【作者】 薛玮飞；

【导师】 陈进；

【作者基本信息】 上海交通大学 ， 机械设计与理论， 2007， 博士

【摘要】 机械噪声蕴含着机器设备状态的重要信息,可被用来进行机器状态监测与故障诊断,在进行噪声故障诊断过程中,准确的找出机器噪声产生的根源是非常关键的。声源辨识技术利用测量面的信息采用特定的变换算法,可以重建出声场中任意场点的声压、声速与声强等声学参量,进行声源辨识与定位及声场的预测。本文详细地分析了国内外声源辨识技术研究的历史和现状,对其中的近场声全息(NAH)与Helmholtz方程最小二乘(HELS)法、波叠加法进行深入的研究的基础上,充分结合HELS与波叠加法这两种方法的优点,提出一种新的声源辨识方法—混合叠加法,该方法的基本思想是:基于Helmholtz方程最小二乘法用相对少量的测点数据获得包围源的最小球面上或之外的任意一假想球面上的声压数据,然后将这些数据作为输入,计算出辐射体内混合内域虚源强的强度值,通过解离散波叠加的方程,重建出在重建面上离散点的声压、声速等值。为了避免傅里叶变换的平面近场声全息在有限传声器阵列上离散带来窗效应和声场重建过程中引起卷绕误差,采用统计最优平面近场声全息技术,并提出了基于统计最优平面近场声全息(SONAH)的噪声源分离技术,从混合噪声信号中分离出各个噪声源信号的时域波形及频域特征,进行故障信号特征分离提取。具体研究内容如下:首先探讨了声场重构技术的研究意义,回顾和分析了声源辨识方法的发展历史和研究现状,详细讨论了现有声源辨识技术的实现方法和各自所具有的优缺点,明确了需要解决的问题,确立了本论文的研究内容。对振动结构机械噪声的声场进行了数学描述,推导了平面近场声全息技术的基本公式,讨论了平面全息的空间波数域的滤波函数。通过数值仿真验证了该算法在一定条件下可以对声源比较精确地辨识,但也显示了在声场重建计算过程中的窗效应和卷绕误差。提出采用混合波叠加法作为声场重建算法,建立了用混合波叠加法进行声场全息重建和预测的数学模型。该方法既继承了波叠加方法适于任意形状声源分析的优点,又继承了HELS方法的稳健性优点。不仅避免了奇异值和解非唯一性问题,同时克服了测量传声器数目多及测量工作和重建计算都相当耗时等问题。用数值仿真分析讨论了虚源点的数目、位置及分布形状对重构结果精度的影响。通过数值算例和实验验证该算法对声源辨识的精确性。提出了基于Tichhonov正则化的统计优化近场声全息声源辨识技术,有效地抑制传声器测量误差对声场的影响影响,给出了正则化系数的选取方法。通过仿真算例验证了SONAH能有效地解决NAH技术在计算过程带来窗效应和卷绕误差以较少的传声器有效地、精确地辨识出噪声源。提出了SONAH应用噪声源的信号特征提取的基本原理:运用SONAH重建振动体的声压场,得到声场中比较重要的振动噪声源的个数,并且把每个信号源的方位计算出来,重建传声器与噪声源系统的混合矩阵,从而逆向求解,得到各个噪声源信号的时域波形及频域特征,进行故障信号特征分离提取。在半消声室,基于Tichohonov正则化的统计优化近场声全息对单个音箱声源、两个音箱声源及电动机声源进行声场重建试验,得到空间场的声压、声速与声强等声学参量;用B&K标准声强探头测得的声强与重建声强进行了比较;并且从一个音箱和电动机混合信号从分离出源信号;验证了该方法的声场重建和预测技术的精确性和可行性、及其在噪声源特征提取的适用性。更多还原

【Abstract】 As the result of vibration emission in air, machine sound signal carries affluent information about the working condition of machine and it can be used to make mechanical fault diagnosis. The fundamental problems for sound diagnosis are to estimate the number of mechanical noise sources and localize them. Sound source identification is a technique that applies the partial information of the acoustic holography to reconstruct the acoustic parameters including sound pressure, velocity and sound intensity at every point in 3-D sound field. In this paper, the research history and applicaiton of sound source identification are studied detailedly in overseas and home. After the investigations and research about implement procedures, characters and existing problems of three sound source identificaiton technologies: Near-field Acoustic Holography (NAH), Helmholtz Equation Least Square (HELS) and Superposition Wave, a combined wave superposition method is developed to overcome time consuming and high cost for sound source identification. It allows for reconstruction of acoustic field radiated from an arbitrary object with few relatively few measurements, and the efficiency of reconstruction can be significantly enhanced. The first step in the combined wave superposition method is to establish the Helmholzt equation least squares formulation based on a finite number of acoustic pressure measurements taken on or beyond a hypothetical spherical surface that enclose the object under consideration. Next enough field acoustic pressures are generated using the Helmholtz equation least squares formulations and taken as the input to calculate the source strength. The acoustic pressures, velocities and sound intensities at the discretized nodes on the reconstructed surface are determined by solving the matrix equation based on the wave superposition. In order to avoid spatial Fourier transform-related truncation error and windowing effects based on NAH, the statistically optimal NAH (SONAH) method is introduced which performs the plane-to-plane calculations directly in the spatial domain. The SONAH algorithm is described and some numerical simulations are presented. In addition, a new technology based on SONAH method is also develop for the seperation of machinery’s acoustic signal.After the estimation of sound source numbers and positions, each source’s spectum is obtained from the mixed signal. The main content of this paper can be summarized as follows:1. Firstly, the research significance of sound source identification is discussed. The research history is reviewed and the research application of is also investigated. The advantage and disadvantage of every sound source identification methods are analyzed and compared detaily,and the concrete research points are decided, then the research content of this paper are defined.2. The basic theory of sound radiation from vibrating structure is introduced, and the near-filed acoustical holography (NAH) algorithm is deduced. Some filters are also introduced and discussed for sound reconstruction accuracy. Two pulsing spheres with the same phase are investigated to reconstruct sound field on the reconstruction plane. The results show that the use of spatial FFT and multiplication with a transfer function in the spatial frequency domain is computationally very efficient, but it causes“wrap-round errors”and windowing effects in the calculations.3. A new sound field reconstruction method of combined wave superposition is proposed for the first time. It not only can avoid singularity present in the integral equations and the non-uniqueness of the solution at critical wave numbers,but also reconstruct of acoustic field radiated from an arbitrary object with few relatively few measurements. It is disscussed about the non-singularity solution problems by using mono-layer potential form for Dirichlet inner region problem and using double potential form for Neumann inner region problem at the Eigen-frequency.By applying pulsing spherical source as the example, the influences of number of virtual source, virtual source location and distribution shape of virtual source on the accurateness of reconstruction result are analyzed, and the instability of the combined wave superposition is investigated.4. In order to avoid spatial Fourier transform-related truncation effects, the measurement aperture (i.e., the hologram surface) must typically extend well beyond the sources, a statistically optimal NAH (SONAH) method is introduced which performs the plane-to-plane calculations directly in the spatial domain. In oder to avoid the estimation errors of the sound sources number and sources positon, a new feature extraction method based on SONAH is developed to get the separated sources from the mixed signal. Firstly, the sound preasure field is reconstructed based on SONAH and the number and position of sound sources are estimted efficiently.Then, the tranfer matrix between microphones and sound sources is established. Finally, by inverse solution, the waveform in time domain and the exatrcted featureg in the frequency domain are obtained, which can be used as a machine diagnostic tool.5. In a semi-anechoic chamber, the sound sources are set up as one high fidelity loudspeaker, two loudspeakers and the motor. The location, the sound pressure and the properties in frequency domain of the sound sources can be found through this method precisely. The experimental results demonstrate that the SONAH is very effective in the low-to-mid regime, and can potentially become a powerful noise diagnostic tool.更多还原