文章摘要
吕向飞,陈进.采用响应面回归的汽车多属性声品质预测方法*[J].,2022,41(3):397-404
采用响应面回归的汽车多属性声品质预测方法*
Automobile multi-attribute accelerating sound quality prediction based on response surface regression method
投稿时间:2021-05-12  修订日期:2022-05-03
中文摘要:
      单一主观评价分数无法准确描述人耳对声品质的多属性偏好特征。本文在多属性声品质试验数据的基础上,以愉悦度、平顺度和驾驶乐趣的主观评价分数为因变量,通过相关分析筛选出响度、尖锐度和A计权声压级三个主要自变量,引入响应面回归方法,分别建立因变量与自变量之间的预测模型,通过与多元线性模型对比验证了精度。最后,建立多属性主观评价分数之间的量化映射模型。研究可为多属性汽车声品质的优化控制提供参考。
英文摘要:
      A single subjective evaluation score cannot accurately describe the multi-attribute preference characteristics of human ears for vehicle sound quality. Based on the multi-attribute sound quality test data, this paper takes the subjective evaluation scores of pleasure, ride comfort and driving pleasure as dependent variables, and three main independent variables of loudness, sharpness and A-weighted sound pressure level are screened out through correlation analysis. Response surface regression method is employed to establish the predictive model between the dependent variable and the independent variable respectively, with which the multi-attribute sound quality is evaluated accurately. Finally, a quantitative mapping model between multi-attribute subjective evaluation scores is established. The research can provide reference for the optimization and control of multi-attribute sound quality for vehicles.
DOI:10.11684/j.issn.1000-310X.2022.03.009
中文关键词: 车辆工程  声品质  响应面回归  相关分析  多属性
英文关键词: Vehicle engineering  Sound quality  Response surface regression  Correlation analysis  Multi-attribute
基金项目:
作者单位E-mail
吕向飞 重庆大学 机械传动国家重点实验室 xiangfei113072@163.com 
陈进 重庆电子工程职业学院 智能制造与汽车学院 281530767@qq.com 
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