摘要
基于振动信号的故障诊断技术在某些场合下存在着局限性,而机械噪声蕴含着丰富的机器状态信息。利用噪声信号进行故障诊断的技术称之为声学诊断技术。为了实现声学诊断技术,必须结合机器噪声信号的特点,对声学特征提取技术进行深入研究,使得提取的特征能更好地描述机械设备的运行状态。常规的声学特征提取技术可以给出故障特征随时间、频率的变化规律,但无法揭示故障特征随声源位置的变化信息。为了能更有效地利用噪声信号对机械设备进行故障诊断,本文研发了基于局部近场声全息的机械噪声源特征提取技术。该技术采用由少量传声器组成的阵列测量声压,应用联合局部近场声全息快速地重构出物体外部声场。进而获得包含声源的个数、位置、强度等信息的全息图。通过比较故障与正常状态下的全息图,可以识别出某个特定位置的声源特征的变化,再结合特征频率和处于该位置的零部件的特征参数,从而判定出具体故障。该技术的特点是:适合于中低频声场的局部重建;对“可视范围”以外的声源具有较低的灵敏度;计算快速,可以实现声场的实时映射等;可以在测量数据有缺失的情况下重建声场。本文具体研究内容如下。
首先简要介绍故障诊断的研究背景,概述设备故障诊断技术及声学诊断技术的发展概况,回顾总结了噪声源识别与声全息技术的发展概况,对其中的近场声全息方法、等效源方法以及改进统计最优近场声全息进行重点论述。针对应用声学特征提取技术对工业现场机械设备进行故障特征提取这一目标,详细讨论现有的各种噪声源识别方法的优缺点,在此基础上提出需要解决的问题,确立了本文的研究基础。
然后,对机械设备振动辐射的噪声场的产生机理和原因进行分析,并对结构声辐射进行数学描述,推导平面近场声全息的基本公式,讨论平面近场声全息的空间波数域的滤波函数,对平面近场声全息进行数值离散,通过数值仿真验证该算法在一定条件下可以对声源比较精确地识别,同时也指出它存在窗效应和卷绕误差的固有缺陷。为了避免这些缺点,全息面必须大于声源面尺寸的两倍,这对于高频情形下大尺寸声源,往往需要大量的测点,测量工作和重构计算都相当耗时,测量成本非常高,不便于实际现场实施。通过理论分析,奠定全文基于声全息的故障特征提取技术的基础。
详细地介绍局部近场声全息的原理,推导声场重建公式;改进了统计最优近场声全息,并讨论了重建过程中的各种影响因素;针对声场指向性不强的声辐射体,提出了基于双全息面测量的声源定位技术;为解决传统波叠加方法中等效源配置的不确定性问题,提出了联合局部近场声全息方法。该方法在不知道任何声源位置信息的情况下,仍然可以精确重建局部声场。得出如下结论:1)近场声全息要求测量网格必须规则布置,但在实际应用过程中这一要求很难满足。联合局部近场声全息克服了这一缺点,它不受测量网格的限制,网格可以随意布置;2)联合局部近场声全息可以用于重建局部声场。该方法允许测量面小于源面,可以简化测量过程,降低实验成本。联合局部近场声全息的其他优点包括:对“可视范围”以外的声源具有较低的灵敏度;计算快速,可以实现声场的实时映射等;可以在测量数据有缺失的情况下重建声场;3)声压幅值误差带来的重建误差要大于相位失配带来的重建误差。在算法的实际应用过程中,应该将主要精力放在校准传感器幅值上;4)改进了空间波数域中波数矢量的选取方法。该方法在最大波数限定的空间波数平面上非均匀地选取各波数矢量,并且越靠近主分析波数,选取的波数矢量越多。较之均匀选取波数矢量的方法,改进方法可以在保证重建精度的前提下,提高统计最优近场声全息对声场的重建效率。
联合局部声场重构属于声学反问题,详细地介绍了联合局部近场声全息中的离散不适定性问题与各类正则化方法由于联合局部近场声全息属于声学反问题,也常被称为不适定性问题,即解非唯一或不连续依赖于测量数据,小的测量误差将带来解的极大振荡,在数值实现中称为离散不适定性问题,提出通过正则化处理来消除离散不适定性问题的影响。首先通过奇异值分解,将传递矩阵表示成各奇异值分量对解的贡献之和,然后通过正则化滤掉或抑制那些使解产生激烈振荡的小奇异值。实现中可以通过寻求最优正则化参数,决定需要滤波的小奇异值。最后通过仿真研究了不同正则化方法重建效果。得出了一些有利于联合局部近场声全息实际应用的结论:1)声场重构问题为一反问题,不与正则化方法结合,联合局部近场声全息无法实现声场的重建;2)正则化算子方面:利用截断奇异值分解法和Tikhonov正则化方法的联合局部近场声全息重建效果相当;3)正则化参数选择方面:与Tikhonov算子结合,Engl误差极小化准则最适合联合局部近场声全息。
最后,进行了实验研究,探讨联合局部近场声全息技术,以及基于此的故障提取技术的可行性和准确性。介绍了振动实验室现有的硬件平台,自行设计完成了全套传声器阵列与采集系统,叙述了实验原理。在此基础上,在半、全消音室内以音箱、电机和电脑机箱为研究对象,进行噪声源识别与故障特征提取的实验研究,完成了实验数据采集,最后对实验结果分析表明:该技术是可行的和准确的,为其在工业现场的应用打下基础。
对全文研究工作进行总结,并概括论文的创新点,同时就基于声全息的故障诊断技术未来的研究工作提出了一些建议,指出了若干值得注意的问题。
At some situations, the fault diagnosis technique based on vibration signals has its restrictions. As the result of vibration emission in air, machine sound signal carries affluent information about the working condition of machine. It processes the advantage of non-contacting measurement. It can partly take place of vibration signal based fault diagnosis and to be used for mechanical fault diagnosis. The fault diagnosis technique based on sound signal is named by acoustical diagnosis technique. To implement this technique, it should take into account of the characters of machines’noise and make deep research into the technique of acoustical feature extraction. So, the extracted feature can describe machineries’condition well. Traditional acoustical feature extraction method can only describe the law for fault features changing on time, frequency, but they can not reveal the changing information of fault features according to the locations of sound sources.
For more efficiently perform fault diagnosis for machineries using sound signal, a fault feature extraction technique based on acoustical holography is presented in this work. This technique use an array consisted of a small number of microphones to acquire sound pressure. Traditional wave superposition method can not reconstruct the sound field precisely because of the absence of equivalent source configuration information. A method named Joint Patch Near-field Holography (JPNAH) is proposed based on the modified statistically optimal near-field acoustical holography and the wave superposition method. The basic idea is that the fictitious sources’location essential to the wave superposition method can be decided by the modified statistically optimal near-field acoustical holography, and then complex sound field will reconstructed by the wave superposition method with high efficiency and precision. Besides the reconstruction of the patch sound field, the JPNAH has many other virtues. Firstly, the JPNAH technique is not sensitive to the sound source outside the patch area. Secondly, compared to the NAH, the JPNAH performs better in the low frequency range. Finally, using the JPNAH, it is possible to achieve a real-time mapping of the complex sound field. Once the sound field reconstructed, normal templates and abnormal templates based on acoustical holography can be constructed. Comparing the object operating condition with these templates, the differences between them can be found. Then, fault features can be found. Further more, fault diagnosis can be performed with some operating parameters of machines. The main contents of this dissertation can be summarized as follows.
Firstly, the background of fault diagnosis will be introduced. The research history of machinery fault diagnosis technique and acoustical fault diagnosis technique will be summarized. Then, the development of noise source identification and acoustical holography technique will be reviewed. Among them, the near-field acoustical holography and equivalent sources method and modified statistically optimal near field acoustic holography are analyzed in specific. With the aim at extracting fault features for machineries in situation by using acoustical feature methods, a number of noise source identification methods are compared with advantages and disadvantages. A foundation of this work is constructed.
After that, the basic theory and reason of sound radiation from vibrating structure of machineries are analyzed. And also the mechanical sound radiation problems are described in numerical formulations. And the near-filed acoustical holography (NAH) algorithm is deduced. Some filters in wave number domain for NAH are also discussed. Then, the NAH are discredited. Through numerical simulation, it is shown that NAH can accurately identify sound sources certain cases. It also shows that it causes“wrap-round errors”and windowing effects in the calculations. To overcome these shortcomings, the holography surface muse as large as two times of source surface. As for large scale objects at high frequency, it will need a large number of microphones. The test and reconstruction calculation will cost lots of time. Also, the testing costs will increase. These disadvantages hinder the broad applications of NAH in practice. Through theoretical analysis, a foundation is constructed for the acoustical holography based fault feature extraction technique.
Based on the SONAH and WSM, a new method named JPNAH is presented. This method can reconstruct the partial sound field without the information of the sound source. The simulation show that several influence factor is essential to the reconstruction, such as sound source type, measurement plane, reconstruction plane, measurement error and the number of the k-vector. The conclusions are: 1) JPNAH is better than NAH because the measurement array can be random style; 2) JPNAH can simplify the measurement and reduce the experiment cost; 3) JPNAH is more sensitive to the amplitude mismatch than to the phase mismatch; 4) In JPNAH, the number of the k-vector must larger 200. Besides the reconstruction of the patch sound field, the JPNAH has many other virtues. Firstly, the JPNAH technique is not sensitive to the sound source outside the patch area. Secondly, compared to the NAH, the JPNAH performs better in the low frequency range. Finally, using the JPNAH, it is possible to achieve a real-time mapping of the complex sound field. The regularization method is essential to the reconstruction of the sound field based on JPNAH. The Tikhonov approaches in conjunction with different regularization parameter selection strategies have the ability to restrain the effect caused by the measurement noise. In practice, it is hard to obtain the knowledge of the noise variance, so the Tikhonov in conjunction with regularization parameter selection strategies that does not require the knowledge of the noise variance must be used in JPNAH. Based on the accurate reconstruction of the sound field, the acoustical-based diagnosis of the machinery will be achieved. In this paper, several regularization methods are discussed, and the best method is selected. Tikhonov in conjunction with Engl’s criterion is the best to the JPNAH.
After that, experiments are done to evaluate feasibility and accuracy of the techniques present by this work: the JPNAH and the acoustical fault feature extraction technique base on it. That will make a basis for its application in situation. The present hardware of the vibration laboratory is introduced. A set of microphone array and data acquisitions system are designed and implemented. The principle of the experiment is described. On basis of that, experiments are performed in a semi-anechoic and anechoic chamber. The sound source models are made up of a sound box, a motor and the fan of the computer. Sound source identification and fault feature extraction are performed on the sound source model. After acquisition of the sound pressure data, the experimental results are analyzed. The efficiency and accuracy of the technique are proved by experimental results.
Conclusions are given at last. The innovations are summarized. At the same time, some advices are given for the future research for the fault feature extraction based on acoustical holography. Also, remarks are given on some problems.
引文
[1]陈进.机械设备振动监测与故障诊断.上海:上海交通大学出版社, 1999
[2] R. H. Lyon. Machinery noise and diagnostics, Boston: Butterworths, 1987.
[3] J. S. Kwak, J. B. Song. Trouble diagnosis of the grinding process by using acoustic emission signals. International Journal of Machine Tools & Manufacture, 2001, 41: 899-913
[4] X. L. Li. A brief review: acoustic emission method for tool wear monitoring during turning. International Journal of Machine Tools & Manufacture, 2002, 42: 157-165
[5] J. Krzysztof. Some aspects of AE application in tool condition monitoring. Ultrasonics, 2000, 38: 604-608
[6] H. Y. Kim, S. R. Kim, J. H. Ahn, et al. Process monitoring of centerless grinding using acoustic emission. Journal of Material Processing Technology, 2001, 111: 273-278
[7] N. Tandon,, A. Choudhury. A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribology International, 1999, 32: 469-480
[8] C. J. Li, S. Y. Li. Acoustic emission analysis for bearing condition monitoring. Wear 1995, 185: 67-74
[9] M. Juha, A. Peter. Acoustic emission of rolling bearings lubricated with contaminated grease. Tribology International, 2000, 33: 777-787
[10] D. Mba. Applicability of acoustic emissions to monitoring the mechanical integrity of bolted structures in low speed rotating machinery: case study. NDT&E International, 2002, 35:293-300
[11] I. Sato. Rotating machinery diagnosis with acoustic emission techniques. Electrical Engineering in Japan, 1990, 110(2): 115-127
[12] S. Frarooy, J. Allan. Condition monitoring and fault diagnosis of railway signaling mechanical equipment using acoustic emission sensors. Insight-Nondestructive Testing and Condition Monitoring, 1995, 37(4): 294-297
[13] K. Shibata, A. Takahashi, T. Shirai. Fault diagnosis of rotating machinery through visualization of sound signals. Mechanical Systems and Signal Processing, 2000, 14(2): 229-241
[14]李造鼎,李锡润等.故障诊断的声学方法,北京:冶金工业出版社
[15]张策.机床噪声原理及控制.天津:天津科学技术出版社, 1984
[16] R. E. Leitzinger. Development of in-process engine defect detection methods using NVH indicators. Thesis of University of Windsor, 2002
[17] U. Benko, J. Petrovcic, D. Juricic, et al. Fault diagnosis of a vacuum cleaner motor by means of sound analysis. J. Sound and Vib., 2004, 276: 781-806
[18] U. Benko, J. Petrovcic, D. Juricic, et al. An approach to fault diagnosis of vacuum cleaner motors based on sound analysis. Mechanical Systems and Signal Processing, 2005, 19: 427-445
[19]侯温良.从振动噪声判别机器故障--谱相关法.声学学报, 1983, 8(6): 339-344
[20]侯温良.机器噪声的谱相关.声学技术, 2001, 20(1): 24-26
[21]舒大文,廖伯瑜.用振动和噪声信号诊断汽车变速箱齿轮故障的研究.昆明理工大学学报, 1997, 22(4): 54-61
[22]卢学军,魏智.变速箱噪声的频谱分析与故障诊断.振动与冲击, 1999, 18(2): 75-78
[23] K. Anand. Blind separation of multiple co-channel BPSK signal arriving at an antenna array. IEEE Signal Processing Lett., 1995, 2: 176-178
[24] J. Karhunen. Applications of neural blind separation to signal and image processing, In Proc. ICASSP, 1997, 1: 131-134
[25] M. Zhang. An alternative algorithm for estimating and tracking talker location by microphone arrays. J. Audio Eng. Soc., 1996, 44: 729-735
[26] D. Leducq. Hydraulic noise diagnostics using wavelet analysis. In Proceedings of the International Conference on Noise Control Engineers, 1990, 997-100
[27] X. L. Li, S. Dong, Z. J. Yuan. Discrete wavelet transform for tool breakage monitoring. International Journal of Machine Tools & Manufacture, 1999, 39: 1935-1944
[28] F. Honatvar, A. N. Sinclair. Nondestructive evaluation of cylindrical components by resonance acoustic spectroscopy. Ultrasonics, 1998, 36: 845-854
[29] K. Shibata, A. Takahashi, T. Shirai. Fault diagnosis of rotating machinery through visualisation of sound signals. Mechanical Systems and Signal Processing, 2000, 14(2): 229-241
[30] W. D. Li, M. Robert, J. C. Parkin. Acoustic based condition monitoring of a diesel engine using self-organizing map networks. Applied Acoustics, 2002, 63: 699-711
[31] G. Hessel, F. P. Schmitt. A neural network approach for acoustic leak monitoring in pressurized plants with complicated topologies. Control Engineering Practice, 1996, 4(9): 1271-1276
[32] K. Manabu, Y. Ueda, H. Matsumoto, et al. Hybrid neural networks for acoustic diagnosis. In Proceedings of the International Joint Conference on Neural Networks, Oct25-29, 1993
[33]吕琛,王桂增.基于时频模域模型的噪声故障诊断.振动与冲击, 2005, 24(2): 54-57
[34] G. B.Parrent. On the propagation of mutual coherence. J.Opt. Soc.Am., 1959, 49
[35] A.F.M.Hussein. Introduction to acoustical holography. J.Acoust.Soc.Am.,1967,42(4): 1478-1479
[36] D.C. Greece. Use of acoustic holography for the imaging of sources of radiated acoustic intensity. J.Acoust.Soc.Am., 1969,46(1): 44-45
[37] S.Ueha. Mapping of noise-like sound sources with acoustical holography. Applied Optics. 1975,14(7): 1478-1479
[38] S. Ueha. Imaging of acoustic radiation soureces with acoustical holograph. Holography. Applied Optics. 1976,23(2): 107-114
[39] J.D.Maynard, E.G.Williams, Y.Lee. Nearfield acoustic holography: I. Theory of generalized holography and the development of NAH. J.Acoust.Soc.Am.,1985, 78(4):1395-1413
[40] W.A.veronesi, J.D.Maynard. Nearfield acoustic holography (NAH) II. Holographic reconstruction algorithms and computer implementation. J. Acoust. Soc. Am., 1987, 81(5): 1307 -1322
[41] E.G.Williams.Sound sourcere constructions using a microphone array. J. Acoust. Soc. Am., 1980, 68(1): 340-344
[42] E.G.Williams, H.D. Dardy. Nearfied acoustical holography using an under water acoumated scanner. J.Acoust.Soc.Am., 1985,78:789-798
[43] E.G.Williams, H.D. Dardy. Generalized nearfied acoustical holography for cylindrical geometry: Theory and experiment. J.Acoust.Soc.Am., 1987,81(2): 399-407
[44] J.C.Lee. Spherical acoustical holography of low-frequency noise soureces. Applied Acoustics. 1996, 48 (4): 85-95
[45] B.M.Salin and V.I.Turchin. Holographic reconstruction of wave fields with an arbitrary time dependence. Sov. Phys. Acoust., 1992,38(1): 77-79
[46] P.Schacht. Improvement of field projection for sound source reconstruction. Acoustica. 1993, 79: 259-265
[47] H.S.Kson and Y.H.Kim. Moving frame technique for planar acoustic holography. J. Acoust. Soc. Am., 1998, 103(4): 1734-1741
[48] S.H.Park and Y.H.Kim. An improved moving frame acoustic holography for coherent bandlimited noise. J.Acoust.Soc.Am.,1998,104(6):3179-3189
[49] H.Fleischer and U.Axelrad. Restoring an acoustic source from pressure data using Wiener filtering. Acoustica, 1986,60: 172-175
[50] J.Hald. Reduction of spatial windowing effects in acoustical holography. Inter-Noise 94. Yokohama (Japan). August, 1994:1887-1890
[51] Zhang Dejun,et. A new method for low frequency NAH-Nearfield Acoustic Holography. 14th ICA. (Beijing, China). 1992
[52] H.S.Kson and Y.H.Kim. Minimizaion of bias error due to windows in planar acoustic holography using a minimum error window. J.Acoust.Soc.Am.,1995,97(5):2657-2663
[53] K.U.Nam and Y.H.Kim. Errors due to sensor and position mismatch in planar acoustic holography. J.Acoust.Soc.Am.,1995,106(4):1655-1665
[54] G.P. Carroll. Feasibility of implementing near-field acoustic holography at large scale. J. Acoust. Soc.Am.,1996,100(4):2654-2664
[55] G.P. Carroll.The effect of sensor placement error on cylindrical near-field acoustic holography at large scale. J.Acoust.Soc.Am.,1999,105(4):2269-2276
[56] G.P. Carroll. Numerical investigation of error mechanisms in near-field acoustic holography. J.Acoust.Soc.Am.,1995,97(5):3348-3357
[57] R.Reibold. Sound source reconstruction using Fourier Optics. Acoustica, 1987,63:60-64
[58] E.G.Williams. Imaging the soureces on a cylindrical shell from far-field pressure measured on a semicircle. J.Acoust.Soc.Am.,1996,99(4):2022-2032
[59] A.N.Norris. Far-field acoustic holography onto cylindrical surfaee using pressure measured on semicircles. J.Acoust. Soc.Am., 1997,102(4): 2098-2107
[60]杨殿阁,郑四发等.用于声源识别的声全息重建方法的研究.声学学报, 2001,26(3):156-160
[61] Williams E G. Approaches to Patch NAH. Proceedings of Inter-noise 2003, August 2003, Jeju, Korea, 2187-2194.
[62] K Saijyou, Yoshikawa S. Reduction methods of the reconstruction error for large-scale implementation of near-field acoustical holography. Journal of the Acoustical Society of America, 2001, 110(4): 2007-2023.
[63] Williams E G, Continuation of acoustic near-fields. Journal of the Acoustical Society of America. 2003, 113(3): 1273-1281.
[64] Williams E G, Houston B H, Herdic P C. Fast fourier transform and singular value decomposition formulations for patch near-field acoustical holography. Journal of the Acoustical Society of America, 2003, 114(3): 1322-1333.
[65] Lee M Y, Bolton J S. Patch near-field acoustical holography in cylindrical geometry. Journal of the Acoustical Society of America, 2005, 118(6): 3721-3732.
[66] Thomas, Jean-Hugh, Pascal. Wavelet preprocessing for lessening truncation effects in near-field acoustical holography. Journal of the Acoustical Society of America, 2005, 118(2): 851-860.
[67]蒋伟康,万泉.近场声全息理论与应用的研究现状与展望.机械强度,2005,27(3): 288-295.
[68] Wang Z, Wu S F. Helmholtz Equation Least Squares (HELS) method for reconstructing the acoustic pressure field. Journal of the Acoustical Society of America, 1997, 102(4): 2020-2032.
[69] Wu S F, Yu J Y. Reconstruction interior acoustic pressure fields via Helmholtz equation Least-squares method. Journal of the Acoustical Society of America, 1998, 104(4): 2054-2060.
[70] Wu S F. On reconstruction of acoustic pressure fields using the Helmholtz equation least squares method. Journal of the Acoustical Society of America, 2000, 107(5): 2511-2522.
[71] Wu S F, Zhao X. Combined Helmholtz equation-least squares method for reconstructing acoustic radiation from arbitrarily shaped objects. Journal of the Acoustical Society of America. 2002, 112(1): 179-188.
[72] Wu S F. Hybrid near-field acoustic holography. Journal of the Acoustical Society of America, 2004, 115(1): 207-217.
[73] Zhao X, Wu S F. Reconstruction of vibroacoustic fields in half-space by using hybrid near-field acoustical holography. Journal of the Acoustical Society of America, 2005, 117(2): 555-565.
[74] Wu S F, Rayess N, Zhao X. Visualization of acoustic radiation from a vibrating bowling ball. Journal of the Acoustical Society of America, 2001, 109(6): 2771-2779.
[75] Semenova T, Wu S F. The Helmholtz equation least-squares method and Rayleigh hypothesis in near-field acoustical holography. Journal of the Acoustical Society of America, 2004, 115(4): 1632-1640.
[76] Semenova T, Wu S F. On the choice of expansion functions in the Helmholtz equation least-squares method. Journal of the Acoustical Society of America, 2005, 117(2): 701-710.
[77] Wu S F, Lu H C, Bajwa M S, Reconstruction of transient acoustic radiation from a sphere. Journal of the Acoustical Society of America, 2005, 117(4): 2065-2077.
[78] Wu S F, Rayess N E, Shiau N M. Visualizing sound radiation from a vehicle front end using the HELS method. Journal of Sound and Vibration, 2001, 248(5): 963-974.
[79] Rayess N E, Wu S F. Experimental validations of the HELS method for reconstructing acoustic radiation from a complex vibrating structure. Journal of the Acoustical Society of America, 2000, 107(6): 2955-2964.
[80] Koopmann G H, Song L, Fahnline J B. A method for computing acoustic fields based on the principle of wave superposition. Journal of the Acoustical Society of America. 1989, 86(6): 2433-2438.
[81] Benthien G W, Schenck H A, Nonexistence and nonuniqueness problems associated with integral equation method in acoustics. Computers & Structures, 1997, 65(3): 292-305.
[82] Jeans R A, Mathews I C. The wave superposition method as a robust technique for computing acoustic fields. Journal of the Acoustical Society of America, 1992, 92(2): 1156-1166.
[83] Wilton D T, Mathews I C, R A Jeans. A clarification of nonexistence problems with the superposition method. Journal of the Acoustical Society of America, 1993, 94(3): 1676-1680.
[84]向宇,黄玉莹.基于复数矢径的波叠加法解声辐射问题.固体力学学报, 2004, 25(1):35-41.
[85] Sarkissian A. Extension of measurement surface in near-field acoustic holography. Journal of the Acoustical Society of America. 2004, 115(4): 1593-1596.
[86] Sarkissian A. Method of superposition applied to patch near-field acoustic holography. Journal of the Acoustical Society of America, 2005, 118(2): 671-678.
[87]毕传兴,陈心昭,陈剑,等.基于等效源法的近场声全息技术.中国科学E辑, 2005, 35(05): 535-548.
[88]毕传兴,陈心昭,周蓉,等.球面波源叠加法与球面波源边界点法实现声全息的比较研究.科学通报, 2005, 55(06): 512-523.
[89]于飞,陈心昭,李卫兵,等.空间声场全息重建的波叠加方法研究.物理学报, 2004, 53(08): 2607-2613.
[90]薛玮飞,陈进,李加庆.机械噪声故障特征提取的波叠加法.机械科学与技术, 2006, (09):1105-1108.
[91]薛玮飞,陈进,李加庆.机械噪声源识别的混合波叠加法.中国机械工程, 2006, 23:2503-2507.
[92] Xue W F, Chen J, Zhang G C. Sound sources identification for machine acoustic signals based on combined wave superposition method. Acta Acustica United with Acustica, 2006, 92(1): 45-50.
[93]李加庆,陈进,张桂才.基于波叠加的噪声源识别方法.上海交通大学学报, 2006, 40(1):124-128.
[94]李加庆,陈进,张桂才.自由场波叠加噪声源识别的仿真研究.振动与冲击, 2006, (4):58-60.
[95] Steiner R, Hald J. Near-field acoustical holography without the errors and its limitations caused by the use of spatial DFT. International Journal of Acoustics and Vibration, 2001, 6(2):83-89.
[96] Hald J. Patch near-field holography using a new statistically optimal method. Proceedings of Inter-noise 2003, 2203-2210.
[97] Cho Y T, Bolton J S. Source visualization by using statistically optimized near-field acoustical holography in cylindrical coordinates. Journal of the Acoustical Society of America, 2005, 118(5): 2355-2364.
[98]李卫兵,陈剑,于飞,等.统计最优平面近场声全息理论与声场分离技术.物理学报, 2005, 54(3): 1253-1260.
[99] Hald J. Patch holography in cabin environments using a two-layer handheld array with an extended SONAH algorithm, Acta Acustica United With Acustica vol.92, suppl.1 : S24, May-June 2006.
[100] Hald J. A comparison of two patch NAH methods. Proceedings of Inter-noise 2006.
[101] Gomes J. Comparing Parameter Choice Methods for the Regularization in the SONAH Algorithm, Acta Acustica United With Acustica vol.92, suppl.1 : S24, May-June 2006.
[102] Sarkissian A, Charles F. Gaumond, et al. Reconstruction of the acoustic field over a limited surface area on a vibrating cylinder. Journal of the Acoustical Society of America, 1993, 93(1): 48-54.
[103] Saijyou K, Uchida, Hiroshi. Data extrapolation method for boundary element method-based near-field acoustical holography. Journal of the Acoustical Society of America, 2004, 115(2):785-796.
[104] Valdivia N P, Williams E G. Reconstruction of the acoustic field using patch surface measurements. Proceedings of ICSV13, 2006
[105]张徳俊.近场声全息对振动体及其辐射场的成像.物理学进展, 1996, 16(34):613-623
[106]张徳俊.振动体及其辐射场的近场声全息试验研究.声学学报, 1992, 17(6):436-445
[107]蒋伟康.声近场综合试验解析技术及其在车外噪声分析中的应用.机械工程学报, 1998, 34(5):76-84
[108]张徳俊.近场声全息对振动体及其辐射场的成像.物理学进展, 1996, 16(34):613-623
[109]张徳俊.振动体及其辐射场的近场声全息试验研究.声学学报, 1992, 17(6):436-445
[110]何祚庸.声学逆问题-声全息变换技术及源特性判别.物理学进展, 1996, 16(34):600-612
[111]程建政.编磐振动特性的声全息研究.声学学报, 2000, 25(1):87-92
[112] Loyau T, Claude J Pascal. Broadband acoustic holography reconstruction from acoustic intensity measurements I: principle of the method. J.Acoust. Soc. Am, 1988, 84(5):1744-1750
[113] Mann J A, Claude J Pascal. Locating noise sources on an industrial air compressor using broadband acoustical holography from intensity measurements(BAHIM). Noise Control Engineering Journal. 1992,39(1):3-12
[114] Sarkissian A. Near-field acoustical holography for axisym-metric geometries. J.Acoust. Soc. Am, 1990, 88(2):961-966
[115] Metherell A F, Spinak S. Acoustical holography of none instant wavefronts detected at a single point in space. Appl.Phy. Lett. ,1968,13:22-28
[116] Hildebr B P, Haines K A. Holography by Scanning. J. Opt.Soc. Am. 1969, 59(1):1-8
[117] Cutrona L J, Leith E N, etc. On the application of coherent optical processing technique to synthetic aperture radar. PIEEE,1996, 54:1026-1033
[118] Curona L.J., Leith E.N.etc. On the application of coherence optical processing techniques to synthetic aperture radar. PIEEE. 1996, 54:1026-1033
[119] Nitadirtk. An experimental underwater acoustic imaging system using multi-beam scanning. Acoustical Imaging, 1978,8:249-266
[120] Zhang Dejun, Cheng Jianzheng, Wei Jihong. Simulating research of Chinese Chime stones using nearfield acoustical holography.第四届国际声与振动会议.
[121] Jerry L.S. A tutiac on underwater acoustic imaging. Acoustical Imaging,1979,9:599-630.
[122]张德俊. 64×64声全息方阵系统性能评价及水下近距离实验验证.第三届全国声学会议报告.1982
[123]何祚庸,王文芝.声全息测量基阵的设计与研制.哈尔滨工程大学学报, 2002, 23(2):59-65
[124]程建政.编磬振动特性的声全息研究.声学学报, 2000, 25(1):87-92
[125]暴雪梅,目标散射场全息重建方法研究.声学学报, 2000, 25(3):254-264
[126]何元安.基于声强测量的近场声全息及其在水下声辐射分析的应用.声学学报, 1996, 21(4):297-305
[127] T. F. Brooks, M. A. Marcolini, D. S. Pope. A directional array approach for the measurement of rotor noise source distributions with controlled spatial resolution. J. Sound and Vib., 1987, 112(1): 192-197
[128] M. Mosher. Phased array for aeroacoustics testing: theoretical development. AIAA paper 96-1713. 2nd AIAA/CEAS Aeroacoustics Conference, State College, Pa., 1996
[129] M. E. Watts, M. Mosher, M. J. Barnes. The microphone array phased processing system (MAPPS). AIAA paper 96-1714. 2nd AIAA/CEAS Aeroacoustics Conference, State College, Pa., 1996
[130] J. F. Piet, G. Elias. Airframe noise source localization using a microphone array. AIAA paper 97-1643-cp. 3rd AIAA/CEAS Aeroacoustics Conference, Atlanta, Georgia, 1997
[131] R. Davy, H. Remy. Airframe noise characteristics of a 1/11 scale airbus model. AIAA paper 98-2335. 4th AIAA/CEAS Aeroacoustics Conference, Toulouse, France, 1998
[132] J. A. Hayes, W. C. Horne, P. T. Soderman, et al. Airframe noise characteristics of a 4.7% scale DC-10 Model. AIAA paper 97-1594-cp. 3rd AIAA/CEAS Aeroacoustics Conference, Atlanta, Georgia, 1997
[133] B. Barsikow. Experiment with various configurations of microphone arrays used to locate sound sources on railway trains operated by the DB AG. J. Sound and Vib., 1996, 193(1): 283-293
[134] J. M. Rigelsford, A. Tennant. A 64 element acoustic volumetric array. Applied Acoustics, 2000, 61: 469-475
[135] J. J. Christensen, J. Hald. Beamforming. B&K Technical Review Bv0056, 2004, 1: 11-39
[136]乔渭阳.基于麦克风阵列测量的飞机机翼噪声源研究.西北工业大学博士学位论文, 1999
[137]乔渭阳,唐狄毅, U. Michel.基于麦克风阵列测量的机翼脱落涡噪声研究.西北工业大学学报, 2001, 19(2): 200-204
[138]乔渭阳, U. Michel.二维传声器阵列测量技术及其对飞机进场着陆过程噪声的实验研究.声学学报, 2001, 26(2): 161-168
[139]贾智骏.基于传声器阵列的声源识别理论与实验研究.上海交通大学硕士学位论文, 2003
[140] Herault J, Jutten C. Space or time adaptive signal processing by neural network models. Neural Network for Computing: In Proceedings of AIP Conference, New York: American Institute for Physics, 1986, 207-211.
[141] Jutten C, Herault J. Blind separation of sources, parts I: an adaptive algorithm based on neuromimetic architecture. Signal Processing, 1991, 24(1):1-10.
[142] Comon P. Independent component analysis, a new concept. Signal Processing, 1994, 36:287-314.
[143] Simon C, Loubaton R, and Jutten C. Separation of a class of convolutive mixtures: a contrast function approach. Signal Processing, 2001, 81:883-887.
[144] Platt C, Faggin F. Networks for the separation of sources that are superimposed and delayed. Advances in Neural Information Processing Systems, 1991,730-737.
[145] Gelle G., Colas M, Serviere C. Blind source separation: A tool for rotating machine monitoring by vibrations analysis. Journal of Sound and Vibration, 2002,248(5): 865-885.
[146] Gelle G, Colas M, Delaunay G. Blind source separation applied to rotating machines monitoring by acoustical and vibrations analysis. Mechanical system and signal processing, 2000, 14(3): 427-442.
[147] Roan M J, Erling J G, Sibul L H. A new, non-linear, adaptive, blind source separation approach to gear tooth failure detection and analysis. Mechanical System and Signal Processing, 2002, 16(5): 719-740.
[148] Wu J B, Chen J, Zhong Z M, Zhong P. Application of Blind Source Separation Method in Mechanical Sound Signal Analysis. Proceedings of the ASME International Mechanical Engineering Congress and Exposition (IMECE2002), Volume 2, November 17-22, 2002, New Orleans, Louisiana, USA, pp. IMECE 2002-39225.
[149]吴军彪,陈进,伍星.基于盲源分离技术的故障特征信号分离方法.机械强度, 2002, 24(4):485-488.
[150] A.J.Burton, G.F.Milter. The application of integral equation methods of the numberical solution of some exterior boundary value problems. Proc. R. Soc. London Ser.A. 1971,323:201-210
[151] D.S. Burnett. A three-dimensional acoustic infinite element based on a prolate sphereoidal multipole expansion. J.Acoust.Soc.Am. 1994,96 (5): 2798-2816
[152] Jacqueline, A.Bettess and P. Bettess. A new mapped infinite wave element for general wave diffraction problems and its validation on the ellipse diffraction problem. Compute Methods Appl. Mech. Engrg. 1998,164:17-48
[153] Khalili N, Yazdchi M, Valliappan S. Wave propagation analysis of two-phase saturated porous media using coupled finite-infinite element method. Soil Dynamics and Earthquake Engineering, 1999,18:533-553
[154] Gerdes K, Ihlenburg F. On the solution effect in FE solutions of the 3D-Helmholtz equation.Comput. Methods Appl.Mech.Engrg., 1999,170:155-172
[155] Safjian A, Newman M. The ill-conditioning of infinite element stiffness matrices. Computers and Mathimatics with Application, 2001,41:1263-1291
[156] Astley R J, Macaulay G J. Mapped wave envelope for acoustical radiation and scattering. Journal of sound and vibration, 1994, 170(1): 97-118