中国机械工程

• 机械基础工程 • 上一篇    下一篇

基于掩蔽效应的汽车非平稳车内噪声烦恼度评价方法

冯天培1;孙跃东1;王岩松2;周萍1;郭辉2;刘宁宁2   

  1. 1.上海理工大学机械工程学院, 上海, 200093
    2.上海工程技术大学汽车工程学院, 上海, 201620
  • 出版日期:2017-12-25 发布日期:2017-12-21
  • 基金资助:
    国家自然科学基金资助项目(51675324,51175320)
    National Natural Science Foundation of China (No. 51675324,51175320)

Annoyance Subjective Evaluation Method of Automotive Interior Nonstationary Noises Based on Human Auditory Masking Effect

FENG Tianpei1;SUN Yuedong1;WANG Yansong2;ZHOU Ping1;GUO Hui2;LIU Ningning2   

  1. 1.School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, 200093
    2.Automotive Engineering College, Shanghai University of Engineering Science, Shanghai, 201620
  • Online:2017-12-25 Published:2017-12-21
  • Supported by:
    National Natural Science Foundation of China (No. 51675324,51175320)

摘要: 基于采集的汽车加速与匀速运动时车内的噪声,利用参考语义细分法进行噪声烦恼度主观评价试验。考虑掩蔽效应,依据听音评价问卷调查结果,计算加速噪声后半时段和匀速噪声的时变心理声学参量平均值,利用支持向量机创建参量平均值与烦恼度主观评价值间的回归数学模型,建立基于掩蔽效应的非平稳车内噪声烦恼度评价方法。同时计算全部噪声样本的时变心理声学参量平均值并建立基于心理声学参量的烦恼度评价方法。留一法与十折交叉法检验结果表明,两种评价方法对非平稳车内噪声烦恼度的预测精确有效,而基于掩蔽效应的烦恼度评价方法预测结果更加精确、稳定性更高;在加速噪声烦恼度的预测方面,基于掩蔽效应的烦恼度评价方法具有更好的预测性能。

关键词: 掩蔽效应, 非平稳车内噪声, 烦恼度, 心理声学参量, 支持向量机

Abstract: Based on the collected interior noises of passenger cars running at accelerating or constant speeds, a subjective evaluation test of vehicle noise annoyance was conducted using anchored semantic differential method herein. Considering masking effect and questionnaire results of the sound quality subjective estimation experiments, the average values of time-varying psychoacoustic parameters of noise samples at constant speeds and the second half of the accelerating noise samples were calculated as independent variables, a regression mathematical relation among the average values and subjective evaluation results of annoyance was built using SVM technique. A masking effect based annoyance evaluation method (ME-AE method) was developed. Furthermore, by calculating average values of time-varying psychoacoustic parameters of all noise samples, a psychoacoustic metrics based annoyance evaluation method (PM-AE method) was developed using SVM. Results of leave-one-out and 10-fold cross-validating experiments suggest that the two annoyance subjective evaluation methods are effective in predicting vehicle interior nonstationary noises with high accuracy. And the proposed ME-AE method is more accurate and stable. Especially for predicting the annoyance of acceleration noises, the new method achieves greater improvements.

Key words: masking effect, vehicle interior nonstationary noise, annoyance, psychoacoustic metrics, support vector machine(SVM)

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