Noise reduction mechanism of high-speed railway box-girder bridges installed with MTMDs on top plate

The issue of low-frequency structural noise radiated from high-speed railway(HSR) box-girder bridges(BGBs) is a significant challenge worldwide. Although it is known that vibrations in BGBs caused by moving trains can be reduced by installing multiple tuned mass dampers(MTMDs) on the top plate, there is limited research on the noise reduction achieved by this method. This study aims to investigate the noise reduction mechanism of BGBs installed with MTMDs on the top plate. A sound radiation prediction model for the BGB installed with MTMDs is developed, based on the vehicle–track–bridge coupled dynamics and acoustics boundary element method. After being verified by field tested results, the prediction model is employed to study the reduction of vibration and noise of BGBs caused by the MTMDs. It is found that installing MTMDs on top plate can significantly affect the vibration distribution and sound radiation law of BGBs. However, its impact on the sound radiation caused by vibrations dominated by the global modes of BGBs is minimal. The noise reduction achieved by MTMDs is mainly through changing the acoustic radiation contributions of each plate of the bridge. In the lower frequency range, the noise reduction of BGB caused by MTMDs can be more effective if the installation of MTMDs can modify the vibration frequency and distribution of the BGB to avoid the influence of small vibrations and disperse the sound radiation from each plate.

Evaluation of Diesel Engine Noise Reduction Measures Based on Hierarchy Diagnosis

Effect of different noise reduction measures for diesel engines was evaluated based on hierarchy diagnosis. The hierarchy diagnosis chart and hierarchy judgment matrix were given. Through evaluation of noise reduction measures, the main strategies of noise reduction were found. The result shows that the noise reduction level of different frequency belts varies from measure to measure. The reduction capacity of different measures could not add simply, which relates to the problem of parameter matching.

Flap side-edge noise mechanism and shape modification noise reduction design

Flap side-edge noise is a significant noise source for airplane at takeoff and landing stages. The generation mechanism of flap side-edge noise is analyzed by numerical simulation on unsteady flow field using Very Large Eddy Simulation （VLES）. Two kinds of flap side-edge shape modifications are proposed, and their frequency spectrum and directivity of far-field noise are compared with the baseline configuration using permeable integral surface Ffowcs Williams and Hawkings （FW-H） acoustic analogy method to investigate their effects on noise reduction. Via the numerical simulation of flow field and acoustic field, it proves that the flap side-edge noise is broadband noise in nature. The different shapes of flap side-edge change the pattern of flow field, vortex structures and the development of vortex, thus having influences on noise source distributions and characteristics of far-field noise. The result shows that at the given 5° angle of attack, the proposed flap side-edge shape modifications can reduce the overall sound pressure level （OASPL） by 1 to 2 dB without decreasing the lift and drag aerodynamic performances.

Jet Noise Reduction of Double-Mixing Exhaust System

A jet noise reduction technique by using the external chevron nozzle with lobed mixer in the double-mixing exhaust system is investigated under cold conditions.The computations of jet field and the experiments of noise field are conducted with scaled model of high-bypass-ratio turbofan engine mixing exhaust system composed of external chevron nozzle with lobed mixer.The computational results indicate that comparing with the baseline nozzle with lobed mixer,the external chevron nozzle with lobed mixer increases mixing of jet and ambient air near the nozzle exit.The experimental results show that the external chevron nozzle with lobed mixer has better jet noise reduction at low frequencies,and this reduction rises with the increase of chevron bend angle.The experimental results also show that the external chevron nozzle with lobed mixer has sound pressure level(SPL)increase which is not obvious at high frequencies.With chevron bend angle increasing,SPL has relatively marked increase at 60°(directivity angle measured from upstream jet axis)and little fluctuations at 90°and 150°.The external chevron nozzle with lobed mixer has overall sound pressure level(OASPL)reduction in varying degrees at 60°and 150°,but it has little OASPL increase at 90°.

Automotive Interior Noise Reduction in High Frequency Using Statistical Energy Analysis

Statistical energy analysis (SEA) is an effective method for predicting high frequency vibro-acoustic performance of automobiles. A full vehicle SEA model is presented for interior noise reduction. It is composed of a number of subsystems based on a 3D model with all parameters for each subsystem. The excitation inputs are measured through road tests in different conditions,including inputs from the engine vibration and the sound pressure of the engine bay. The accuracy in high frequency of SEA model is validated,by comparing the analysis results with the testing pressure level data at driver's right ear. Noise contribution and sensitivity of key subsystems are analyzed. Finally,the effectiveness of noise reduction is verified. Based on the SEA model,an approach combining test and simulation is proposed for the noise vibration and harshness (NVH) design in vehicle development. It contains building the SEA model,testing for subsystem parameter identification,validating the simulation model,identifying subsystem power inputs,analyzing the design sensitivity. An example is given to demonstrate the interior noise reduction in high frequency.

Numerical analysis of broadband noise reduction with wavy leading edge

Large Eddy Simulation（LES） is performed to investigate the airfoil broadband noise reduction with wavy leading edge under anisotropic incoming turbulence. The anisotropic incoming turbulence is generated by a rod with a diameter of 10 mm. The incoming flow velocity is 40 m/s and the corresponding Reynolds numbers based on airfoil chord and rod diameter are about 397000 and 26000, respectively. The far-field acoustic field is predicted using an acoustic analogy method which has been validated by the experiment. A straight leading edge airfoil and a wavy leading edge airfoil are simulated. The results show that wavy leading edge increases the airfoil lift and drag whereas the lift and drag fluctuations are substantially reduced. In addition, wavy leading edge can significantly change the flow pattern around the leading edge and a pair of counter-rotating streamwise vortices stemming from each wavy leading edge peak are observed.An averaged noise reduction of 9.5 dB is observed with the wavy leading edge at the azimuthal angle of 90°. Moreover, the wavy leading edge can mitigate noise radiation at all the azimuthal angles without significantly changing the noise directivity. The underlying noise reduction mechanisms are then analyzed in detail.

An improved noise reduction transformation for algorithm based on wavelet MEMS gyroscope

To solve the large noise problem for the low- precision gyroscopes in micro-electro mechanical systems （MEMS） of inertial navigation system, an improved noise reduction method, based on the analyses of the fast Fourier transformation （FFT） noise reduction principle and the simple wavelet noise reduction principle, was proposed. Furthermore, the FFT noise reduction method, the simple wavelet noise reduction method and the improved noise reduction method were comparatively analyzed and experimentally verified in the case of the constant rate and dynamic rate. The experimental analysis results showed that the improved noise reduction method had a very good result in the noise reduction of the gyroscope data at different fi：equencies, and its performance was superior to those of the FFT noise reduction method and the simple wavelet noise reduction method.

Utilization of Whale-inspired Leading-edge Tubercles for Airfoil Noise Reduction

Numerical studies are conducted to explore the noise reduction effect of leading-edge tubercles inspired by humpback whale flippers.Large eddy simulations are performed to solve the flow field,while the acoustic analogy theory is used for noise prediction.In this paper,a baseline airfoil with a straight leading-edge and three bionic airfoils with tubercled leading-edges are simulated.The tubercles have sinusoidal profiles and the profiles are determined by the tubercle wavelength and amplitude.The tubercles used in this study have a fixed wavelength of 0.1c with three different amplitudes of 0.1c,0.15c and 0.2c,where c is the mean chord of the airfoil.The freestream velocity is set to 40 m/s and the chord based Reynolds number is 400,000.The predicted flow field and acoustic field of the baseline airfoil are compared against the experiments and good agreements are found.A considerable noise reduction level is achieved by the leading-edge tubercles and the tubercle with larger amplitude can obtain better noise reduction.The underlying flow mechanisms responsible for the noise reduction are analyzed in detail.

基于多层级注意力机制和动态阈值的远程监督关系抽取

远程监督关系抽取面临着数据质量的问题,即生成的数据集存在多类噪声,包括噪声词、噪声句和噪声包。现有研究主要集中在噪声句方面,忽略了其他噪声的影响,无法彻底消除噪声。为此,提出一种基于多层级注意力机制和动态阈值的远程监督关系抽取模型(MADT)。该模型首先采用预训练语言模型获取实体对语义表示,再通过双向门控循环单元和自注意力机制获得蕴涵关键词信息的语义特征,然后结合句子深层上下文表示依次处理三种噪声问题。此外,还提出一种动态阈值方法进一步剔除噪声句,增强正例句对包表示的贡献,并采用基于语义相似性的注意力机制降低噪声包的影响。在NYT10d和NYT10m数据集上的实验表明,MADT模型能够解决远程监督关系抽取中各个层面的噪声,有效提升关系的抽取性能。

基于深度学习优化的图像高质量动态降噪算法

电子设备采集图像会受到光照、湿度等因素影响,从而产生噪声污染,影响图像的视觉效果.本研究以残差网络深度学习模型为基础,融合注意力机制构建图像动态降噪方法,采用深度可分离残差网络模型取代传统CNN网络来进行图像去噪的特征提取,同时在残差网络模型中加入了非局部注意力模块和通道注意力模块来优化去噪中的特征提取任务.实验结果表明,构建的模型参数具备更好的图像降噪特征提取效果,其PSNR(Peak Signal-to-Noise Ratio,PSNR)值最大为28.88.同时在不同的数据集性能测试中,AD-ResNet降噪模型在高斯噪声的处理中最高峰值信噪比为27.32,最高结构相似度为0.7826;而在泊松噪声处理中,最高峰值信噪比为26.61,最高结构相似度为0.7374.本文方法实现了高精确率和高效率图像降噪,具备有效的图像降噪处理性能.

基于灰色关联度法的发动机噪声影响因素及降噪研究

随着汽车工业的蓬勃发展,汽车噪声严重影响着人们的日常生活,汽车产生的噪声包括发动机噪声、传动系统噪声、风扇噪声以及排气系统噪声,其中发动机噪声是汽车噪声的主要来源,引起国内外学者的广泛研究。文章运用灰色关联度法对发动机噪声影响因素(转速、高度、水平距离)进行计算,得出相应关联系数与关联度,由此得出发动机噪声影响因素的主次程度,并针对主要影响因素进行降噪方法研究。

密封端面声发射信号降噪处理技术研究

针对利用声发射技术监测密封端面摩擦状态,受到轴承、电机等部件摩擦产生背景噪声对密封端面摩擦信号的干扰,导致获取密封端面声发射信号信噪比不高的问题,文章提出的基于经验小波变换和相对熵(EWT-KLD)的滤波降噪方法,对采集到的原始信号进行滤波降噪处理,以提高密封端面摩擦产生声发射信号的信噪比。通过试验验证,该方法可适用于不同工况、不同介质、不同摩擦状态的声发射信号进行降噪,提高50 kHz以上声发射信号的信噪比,尤其是密封端面微弱摩擦产生信号的信噪比,有效地提高了密封端面摩擦声发射检测的精度和灵敏度,对于早期密封端面摩擦监测的作用尤为明显,使得密封端面摩擦状态累积变化过程的监测更准确。

基于DBO-DA-GRU的大坝变形预测模型

针对大坝变形数据中存在噪声干扰、常规深度学习预测模型关键信息挖掘能力较弱且难以确定最优参数等问题,首先采用变分模态分解(VMD)联合小波阈值降噪方法对监测数据进行处理;然后利用基于双重注意力机制的门控循环单元(DA-GRU)对降噪后的变形数据进行预测,并引入蜣螂优化算法(DBO)对模型参数进行寻优,从而构建了基于DBO-DA-GRU的大坝变形预测模型;最后以某拱坝实测变形数据为例,验证了DBO-DA-GRU较BP、GRU、DBO-GRU模型的预测精度更高、稳健性更好,可为大坝变形安全监控提供一定参考价值。

超音速气动喷雾技术噪声特性及致噪机理研究

超音速气动喷雾降尘是一种新型的微米级雾滴高效捕尘技术,在呼吸性粉尘治理方面效果良好,但造成的严重噪声污染不可忽视。为探究其噪声特性及致噪机理,研究采用试验的方法,利用YSD130噪声分析仪对超音速同轴雾化降尘装置噪声展开测定,通过对比不同工况下声源处气流噪声与喷雾噪声,分析其在不同压力、水流量下的频谱特性及变化规律。研究显示:超音速动力喷雾噪声以高频噪声为主,随着频率的增加,声压级增加,其噪声均值为110.1 dB,会造成人的听力系统受损。不完全的雾化会导致低频段(<500 Hz)的声压级增加,长期接触易引发神经衰弱、失眠、头疼等症状;更高效的雾化会导致中高频段(≥500 Hz)的声压级增加,长期暴露于该环境易引发声带疲劳、声带炎症等症状。在相同水流量下,随着压力的增大,超音速气动喷雾噪声的声压级呈先增大后减小的趋势。在相同压力下,随着水流量的增加,不同频段的声压级呈先增大后减小的趋势。气流能量降低和层间相对速度下降是噪声强度降低的主要原因。水流量为60 mL/min,气动压力为0.4 MPa时,噪声各项参数最大。研究结果丰富了气动喷雾噪声理论,可为超音速气动喷雾装置结构优化、噪声防治技术装备的研发提供理论支持。

某V型发动机降噪件噪声验证

文章通过对特定型号发动机的两个在发动机运行中产生较大噪声机械部件:前端盖板以及左缸罩盖的结构以及材料进行优化处理,即将前端盖板以及左缸罩盖的材料ZL106/108更换为6061铝合金材料,同时在前端盖板以及左缸罩盖的结构上加设加强筋条,使其平面模态达到3000Hz,之后采用工程九点噪声验证来验证整体噪声,前端面噪声以及左侧噪声的降幅值,有效地降低了该型号发动机的整机噪声,前端面噪声以及左侧噪声,满足了开发要求。

密级配橡胶沥青路面降噪技术原理与研究综述

密级配橡胶沥青路面是低噪声路面发展的新形式。为了推动低噪声路面的发展,阐述了轮胎/路面噪声的产生、增强机理及密级配橡胶沥青路面的降噪机理和降噪效果。首先介绍大孔隙和密级配两种类型降噪沥青路面及其降噪机理,然后对轮胎/路面噪声的产生和增强机制进行论述,接着针对密级配降噪沥青路面降噪模式、胎路噪声的影响因素及检测方法进行重点评述,最后对密级配低噪声沥青路面的发展及优化方向进行展望。大多数低噪声沥青路面都偏向于开级配大孔隙类型,对密级配沥青路面的降噪机理及实现路径研究较少。开级配大孔隙沥青路面在孔隙堵塞时,其降噪效果急剧下降,并且堵塞的孔隙难以恢复,这制约了其广泛使用。而密级配橡胶沥青路面通常依靠自身丰富的表面纹理及橡胶颗粒的弹性实现吸声阻尼降噪,故不存在上述不足。密级配橡胶沥青路面虽在降噪效果方面不如开级配大孔隙路面,但因其优异的路用性能和持久稳定的降噪效果,已成为低噪声路面在实际工程应用中的重要选择。为了更好应用密级配橡胶降噪沥青路面,未来应重点研究影响其降噪效果的诸多重要因素,如橡胶颗粒的掺入方式、粒径和掺量等。

粉煤灰陶粒轻质混凝土声屏障性能试验研究

混凝土是一种应用广泛、可使用多种固废制备的建筑材料。本研究将粉煤灰陶粒作为轻骨料,水泥-粉煤灰-硅灰-煤系偏高岭土作为复合胶凝材料,制备用作声屏障的粉煤灰陶粒轻质混凝土,并对其力学性能、吸声性能和抗碳化性能进行试验研究。结果表明:当粉煤灰-硅灰-煤系偏高岭土总掺量为胶凝材料总质量的10%时,试样的力学性能、抗碳化性能有所提高,吸声性能有所降低;随着粉煤灰-硅灰-煤系偏高岭土掺量进一步增加,试样的力学性能、抗碳化性能有所降低,吸声性能有所提高。1500 Hz及以下频率吸声系数变化幅度较小,2000 Hz时吸声效果最好,试样的平均吸声系数在0.44~0.58,降噪系数在0.74~0.89。

声学黑洞在减振降噪中的研究进展

声学黑洞结构作为一种轻质、高效、宽频弹性波调控手段,在减振降噪领域具备广阔的应用前景。本文基于声学黑洞效应,以轻质高效宽频减振降噪材料用于解决工程声振问题为目的,介绍了单层/双层声学黑洞梁和附加声学黑洞吸振梁、声学黑洞压痕板和内雕板、声学黑洞圆柱壳,以及声学黑洞管道减振降噪的研究进展。结合当前声学黑洞减振降噪研究和应用过程中存在的不足,对声学黑洞减振降噪领域存在的问题和未来的研究方向进行预判,为声学黑洞减振降噪研究和应用提供一些参考。

结合自注意力机制和软阈值降噪的对比联邦学习特征聚合算法

传统人工智能(artificial intelligence,AI)技术在智慧视觉领域的应用面临着数据异构分布、数据隐私保护和噪声数据干扰等一系列技术难点。为了克服这些挑战,在联邦学习和信号降噪算法的思想上,提出了一种基于降噪和数据特征聚合的对比联邦学习算法(comparative federated learning aggregation feature algorithm with noise reduction,FedCAFNR)。FedCAFNR引入自注意力机制和深度残差网络,构建自适应阈值降噪网络,提高联邦学习从异构性数据中学习关键特征的能力。通过对比学习模型之间的差异,提升局部训练精度,有效增强了个体与全局模型的一致性,进一步提高了模型对非独立同分布数据的鲁棒性。采用3种多分类数据集进行仿真实验,在数据隐私保护的前提下证明了FedCAFNR算法具有良好的收敛性和可拓展性。此外,新算法改进了学习效率,并提高了异构数据环境下联邦学习现有算法的一致性、鲁棒性。

电梯噪声成因分析及降噪措施

电梯作为现代建筑中不可或缺的一部分,已经深入到人们的生活之中。然而,随着电梯使用频率的增加,电梯运行过程中的噪声问题日益凸显,不仅影响乘客的舒适度,还可能对人们的心理健康造成不良影响。因此,对电梯噪声的成因进行深入研究,并提出相应的降噪措施,具有重要的现实意义和应用价值。该文分析电梯噪声的成因,并针对不同的噪声来源提出有效的降噪措施。通过对这些噪声源的深入研究,我们可以更好地理解电梯噪声的产生机制,为后续的降噪措施提供理论依据。