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灵敏度分析法在车内噪声优化中的应用 被引量:2

Application of Sensitivity Analysis to Optimization of Vehicle Interior Noise
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摘要 针对某款运动型多用途车(SUV)车型存在行驶时车内噪声过大的问题,建立了该车型的车身声固耦合模型。通过仿真分析了在发动机左侧悬置点处稳态激励下的车内声学响应,找出了目标场点的声压峰值以及对应的频率。首先,建立发动机左侧悬置点处到驾驶员右耳处这条传递路径的响应面模型,应用Sobol’全局灵敏度分析法,筛选出对声学响应影响最大的板件。然后,针对这些板件再次进行局部灵敏度分析,找出了这些板件厚度变化的具体影响,并据此确定了优化过程中设计变量的取值范围。最后,建立优化数学模型进行声学响应优化。研究结果表明:应用灵敏度分析法的优化过程效率更高,优化后目标场点的峰值声压降低了6.5 d B(A),并且在整个分析频段内,车内整体噪声有较明显的降低。 In view of the noise problem of sport utility vehicle( SUV),an acoustic structure coupling model for the vehicle body was established. The acoustic response of the vehicle under the steady stimulation on the left engine mounting point was predicted by simulation. The peak sound pressure and the corresponding frequencies of the target sites were found out. To facilitate the subsequent optimization analysis,the response surface model of the transmission path of the left engine mounting point to the right ear of the driver was established. With the application of Sobol ' global sensitivity analysis,the greatest effects of plates on acoustic response were selected,then local sensitivity analysis was performed for these plates. The specific influence of these plates was analyzed when thickness varied. Based on this,the value range of design variables in the optimization process was determined. At last,a mathematical model was established to optimize the acoustic response. The results show that the efficiency of the optimization process based on the results of sensitivity analysis is proved to be higher,and the peak sound pressure of the target field is decreased by 6. 5 d B( A). In the entire analysis frequency segment,the overall sound level in the car reductes obviously.
作者 潘公宇 任成
出处 《河南科技大学学报(自然科学版)》 CAS 北大核心 2018年第6期35-40,44,共7页 Journal of Henan University of Science And Technology:Natural Science
基金 国家自然科学基金项目(51575238)
关键词 车内噪声 声固耦合 响应面模型 Sobol’全局灵敏度分析 局部灵敏度分析 vehicle interior noise acoustic structure coupling response surface model Sobol'global sensitivity analysis local sensitivity analysis
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