基于蜗舌改型的空调用离心风机流动分析及降噪研究

本文采用计算流体动力学和声类比相结合的混合方法对空调用离心风机进行流场以及声场的计算,同时进行风机风量和噪声的实验测量,验证所采用的数值计算模型和计算方法的有效性.针对原型非常规蜗壳,提取蜗壳中间截面型线进行直蜗舌的蜗壳设计,在此基础上设计了三种倾斜蜗舌的蜗壳.根据数值计算结果,对最优倾斜蜗舌进行了实验验证。经实验测试,风机在各个工况点风量均有提升,在最大风量点风量提升6.0%,噪声降低1.4 dB(A).数值分析风机内部流动特征及噪声特性,发现在蜗舌附近流动区域内湍流强度和涡量明显减小,在叶片通过频率处声功率谱密度以及噪声峰值明显下降,这也表明风机的旋转噪声得到了有效控制。     

An investigation into the noise generation of CPAP devices: Experimental and numerical study

Continuous positive airway pressure (CPAP) devices are popularly used for obstructive sleep apnoea (OSA) treatment. However, the noise level emission from these devices has been identified as a potential factor for patient’s discomfort and rejection. There is a need to obtain information on the noise characteristics and source locations in order to tackle the most serious noise source within these devices. A typical CPAP device was used for the investigation and its sound characteristics and sound power levels were determined. The noise generated from a centrifugal fan was also independently investigated to address its contribution to the overall noise of the device. Frequency analysis suggested that the noise generated from both the CPAP device and the fan is broadband in nature with discrete peaks containing rotational and non-rotational components. The broadband components were then studied in detail using numerical simulation approach. Computational aeroacoustics (CAA) method with hybrid approach was used to a three-dimensional (3-D) CPAP fluid model to predict the aerodynamic and aeroacoustics behaviours of the device. This showed a complicated flow structure involving flow separation, rotation, and vortices in several locations which resulted in high level of flow turbulence inside the device. The turbulent components were used to estimate the broadband noise level at source using the broadband noise source (BNS) models. It shows the most critical location is at the fan region and at the fan inlet.     

Experimental and numerical studies on the discrete noise about the cross-flow fan with block-shifted impellers

The experimental and numerical studies have been carried out to investigate the blade passage frequency (BPF) noise of a cross-flow fan (CFF) with the block-shifted impeller. Firstly, the aeroacoustic and aerodynamic features about the five different block-shifted impellers have been obtained experimentally. Secondly, the dynamic pressure sensors were put in the noise generating surfaces to investigate the pressure fluctuations generated by the shifted blocks in the near-field through the cross-correlation analysis. Thirdly, the two-dimensional (2D) unsteady flow field has been simulated by commercial CFD software and the vortex flow patterns and the unsteady force of the blade have been analyzed to detect the noise source about the CFF. Finally, the noise properties about the CFF were predicted by a hybrid method through the Farassat’s equation and the surface pressure fluctuations were provided by the CFD simulations. A simplified theory model has also been built up at the same time. The comparisons are made between the results of hybrid method and the theory model to validate the correctness of the noise prediction methods. The accuracy of these results was also evaluated by the corresponding experimental ones. The results indicate that the impellers with different block-shifted angles are the same in aerodynamic performance but different in the BPF noise. The relations between the shifted angles and the BPF noise levels have been predicted and discussed for the noise reduction.     

开式轴流风扇气动噪声预测

本文采用LES/FW-H的匹配方法,研究了开式轴流风扇内部旋涡流动特征及其与叶片表面干涉引起的气动噪声之间的联系,同时进行了远场噪声预测,探讨了叶轮不同表面辐射噪声时的频谱分布特征.研究结果表明,开式轴流风扇吸力面附近形成的叶尖涡和前缘分离涡在吸力面叶片表面相应位置形成大压力波动,形成主要噪声源;叶片吸力面的辐射噪声可以通过改善吸力面附近的旋涡流动来降低;低速轴流叶轮由叶轮壁面辐射的噪声以宽频成分为主.     

Fan interaction noise reduction using a wake generator: experiments and computational aeroacoustics

A control grid (wake generator) aimed at reducing rotor-stator interaction modes in fan engines when mounted upstream of the rotor has been studied here. This device complements other active noise control systems currently proposed. The compressor model of the instrumented ONERA CERF-rig is used to simulate suitable conditions. The design of the grid is drafted out using semi-empirical models for wake and potential flow, and experimentally achieved. Cylindrical rods are able to generate a spinning mode of the same order and similar level as the interaction mode. Mounting the rods on a rotating ring allows for adjusting the phase of the control mode so that an 8 dB sound pressure level (SPL) reduction at the blade passing frequency is achieved when the two modes are out of phase. Experimental results are assessed by a numerical approach using computational fluid dynamics (CFD). A Reynolds averaged Navier-Stokes 2-D solver, developed at ONERA, is used to provide the unsteady force components on blades and vanes required for acoustics. The loading noise source term of the Ffowcs Williams and Hawkings equation is used to model the interaction noise between the sources, and an original coupling to a boundary element method (BEM) code is realized to take account of the inlet geometry effects on acoustic in-duct propagation. Calculations using the classical analytical the Green function of an infinite annular duct are also addressed. Simple formulations written in the frequency domain and expanded into modes are addressed and used to compute an in-duct interaction mode and to compare with the noise reduction obtained during the tests. A fairly good agreement between predicted and measured SPL is found when the inlet geometry effects are part of the solution (by coupling with the BEM). Furthermore, computed aerodynamic penalties due to the rods are found to be negligible. These results partly validate the computation chain and highlight the potential of the wake generator system proposed.     

电子器件散热风扇气动噪声管道声学模态截止控制技术

深度学习输入特征的选择直接影响其分类性能,为了进一步提高基于深度学习的鸟类物种识别模型的分类性能,该文提出一种多特征融合识别方法。该方法首先通过短时傅里叶变换、梅尔倒谱变换和线性调频小波变换分别计算得到鸣声信号的3种语图样本集,然后分别利用3种语图样本集训练3个基于VGG16迁移的单一特征模型,将3个模型的输出进行自适应加权求和实现融合,并修正了加权交叉熵函数以克服样本不平衡的问题,最后对语图进行分类实现鸟类物种的识别。以ICML4B鸣声库的35种鸟类为研究对象,对比了4种模型的平均识别准确率(MAP),结果表明特征融合模型较单一特征模型的MAP最大提高了0.307;选择输入语图的持续时间分别为100 ms、300 ms以及500 ms,对比不同持续时间下4种模型的测试MAP值,结果表明持续时间为300 ms时4种模型的MAP值均为最高;对比了不同信噪比下4种模型的识别效果,多特征融合模型的识别准确率随着信噪比的下降降低最少。说明在选择合适的语图持续时间后,该文提出的特征融合模型能得到更高的识别准确率,具有一定的抗噪能力,且训练参数少,更适合于少样本鸟类的识别。     

Numerical and experimental investigations of the unsteady aerodynamics and aero-acoustics characteristics of a backward curved blade centrifugal fan

A numerical study of the aerodynamic and aeroacoustic behaviors of a backward curved blade centrifugal fan was conducted under two important flow conditions: BEP and 1.3 × BEP. Three-dimensional numerical simulations of the complete unsteady flow field for the whole impeller-volute configuration were used to determine the aeroacoustic sources. To locate the unsteady flow and perturbations, the near field wall pressure fluctuations at different strategic points on the volute were computed using the URANS approach. Thus the intensities and positions of the aeroacoustic sources were identified by analyzing frequency spectra. The aeroacoustic sources caused by fluctuations in the interactions of the flows leaving the impeller and volute were close to the volute tongue, and the most effective noise sources related to the flow rate were near the impeller shrouds. In addition, the unsteady flow variables provided by CFD calculations were used as inputs in the Ffowcs Williams-Hawkings equation to estimate the noise tones of the fan. The aeroacoustic calculation results showed that the volute noise was much larger than the blade noise, and the noise mainly propagated from the outlet duct of the fan. Moreover, to account for the noise propagation, three calculation methods were used by applying different solid boundaries. Compared with the other methods, the FEM method, which accounted for the complex solid boundaries, produced good agreement and showed that the complex solid boundaries cannot be neglected in aeroacoustic predictions. The calculation results showed good agreement with the experimental results.     

Flow-induced noise in a suction nozzle with a centrifugal fan of a vacuum cleaner and its reduction

Noise reduction in a vacuum cleaner with a brush nozzle for cleaning a bed blanket is investigated numerically in fluid dynamic aspects. Governing equations describing nonlinear flow fields in a suction nozzle are solved simultaneously. The components of a rotary fan, a brush drum, and a separation block are installed in the nozzle. First, flow patterns in the nozzle are analyzed and based on them, flow resistance is evaluated to find a primary noise source. Flow resistance induces the loss of a suction performance as well as noise generation. In the brush nozzle, the separation block and the rotary fan obstruct smooth air flow and result in high level of noise emission. The rotation of the fan itself affects little noise generation. From the numerical results, a method to reduce noise and maintain the suction performance is suggested. In this method, the suction performance is increased through the optimization of the separation block, which is attained by the modification of its shape. And then, the height of a fan blade is shortened, leading to the performance loss. At the cost of it, the sound power level of noise is reduced by 4-5 dB(A) and at the same time, the tonal noise and the sound quality are improved appreciably. The method has been verified by experimental tests. It is found that in the brush nozzle, flow resistance is critical in noise emission and accordingly, fluid dynamic approach to noise reduction is effective.     

Measurements of aerodynamic noise and wake flow field in a cooling fan with winglets

The aerodynamic noise and the wake flow field in a cooling fan under actual operating conditions are studied with and without winglets on the fan blades. In order to understand the influence of the winglet, the aerodynamic noise and the wake velocity distribution are measured. The results indicated that overall noise level decreased and the noise spectrum was changed in a low frequency range when the winglet was installed. It was found from the flow visualization and PIV measurement that the influence of the winglet appeared in the traces of the tip vortices and the magnitude of vorticity was reduced in the near wake region, which suggest the observed reduction in aerodynamic noise     

Fast prediction of aerodynamic noise induced by the flow around a cylinder based on deep neural network

Accurate and fast prediction of aerodynamic noise has always been a research hotspot in fluid mechanics and aeroacoustics. The conventional prediction methods based on numerical simulation often demand huge computational resources, which are difficult to balance between accuracy and efficiency. Here, we present a data-driven deep neural network (DNN) method to realize fast aerodynamic noise prediction while maintaining accuracy. The proposed deep learning method can predict the spatial distributions of aerodynamic noise information under different working conditions. Based on the large eddy simulation turbulence model and the Ffowcs Williams-Hawkings acoustic analogy theory, a dataset composed of 1216 samples is established. With reference to the deep learning method, a DNN framework is proposed to map the relationship between spatial coordinates, inlet velocity and overall sound pressure level. The root-mean-square-errors of prediction are below 0.82 dB in the test dataset, and the directivity of aerodynamic noise predicted by the DNN framework are basically consistent with the numerical simulation. This work paves a novel way for fast prediction of aerodynamic noise with high accuracy and has application potential in acoustic field prediction.