车内语言清晰度分析评价及其主动控制技术研究
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摘要
车内噪声是影响乘车人舒适性、听觉、语言清晰度以及对车内外各种声音讯号识别能力的重要因素。车内噪声水平已经成为汽车乘坐舒适性的重要性能指标之一，它的优劣直接影响汽车产品的竞争力和消费者的购车取向。现有汽车噪声法规和标准中，多采用A计权声压级作为汽车噪声水平的评价指标，其强制规定了汽车噪声允许达到的声压级限值，但是未深入考虑车内噪声特性。随着汽车工业的进一步发展，对汽车噪声水平和品质有了更高的要求，单一A计权声压级指标已经无法满足，车内噪声品质评价迅速发展起来，它指出了人对噪声的感受由人生理和心理共同影响，反映了噪声受众对噪声的主观感觉与评判。结合本课题组承担的国家自然基金项目《车内噪声品质分析评价及其自适应主动控制方法研究》（项目编号：50975119），开展了汽车噪声品质的分析评价，以及自适应主动控制方法和技术的研究。
首先，针对不同车型在典型工况下的车内噪声，进行语言清晰度测试试验，研究用声学客观评价参量对车内语言清晰度进行建模，建立与试验结果相一致的车内语言清晰度客观评价模型。具体通过组织听音人对车内噪声环境背景下的语言清晰度进行实验室主观听音评价，得到车内噪声环境下语言清晰度测试试验结果。同时计算了车内噪声样本的声学客观评价参量，包括有语言清晰度指数、响度、尖锐度、粗糙度、两种不同计权声压级、PSIL、SIL、SIL(3)。采用回归分析方法，建立了与语言清晰度测试试验结果相一致的，以声学客观评价参量为变量的车内语言清晰度客观评价模型。对比分析了建立的多元线性回归和二次多项式车内语言清晰度模型之间的优劣，并进行了模型检验，最终验证了与语言清晰度指数相关的二次多项式车内语言清晰度客观评价模型，具有好的拟合优度和数据检验显著水平。
其次，在分析车内噪声特性基础上，对车内噪声按照ERB进行了特征频带划分，利用参数化滤波技术对不同特征频带噪声声压级进行处理，得到了用于声学客观评价参量特征频带灵敏度分析的噪声样本，并计算了噪声样本的各声学客观评价参量，分析确定了不同特征频带噪声声压级的变化对声学客观评价参量的灵敏度，特别分析了车内语言清晰度特征频带灵敏度。语言清晰度指数敏感频带集中在特征频带5及其附近特征频带，其特征频带灵敏度相对变化率曲线呈“漏斗”状。优先改变这些特征频带噪声声压级可显著调节语言清晰度指数的数值大小与车内语言清晰度状况。心理声学客观评价参量响度、尖锐度、粗糙度、A计权声压级的敏感频带集中在前5个特征频带，前5个特征频带车内噪声声压级变化对上述车内噪声心理声学客观评价参量影响显著。
为寻求车内语言清晰度主动控制最优目标，进一步分析了车内噪声中低频特征频带成分特性。设计了6个特征频带5种试验水平的试验，并提出了以语言清晰度指数和声音品质客观评价模型得分作为试验指标考察车内语言清晰度优化问题。对60km/h、100km/h、120km/h匀速行驶时车内噪声样本进行正交试验，运用极差分析方法，计算得到了语言清晰度指数和声音品质客观评价模型得分的各特征频带优水平和最优组合。依据试验指标各特征频带的最优组合，通过实验验证了最优组合控制在改善车内语言清晰度和声音品质方面的能力。
然后，提出了以FSLLMS为核心的ANE主动控制算法，该算法以ERB进行特征频带划分，能实现选择性抵消或补充不同特征频带噪声声压级。在Matlab/Simulink仿真环境下构建了以该算法为核心的车内语言清晰度自适应主动控制系统模型。针对100km/h匀速行驶时车内噪声，利用车内语言清晰度主动控制系统进行了改进车内语言清晰度和声音品质的主动控制仿真。改进车内语言清晰度，使车内语言清晰度客观评价模型达到最优的主动控制，能有效降低噪声声压级，语言清晰度指数提高了14.3%；改进车内声音品质，使声音品质客观评价模型得分达到最优的主动控制，优化了声音品质的综合表现，优化率达到8.93%。
最后，设计开发了具有自主知识产权的车内语言清晰度自适应主动控制器，编写了相应的控制程序，构建了车内语言清晰度自适应主动控制系统。进行了60km/h、100km/h、120km/h三种工况下的车内噪声实车控制试验，分析了控制前后车内语言清晰度和声音品质的变化情况。改进车内语言清晰度，使车内语言清晰度客观评价模型达到最优的主动控制，能有效地降低车内噪声的声压级和响度，提高车内语言清晰度，响度最大降低量达到7.14sone，语言清晰度指数最大提高了17.05%；改进车内声音品质，使声音品质客观评价模型得分达到最优的主动控制，能够改善车内声音品质，其最大改进率达到14.48%，同时车内语言清晰度指数也有所提高，最大改进率达到14.96%。该试验结果令人满意，证明了提出的主动控制算法能有效实现车内声音品质的改善。
Automotive interior noise can affect the performance of ride comfort, hearing damage,speech intelligibility. It also deprived occupant of identifying the wanted information fromvarious sound signals resulted from inside and outside the vehicle. The interior noise levelhas become one of the important performance indicators of ride comfort, and it directlyaffects the competitiveness and consumer orientation towards to the automotive products.The A-weighted sound pressure level (SPL) is almost used as a vehicle noise levelevaluation among current automotive noise regulations and standards. These laws andregulations set a limitation to SPL of automotive noise, but did not take the interior noisecharacteristics into considered in depth. The quicker development of the automotiveindustry is the higher requirements are put forward to automotive noise and sound quality.Sound quality evaluation has been developed rapidly because single A-weighted SPL hasbeen unable to fully meet task in automotive industry. It pointed out that people feel thenoise affected by human physiological and psychological, and reflect a subjective feelingand evaluation. Supported by National Natural Science Foundation project,“the analysisand evaluation of sound quality of interior noise and adaptive active control methods”(itemnumber:50975119), automotive sound quality are conducted to analyze the characteristicsof interior noise and the methods of adaptive active control are researched.
Firstly, the test of speech intelligibility is carried out under interior noise when car isoperating at different conditions. The relationship between speech intelligibility andacoustics objective evaluation indexes is studied. And then the establishment of an objectiveevaluation model of speech intelligibility is consistent with the test results. The testingresults of speech intelligibility are obtained thought organizing many audients to do the subjective evaluation of the speech intelligibility in the vehicle interior noise background.At the same time, the acoustic objective evaluation indexes of the vehicle noise sampleshave been calculated, such as speech intelligibility index, loudness, sharpness, roughness,2different weighted SPL, PSIL, SIL, and SIL(3). Two objective evaluation models of speechintelligibility with the independent variable of acoustic objective index are established byregression analysis. These models are consistent with the testing result. The advantage ofmultiple linier regression and quadratic polynomial model has been compared. The resultshows that the quadratic polynomial objective evaluation model of speech intelligibility,related the SII, has better fitness and signification level.
Secondly, the vehicle interior noise frequency band has been divided according to ERB,and the different special bandwidth noise has been processed with parametric filteringmethod and the processed noise samples are used to analysis the special bandwidthsensitivity of acoustic objective evaluation indexes. In addition, acoustic objectiveevaluation index of the all noise sample has been calculated, and the sensitivity of the SPLchange of different special bandwidth noise on the acoustic objective evaluation index hasbeen analyzed. And the special bandwidth sensitivity of speech intelligibility has beentechnically analyzed. The sensitive frequency bandwidth of speech intelligibility index isconcentrated at the5th and nearby special bandwidth and its relative gradient curve isfunnel-shaped. The change of the SPL in these special bandwidths can significantly adjustthe value of speech intelligibility index. The sensitive bandwidth of the psychologicalobjective evaluation indexes such as loudness, sharpness, roughness and A-weighted SPLare concentrated in the first5special bandwidths. So the change of the SPL in these specialbandwidths has been a dramatic influence on these indexes.
Furthermore, the mid-low frequency band character of the vehicle interior noise hasbeen analyzed to acquire the optimal target of speech intelligibility. The speechintelligibility index and sound quality objective evaluating model’s score has been proposedas testing indexes, and a testing schedule with6special bandwidths and5testing levels hasbeen designed to evaluate the question of interior noise optimization. Do the orthogonally experiments on the interior noise sample of the working condition of60km/h,100km/h and120km/h, and the optimal combination of the optimal levels in each special bandwidthbased on the speech intelligibility and sound quality evaluating model has been obtainedthought the range analysis. The all results are validated to improve the sound quality byexperiments based on the conclusion from the combination of orthogonal experiments.
Then, an ANE active control algorithm with the FSLLMS core is proposed. It canachieve selective counteract or supplement to the different special bandwidths’ SPL. Thespeech intelligibility adaptive active control model is established in MATLAB/Simulink. Dothe active control simulation on the interior speech intelligibility and sound qualityimprovement using interior active control system with the working condition of100km/h.To improve interior speech intelligibility, the target is to enable the objective evaluatingmodel reach optimal active control level which can effectively reduce the noise SPL andincrease the speech intelligibility index by14.3%. To improve the interior sound quality, thetarget is enable the objective evaluating model’s score reach the optimal strategy which canmake better sound quality comprehensive performance with improvement rate of8.93%.
Finally, an adaptive active controller with proprietary intelligent property of the speechintelligibility is developed and the relative control program is written and the adaptiveactive control system of speech intelligibility is constructed. Do the real vehicle noisetesting in the working condition of60km/h,80km/h and120km/h, and analyze thedifference between the interior SPL before and after control. The adaptive active controlsystem of speech intelligibility is aimed to improve the performance of speech intelligibilitywhich can reduced the value of loudness with maximum reduction of7.14sones andenhance speech intelligibility with the maximum improvement rate of17.05%; the system isaimed to effectively improve the score of sound quality objective evaluation model whichcan achieve the biggest improvement rate of14.48%. Besides, the interior speechintelligibility index was also increased by14.96%. The satisfied test results can present that the proposed algorithm and corresponding control system is not only effective but also canachieve improvement in interior sound quality.
首先，针对不同车型在典型工况下的车内噪声，进行语言清晰度测试试验，研究用声学客观评价参量对车内语言清晰度进行建模，建立与试验结果相一致的车内语言清晰度客观评价模型。具体通过组织听音人对车内噪声环境背景下的语言清晰度进行实验室主观听音评价，得到车内噪声环境下语言清晰度测试试验结果。同时计算了车内噪声样本的声学客观评价参量，包括有语言清晰度指数、响度、尖锐度、粗糙度、两种不同计权声压级、PSIL、SIL、SIL(3)。采用回归分析方法，建立了与语言清晰度测试试验结果相一致的，以声学客观评价参量为变量的车内语言清晰度客观评价模型。对比分析了建立的多元线性回归和二次多项式车内语言清晰度模型之间的优劣，并进行了模型检验，最终验证了与语言清晰度指数相关的二次多项式车内语言清晰度客观评价模型，具有好的拟合优度和数据检验显著水平。
其次，在分析车内噪声特性基础上，对车内噪声按照ERB进行了特征频带划分，利用参数化滤波技术对不同特征频带噪声声压级进行处理，得到了用于声学客观评价参量特征频带灵敏度分析的噪声样本，并计算了噪声样本的各声学客观评价参量，分析确定了不同特征频带噪声声压级的变化对声学客观评价参量的灵敏度，特别分析了车内语言清晰度特征频带灵敏度。语言清晰度指数敏感频带集中在特征频带5及其附近特征频带，其特征频带灵敏度相对变化率曲线呈“漏斗”状。优先改变这些特征频带噪声声压级可显著调节语言清晰度指数的数值大小与车内语言清晰度状况。心理声学客观评价参量响度、尖锐度、粗糙度、A计权声压级的敏感频带集中在前5个特征频带，前5个特征频带车内噪声声压级变化对上述车内噪声心理声学客观评价参量影响显著。
为寻求车内语言清晰度主动控制最优目标，进一步分析了车内噪声中低频特征频带成分特性。设计了6个特征频带5种试验水平的试验，并提出了以语言清晰度指数和声音品质客观评价模型得分作为试验指标考察车内语言清晰度优化问题。对60km/h、100km/h、120km/h匀速行驶时车内噪声样本进行正交试验，运用极差分析方法，计算得到了语言清晰度指数和声音品质客观评价模型得分的各特征频带优水平和最优组合。依据试验指标各特征频带的最优组合，通过实验验证了最优组合控制在改善车内语言清晰度和声音品质方面的能力。
然后，提出了以FSLLMS为核心的ANE主动控制算法，该算法以ERB进行特征频带划分，能实现选择性抵消或补充不同特征频带噪声声压级。在Matlab/Simulink仿真环境下构建了以该算法为核心的车内语言清晰度自适应主动控制系统模型。针对100km/h匀速行驶时车内噪声，利用车内语言清晰度主动控制系统进行了改进车内语言清晰度和声音品质的主动控制仿真。改进车内语言清晰度，使车内语言清晰度客观评价模型达到最优的主动控制，能有效降低噪声声压级，语言清晰度指数提高了14.3%；改进车内声音品质，使声音品质客观评价模型得分达到最优的主动控制，优化了声音品质的综合表现，优化率达到8.93%。
最后，设计开发了具有自主知识产权的车内语言清晰度自适应主动控制器，编写了相应的控制程序，构建了车内语言清晰度自适应主动控制系统。进行了60km/h、100km/h、120km/h三种工况下的车内噪声实车控制试验，分析了控制前后车内语言清晰度和声音品质的变化情况。改进车内语言清晰度，使车内语言清晰度客观评价模型达到最优的主动控制，能有效地降低车内噪声的声压级和响度，提高车内语言清晰度，响度最大降低量达到7.14sone，语言清晰度指数最大提高了17.05%；改进车内声音品质，使声音品质客观评价模型得分达到最优的主动控制，能够改善车内声音品质，其最大改进率达到14.48%，同时车内语言清晰度指数也有所提高，最大改进率达到14.96%。该试验结果令人满意，证明了提出的主动控制算法能有效实现车内声音品质的改善。
Automotive interior noise can affect the performance of ride comfort, hearing damage,speech intelligibility. It also deprived occupant of identifying the wanted information fromvarious sound signals resulted from inside and outside the vehicle. The interior noise levelhas become one of the important performance indicators of ride comfort, and it directlyaffects the competitiveness and consumer orientation towards to the automotive products.The A-weighted sound pressure level (SPL) is almost used as a vehicle noise levelevaluation among current automotive noise regulations and standards. These laws andregulations set a limitation to SPL of automotive noise, but did not take the interior noisecharacteristics into considered in depth. The quicker development of the automotiveindustry is the higher requirements are put forward to automotive noise and sound quality.Sound quality evaluation has been developed rapidly because single A-weighted SPL hasbeen unable to fully meet task in automotive industry. It pointed out that people feel thenoise affected by human physiological and psychological, and reflect a subjective feelingand evaluation. Supported by National Natural Science Foundation project,“the analysisand evaluation of sound quality of interior noise and adaptive active control methods”(itemnumber:50975119), automotive sound quality are conducted to analyze the characteristicsof interior noise and the methods of adaptive active control are researched.
Firstly, the test of speech intelligibility is carried out under interior noise when car isoperating at different conditions. The relationship between speech intelligibility andacoustics objective evaluation indexes is studied. And then the establishment of an objectiveevaluation model of speech intelligibility is consistent with the test results. The testingresults of speech intelligibility are obtained thought organizing many audients to do the subjective evaluation of the speech intelligibility in the vehicle interior noise background.At the same time, the acoustic objective evaluation indexes of the vehicle noise sampleshave been calculated, such as speech intelligibility index, loudness, sharpness, roughness,2different weighted SPL, PSIL, SIL, and SIL(3). Two objective evaluation models of speechintelligibility with the independent variable of acoustic objective index are established byregression analysis. These models are consistent with the testing result. The advantage ofmultiple linier regression and quadratic polynomial model has been compared. The resultshows that the quadratic polynomial objective evaluation model of speech intelligibility,related the SII, has better fitness and signification level.
Secondly, the vehicle interior noise frequency band has been divided according to ERB,and the different special bandwidth noise has been processed with parametric filteringmethod and the processed noise samples are used to analysis the special bandwidthsensitivity of acoustic objective evaluation indexes. In addition, acoustic objectiveevaluation index of the all noise sample has been calculated, and the sensitivity of the SPLchange of different special bandwidth noise on the acoustic objective evaluation index hasbeen analyzed. And the special bandwidth sensitivity of speech intelligibility has beentechnically analyzed. The sensitive frequency bandwidth of speech intelligibility index isconcentrated at the5th and nearby special bandwidth and its relative gradient curve isfunnel-shaped. The change of the SPL in these special bandwidths can significantly adjustthe value of speech intelligibility index. The sensitive bandwidth of the psychologicalobjective evaluation indexes such as loudness, sharpness, roughness and A-weighted SPLare concentrated in the first5special bandwidths. So the change of the SPL in these specialbandwidths has been a dramatic influence on these indexes.
Furthermore, the mid-low frequency band character of the vehicle interior noise hasbeen analyzed to acquire the optimal target of speech intelligibility. The speechintelligibility index and sound quality objective evaluating model’s score has been proposedas testing indexes, and a testing schedule with6special bandwidths and5testing levels hasbeen designed to evaluate the question of interior noise optimization. Do the orthogonally experiments on the interior noise sample of the working condition of60km/h,100km/h and120km/h, and the optimal combination of the optimal levels in each special bandwidthbased on the speech intelligibility and sound quality evaluating model has been obtainedthought the range analysis. The all results are validated to improve the sound quality byexperiments based on the conclusion from the combination of orthogonal experiments.
Then, an ANE active control algorithm with the FSLLMS core is proposed. It canachieve selective counteract or supplement to the different special bandwidths’ SPL. Thespeech intelligibility adaptive active control model is established in MATLAB/Simulink. Dothe active control simulation on the interior speech intelligibility and sound qualityimprovement using interior active control system with the working condition of100km/h.To improve interior speech intelligibility, the target is to enable the objective evaluatingmodel reach optimal active control level which can effectively reduce the noise SPL andincrease the speech intelligibility index by14.3%. To improve the interior sound quality, thetarget is enable the objective evaluating model’s score reach the optimal strategy which canmake better sound quality comprehensive performance with improvement rate of8.93%.
Finally, an adaptive active controller with proprietary intelligent property of the speechintelligibility is developed and the relative control program is written and the adaptiveactive control system of speech intelligibility is constructed. Do the real vehicle noisetesting in the working condition of60km/h,80km/h and120km/h, and analyze thedifference between the interior SPL before and after control. The adaptive active controlsystem of speech intelligibility is aimed to improve the performance of speech intelligibilitywhich can reduced the value of loudness with maximum reduction of7.14sones andenhance speech intelligibility with the maximum improvement rate of17.05%; the system isaimed to effectively improve the score of sound quality objective evaluation model whichcan achieve the biggest improvement rate of14.48%. Besides, the interior speechintelligibility index was also increased by14.96%. The satisfied test results can present that the proposed algorithm and corresponding control system is not only effective but also canachieve improvement in interior sound quality.
引文
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