing 400054,China;Chongqing Dajiang Special Equipment for Smart Defense Co.,Ltd.,Chongqing 401320,China)
出处
《振动工程学报》
EI
CSCD
北大核心
2023年第5期1349-1355,共7页
Journal of Vibration Engineering
基金
重庆市基础与前沿研究计划项目(cstc18jcyjAX0092)
重庆市教委科学技术研究项目(KJQN201901146)
重庆市自然科学基金资助项目(cstc2019jcyj-msxmX0204)
重庆理工大学研究生创新项目(gzlcx20222130)。
