高分子梯度溶液吸声机理的研究

制备了高分子均匀溶液和梯度溶液,并在声管中测试其声衰减性能.实验结果表明,高分子梯度溶液的声衰减效果明显优于(即大于)相应的均匀溶液的声衰减.根据连续分层介质中声波传播理论建立了计算高分子梯度溶液声衰减的数学模型.计算结果与实验结果一致.由实验和理论分析结果得出了高分子梯度溶液的梯度吸声机理,即多次反射、多次吸收,最终将声能转化为热能.     

Hybrid passive/active absorbers for flow ducts

A new type of acoustic liner developed for broadband noise reduction in flow ducts is considered in this paper. It combines passive absorbent properties of a porous layer and active control at its rear face. The complete design procedure of this hybrid passive/active liner is developed here. The passive part is first considered with the determination of a suitable porous material and the cut-off frequency separating the active low frequency regime from the passive high frequency one. The control system is then presented: a digital adaptive feedback control is performed independently cell by cell, allowing an easy subsequent increase of the liner surface. The entire optimization process has been successfully applied to a laboratory flow duct: both predictions and measurements show the interest of the hybrid liner to reduce the noise radiation.     

Sound field of a baffled sound source covered by an anisotropic rigid-porous material

A theoretical approach for the sound field of a piston sound source covered by a finite thickness layer of anisotropic rigid-porous material is presented. The formulation is an extension of the method worked out by Amedin et al. [Sound field of a baffled piston source covered by a porous medium layer. J Acoust Soc Am 1995;98(3):1757]. First, in the present study the sound field of a point source is described by cylindrical waves. Then, with the proper boundary conditions, the sound pressure radiated from a piston source covered by a layer of anisotropic porous material can be calculated. The effects of frequency and bulk density of material on the sound propagation in an anisotropic porous material are studied. Finally, the effect of anisotropy is discussed.     

基于DEMON线谱的轴频提取方法研究

目标的螺旋桨不同则轴频不相同。轴频是目标的特征之一,可以应用于目标识别当中。本文提出一种改进的高频噪声解调分析(DEMON)方法,能够得到具有明显线谱的DEMON谱;提出最大公约数算法,并给出提取轴频的具体步骤。海试数据实验结果验证了本文所提方法及算法的有效性和可行性。     

Pattern时延差编码四信道水声通信技术研究

本文所研究的是基于Pattern时延差编码（PDS）体制下的水声通信技术.PDS水声编码体制利用Pattern码片出现在码元窗的时延差值进行时延编码,通过码元分割,有效的降低了水声信道的多途干扰;通过频率分割划分四个通信信道,增加通信速率至1000bit/s.在接收端利用带通滤波器来实现通信信道分割,每个信道再应用拷贝相关器实现码元分割并估计出时延差值,完成译码.仿真实验表明,该系统适合于大量不同水声信道高可靠性工作,为水声通信网络化打下坚实基础.     

一种水下运动目标被动报警的新算法

根据矢量水听器的测向原理和算法，提出了一种目标方位角的变化实现水下运动目标低频高精度的报警方法。该报警系统以水下设施为平台，对靠近设施的运动目标的方位进行跟踪测量，并在目标距离水下设施最近时给出报警信号，以达到有效地避免事故的目的。与传统的利用声级变化报警或主动回波测距报警方法相比，该方法具有低频、作用距离远和高精度的特点。     

Frequency fine-tuning in Class IV flextensional transducers

Class IV flextensional transducers (FTs) are the best-known FTs in literature. These are light-weight projectors (compared to the conventional Tonpilz designs) with capability for high power delivery at low frequencies. The resonance frequencies of this type of transducers are known to be dominantly dependent on the characteristics of the outer shell than on the driver stack. Consequently, the method of achieving fine-tuning of the transducer by modifying the characteristics of the stack, as practiced in the case of Tonpilz designs, is not very effective. This paper describes a method for fine-tuning of the frequency of a Class IV FT, which involves only a modification of a pair of small components used for coupling the stack to the transducer. The effectiveness of the method is examined by finite element modelling using the package ATILA, in the case of a 3 kHz aluminium shell transducer. Experimental results are also presented.     

一个新型的水下实况微光高速电视记录系统

介绍了一个新型的水下实况微光高速电视记录系统在船上或岸上使用该系统的控制系统,可对该系统的水下成像系统进行远程控制,并通过该水下成像系统得到水下运动目标的水下常速电视图像、水下高速电视图像和水下微光高速电视图像该系统的工作水深可达水下50m.     

柱状分层固体媒质的声散射

本文评述了各向同性和横向各向同性柱状分层固体声散射理论和实验研究进展介绍了描述圆柱状界面薄层特性的弹簧模型，也讨论了该领域中有待进一步研究的一些问题。     

Neural networks for prediction of acoustical properties of polyurethane foams

This paper presents a study of neural networks for prediction of acoustical properties of polyurethane foams. The proposed neural network model of the foam uses easily measured parameters such as frequency, airflow resistivity and density to predict multiple acoustical properties including the sound absorption coefficient and the surface impedance. Such a model is quite robust in the sense that it can be used to develop models for many different classes of materials with different sets of input and output parameters. The current neural network model of the foam is empirical and provides a useful complement to the existing analytical and numerical approaches.