支持向量机车内加速噪声声品质预测
中国测试周明刚, 刘 阳, 陈 源, 文 瑶
摘  要:为准确评价车内加速噪声声品质,利用成对比较法对14款汽车从30 km/h加速到80 km/h行驶时的车内噪声进行主观评价试验,同时计算5个主要心理声学客观参量,并通过相关分析得出对声品质有重要影响的客观参量。采用支持向量机建立车内加速噪声声品质的预测模型,经验证其预测相对误差都在9.5%以内,表明该模型可以准确地对车内噪声声品质进行预测。
关键词:声品质;加速工况;支持向量机;预测模型
文献标志码:A     文章编号:1674-5124(2015)12-0083-04
Study on the prediction of car acceleration noise sound quality based on
support vector machine 
ZHOU Minggang, LIU Yang, CHEN Yuan, WEN Yao
(Engineering Design and Research Institute of Agricultural Machinery,
Hubei University of Technology,Wuhan 430068,China)
Abstract: To accurately evaluate the sound quality of car interior accelerating noise, the noise samples from 14 different brands of cars during acceleration from 30 km/h to 80 km/h were selected, and subjective evaluation test was carried out with the paired comparison method, meanwhile, five main psychoacoustic parameters were calculated, and the objective parameters having significant effect on the sound quality were extracted by the correlation analysis. A car interior accelerating sound quality prediction model was built based on support vector machine (SVM), and the relative predict error had been proved less than 9.5% these shows that the prediction model can accurately predict the sound quality of the car interior noise.
Keywords: sound quality; accelerating condition; support vector machine; prediction model