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Time-Domain Source Contribution Analysis Method for In-Room Pass-By Noise

机译:室内通用噪声的时域源贡献分析方法

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This paper presents a new time-domain source contribution analysis method for in-room pass-by noise. The core of the method is a frequency-domain ASQ model (Airborne Source Quantification) representing each noise generating component (engine, exhaust, left and right tyres, etc.) by a number of acoustic sources. The ASQ model requires the measurement of local FRF's and acoustic noise transfer functions to identify the operational loads from nearby pressure indicator responses and propagate the loads to the various target microphones on the sides of the vehicle. Once a good ASQ model is obtained, FIR filters are constructed, allowing a time-domain synthesis of the various source contributions to each target microphone. The synthesized target response signals are finally recombined into a pass-by sound by taking into account the speed profile of the vehicle. This allows several useful analyses such as: i) analysis and ranking of the source contributions during a pass-by, ii) comparison of the summed path contributions with the measurement data, iii) in-depth time and frequency analyses, iv) auralization and sound quality evaluations. A large in-room test campaign was carried out to validate the proposed method. The tests were performed on a passenger car in a chassis dyno semianechoic room. Several operational tests were conducted including run-up, coast-down and constant speed experiments in different throttles and gears, tests on smooth and tarmac road profiles, measurements with the powertrain switched off and tests according to the ISO 362 standard (2007). A reduced ASQ model was utilized shortening the total measurement time. The test results were very satisfying, exposing physically realistic source contributions and a sound quality accurate synthesis up to 8 kHz.
机译:本文介绍了用于室内通过噪声的新时域源贡献分析方法。该方法的核心是频域ASQ模型(空气源量化),其表示每个声源的每个噪声产生部件(发动机,排气,左和右转轮等)。 ASQ模型需要测量本地FRF和声噪声传递的功能,以从附近的压力指示器响应识别操作负载,并将负载传播到车辆侧面的各种目标麦克风。一旦获得了良好的ASQ模型,构造了FIR滤波器,允许对每个目标麦克风的各种源贡献的时域合成。通过考虑车辆的速度轮廓,最终将合成的目标响应信号重新组合成通过声音。这允许几种有用的分析如:i)在通过,ii)在对测量数据,III)的总和分析,IV)Auratization,IV)Auratization和Source Actizes,IV)Auratization和IV)的分析和排序源分析音质评估。进行了一个大型的室内测试活动以验证提出的方法。测试是在底盘赛道半思纪古董室的乘用车上进行。进行了几种操作试验,包括在不同节流阀和齿轮中的加速,海岸下降和恒定的速度实验,在光滑和柏油路路型材上测试,动力总成的测量根据ISO 362标准关闭和测试(2007)。使用缩小的ASQ模型缩短了总测量时间。测试结果非常令人满意,暴露了物理上现实的源贡献和高达8 kHz的声音质量合成。

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