采用生理响度感知机制的车内噪声声品质预测

现有车内噪声声品质预测的响度计算中没有考虑真实人耳生理解剖结构的传声特性,因此提出了一种基于生理响度感知模型的车内噪声声品质预估方法。首先,采集两款轿车的车内噪声样本,并通过主观评价试验得到车内噪声的主观评价烦恼度。之后,整合中耳集总参数模型与耳蜗传输线模型,构建生理响度模型。然后,以生理响度模型的响度计算值为主要参数,结合尖锐度、粗糙度与车内噪声的主观评价值,通过TabNet模型构建了车辆声品质预测模型。最终,对比分析了所构建声品质模型与基于现有标准响度模型所构建的声品质模型的预测效果。结果表明,采用生理响度模型的声品质预测平均误差百分比仅有4.73%,优于采用Moore响度(6.13%)与Zwicker响度(6.94%)的声品质预测结果。此外,所构建的TabNet声品质预测模型的平均误差百分比也低于基于BP神经网络模型的平均误差百分比(7.60%)。采用生理响度模型的TabNet声品质预测能够提高车内噪声声品质客观评价的准确率。     

利用卷积网络的高速列车主观声品质预测

随着高速列车在中国的高速发展,乘客对舒适性的要求不断提高。因此高速列车内声学舒适性是一个需要研究和解决的问题。首先,该文基于声学人工头设备,获取了高速列车行驶在350 km/h速度下不同车厢、不同区域的双耳噪声样本,并对其分别开展了主观声学评价和基于响度、尖锐度、粗糙度和抖动度等参数的客观声品质分析。结果表明,350 km/h速度下高速列车车内噪声能量集中在3000 Hz以内,风挡区域是舒适性评价较差的位置,而响度是影响主观评价最大的因素。其次,利用卷积神经网络算法将主观评价结果与高速列车噪声样本相关联,建立了车内噪声主观声品质预测模型,并与基于BP神经网络的预测模型进行了对比。结果表明,基于卷积神经网络的主观声品质预测模型具有更高的预测精度,更适宜用于指导高速列车车内声学舒适性的优化设计。     

空调压缩机噪声测试及其声品质客观参量分析*

针对空调压缩机辐射声场的不同场点噪声声品质的差异,采用心理学声品质参量即响度、尖锐度、总感觉噪度,对压缩机辐射声场的不同场点噪声进行声品质客观参量分析,研究压缩机场点噪声声品质客观参量值变化规律。通过特征响度研究各场点噪声响度在频域的分布,并得出压缩机各场点噪声特征响度峰值所在噪声频带。实验结果表明,对于处在压缩机不同方向上的场点,其噪声声品质客观参量值存在明显差异,但其噪声特征响度峰值却处在相同的噪声频带。研究工作为压缩机全方向降噪提供参考依据也为研究压缩机的噪声声品质探索了一种新思路。     

车内某高频噪声的分析和优化控制

针对某柴油皮卡车型在急加油门时出现的高频噪声,利用声学滤波技术确定其噪声能量主要分布在9000～1400 Hz频段。采用近场声学测试、声振频谱分析等方法锁定噪声源来自废气再循环冷却器。通过理论分析和计算流体动力学数值仿真技术,研究了该废气再循环冷却器波纹管处介质流场情况,流场的不均匀性和大涡流是辐射高频噪声的主要原因。仿真分析显示优化设计后该高频噪声得到明显改善,最后通过整车实验验证,结果显示优化效果良好。     

典型城市地铁站台噪声满意度*

地铁是城市轨道交通重要组成部分,地铁站台噪声对乘客身心健康有重要影响。以合肥轨道交通一号线为例,具体选择地下侧式、地下双岛式和地下岛式3个典型空间类型的地铁站台为研究对象,通过噪声测量和问卷调查相结合的方法,针对地铁在不同运营时段的乘客站台噪声满意度与噪声声元素舒适度进行评价,探讨性别、声元素舒适度以及站台噪声对乘客噪声满意度的影响。结果表明：对地铁站台噪声满意度评价,乘客性别差异不显著;在乘车高峰期时段,地铁站台广播提示声、地铁工作人员吹哨声、列车进站声和列车出站声是影响乘客站台噪声满意度主观评价的主要噪声声元素;乘客噪声满意度主观评价与站台噪声值呈强负相关,噪声值越高,满意度越低;乘客噪声满意度为可接受时的地铁站台噪声阈值,在乘车高峰期时段为74 dB(A),非高峰期时段为67 dB(A)。该文工作可为城市地铁站台噪声满意度评价及其空间结构设计提供科学参考。     

汽车车内噪声主动控制系统仿真

摘要：降低汽车空腔的振动,是抑制汽车车内噪声的有效途径之一。以激振器、作动器和控制器等为主要部件,搭建了简化的汽车车内噪声主动控制系统,该系统通过将汽车空腔模型简化为板件,以减弱板件振动为目标,实现了汽车车内噪声主动控制。采用简谐正弦及余弦信号作为激振器发出的激励,用于模拟板件的初始振动,控制器通过采用模糊控制算法直接控制压电陶瓷作动器的振动,压电陶瓷作动器的振动用于抑制板件的振动,完成了汽车车内噪声主动控制系统仿真。仿真结果表明,研究采用的汽车车内噪声主动控制系统,使汽车空腔振动降低23%,为解决由汽车发动机和动力总成的振动所引发的汽车车内噪声问题提供了一个有效途径。     

大学物理探究式教学

在一些大学里,物理教学的方式还是传统的填鸭式,这不利于对学生创新能力和自主性学习的培养。本文首先介绍一下探究式教学以及探究式教学的意义,再从其他的几个方面详细的阐述探究式教学的具体实施措施。     

节气门全开工况下的车内轰鸣噪声预测*

采用内燃机多体动力学理论提取了某四缸汽油机的燃烧激励和惯性激励,将其加载到某车型的整车有限元模型上预测节气门全开工况下的车内噪声。通过仿真与实验的对比,发现仿真声压级曲线的变化趋势与实验基本一致,并且较好地捕捉到了3300～3700 r/min转速段内的轰鸣噪声,证明了仿真结果的可靠性,为整车开发阶段的节气门全开工况NVH性能预测提供技术参考。     

一种吸油烟机声品质满意度分级限值评定方法

声品质作为一种描述吸油烟机噪声听觉感知特性的手段已经被行业所接受,团体标准T/CAS 341–2019《吸油烟机噪声声品质测试方法》给出了吸油烟机声品质测试与建模方法,同时通过声品质指数给出了声品质的数值化表达.该标准为各厂商定量描述声品质提供了依据,但目前仍缺乏对产品声品质满意度级别的划分方法,这不利于声品质技术的推...     

The identification of tyre induced vehicle interior noise

Sound transmission into a vehicle is classified as either airborne or structure borne sound. From the point view of noise control, the reduction of noise transferred by different paths requires different solutions. Coherence function analysis is often used to identify transmission paths. However it can be difficult to separate the airborne from structure borne components. The principle of acoustic reciprocity offers a convenient method for overcoming this difficulty. The principal states that the transfer function between an acoustic volume velocity source and an acoustic receiver is independent of a reversal of the position of source and receiver. The work done on this study involves exciting a stationary tyre and measuring the surface velocity of the tyre at a number of discrete points. The acoustic transfer functions between each point on the tyre and a receiver point are measured reciprocally. Two sets of measurements are then combined to yield a measure of the sound pressure due to a point force on the tyre via the acoustic transmission path only. This technique also provides information on the relative contributions of various regions of the tyre wall to the resultant noise. Also the sound radiation characteristics, the horn effect, and resonance at the wheel housing are identified through the reciprocal measurement.     

Sound quality prediction of vehicle interior noise using deep belief networks

The sound quality of vehicle interior noise strongly influences passengers’ psychological and physiological perceptions. To predict the sound quality of interior noise, a vehicle road test with four compact cars has been conducted. All recorded interior noise signals have been denoised via a discrete wavelet transform (DWT) denoising procedure and subsequently evaluated subjectively through the anchor semantic differential (ASD) test by a jury. In addition, a novel prediction method, namely, regression-based deep belief networks (DBNs), which substitute the support vector regression (SVR) layer for the linear softmax classification layer at the top of the general DBN’s structure, has been proposed to predict the interior sound quality. The parameter selection of the DBN model has been compared and studied using a grid search. In addition, four conventional machine-learning-based methods have been introduced to enable a comparison of the performance with the newly developed DBNs. Furthermore, the feature fusion ability of DBNs has been studied by varying the amount of information that the dataset offers. The results show the following: (1) The accuracy and robustness of the proposed DBN-based sound quality prediction approach are better than those of the 4 other referenced methods. (2) The multiple-feature fusing process can strongly affect the prediction performance. (3) Finally, the unsupervised pre-training process of the DBNs can enhance the information fusing ability. Finally, the newly proposed regression-based DBN approach may be extended to address other vehicle noises in the future.     

A modified tonality and its application to objective evaluation of laser printers noise

Noise in a laser printer is affected by many components, such as spring force, spring constant, and friction coefficient. Objective evaluation of pick up noise is difficult because of background noises, such as operating sound. In particular, pick up noise generated between the friction pad and paper in the process of printing has become an essential aspect of quality evaluation. However, the existing criteria for evaluating pick-up noise have solely relied on subjective human judgments; therefore, there is a need to objectify these criteria. In this paper, the noise index for determining the existence of pick-up noise is established using a modified tonality at just noticeable sound level limit. The study has investigated factors that cause pick-up noise and suggests the substitution of printer components that determine spring constants, spring force, and the quality of friction pads. The proposed noise index is successfully applied to classifying the pick-up noise and mitigating the noise through the optimized design combination of laser printer components.     

The impact of urban noise on primary schools. Perceptive evaluation and objective assessment

This paper aims to assess the impact of environmental noise in the vicinity of primary schools and to analyze its influence in the workplace and in student performance through perceptions and objective evaluation. The subjective evaluation consisted of the application of questionnaires to students and teachers, and the objective assessment consisted of measuring in situ noise levels. The survey covered nine classes located in three primary schools. Statistical Package for Social Sciences was used for data processing and to draw conclusions. Additionally, the relationship of the difference between environmental and background noise levels of each classroom and students with difficulties in hearing the teacher’s voice was examined. Noise levels in front of the school, the schoolyard, and the most noise-exposed classrooms (occupied and unoccupied) were measured. Indoor noise levels were much higher than World Health Organization (WHO) recommended values: L_Aeq,30min averaged 70.5 dB(A) in occupied classrooms, and 38.6 dB(A) in unoccupied ones. Measurements of indoor and outdoor noise suggest that noise from the outside (road, schoolyard) affects the background noise level in classrooms but in varying degrees. It was concluded that the façades most exposed to road traffic noise are subjected to values higher than 55.0 dB(A), and noise levels inside the classrooms are mainly due to the schoolyard, students, and the road traffic. The difference between background (L_A95,30min) and the equivalent noise levels (L_Aeq,30min) in occupied classrooms was 19.2 dB(A), which shows that students’ activities are a significant source of classroom noise.     

发展性评价在大学物理实验教学中的应用

针对当前大学物理实验评价中存在的问题,建议在实验教学中引入发展性评价,提出了两种具体实施模式.模式一采用在平时实验中学生自评、同伴评价与教师评价相结合的方式,模式二采用在操作考试中将工作单和观察法相结合的方式,并进行了对比试验.试验结果表明,发展性评价较有效地改善了实验效果.     

Low-frequency characteristics of vehicle interior sound fields

Good-quality sound reproduction requires a flat frequency response at the listening position. In a very small listening space, such as a vehicle interior, reflected wave introduce significant variation in the frequency response. Experimental results and a simple model are presented.