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Source localization and power estimation in aeroacoustic noise measurements.

机译：航空噪声测量中的源定位和功率估计。

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摘要

Using microphone arrays for noise source localization and power estimation has become common practice in aeroacoustic measurements, with the ultimate goal being the development of acoustic treatments to reduce overall airframe noise. This dissertation discusses the challenges involved in aeroacoustic testing with microphone arrays and develops a number of new signal processing techniques to overcome these challenges. The proposed algorithms are validated using both simulations and experimental data acquired at the University of Florida Aeroacoustic Flow Facility (UFAFF) with a 63-element microphone array.;The standard delay-and-sum (DAS) beamformer is the most widely employed beamforming algorithm due to its simplicity and robustness, although it suffers from high sidelobe level and low resolution problems. Deconvolution can be used to eliminate the effects of the array response function from the DAS estimates. In this dissertation, the deconvolution problem is carried onto the sparse signal representation area and a sparsity constrained deconvolution approach (SC-DAMAS) as well as a sparsity preserving covariance matrix fitting approach (CMF) area presented. These algorithms are shown to offer better performance than several existing methods.;Next, a systematic experimental analysis of DAS, deconvolution approach for the mapping of acoustic sources (DAMAS), SC-DAMAS, CMF, and CLEAN based on spatial source coherence (CLEAN-SC) is presented using uncorrelated and coherent sources as well as a NACA Mod 63-215 Mod B airfoil model. The source localization and absolute signal power estimation performance of the aforementioned algorithms are analyzed.;To deal with correlated sources, the CMF-C algorithm, which is an extension to CMF, is proposed as an alternative to DAMAS-C, which is the extension of DAMAS to the correlated case. Since DAMAS-C and CMF-C are computationally impractical, an alternative algorithm, named mapping of acoustic correlated sources (MACS), is also presented. MACS is shown to work with simulated and experimental data containing correlated (or coherent) sources within a reasonable amount of time.;Furthermore, a systematic uncertainty analysis of the DAS beamformer and a widely used array calibration procedure is presented. It is shown using experimental data that the uncertainties in the DAS beamformer integrated levels can be expected to be larger than about +/-1 dB. It is also shown that the array calibration procedure is essential when the assumed steering vectors are expected to contain errors.;Most existing array processing algorithms for aeroacoustic noise measurement applications assume the presence of monopole sources. The last chapter of the dissertation addresses the problem of directive sources with unknown steering vectors. An algorithm for estimating non-diagonal measurement noise covariance matrices is also presented in this chapter as an alternative to diagonal removal.
机译：使用麦克风阵列进行噪声源定位和功率估计已成为航空声学测量中的普遍做法，其最终目标是开发声学处理方法以减少机身整体噪声。本文讨论了麦克风阵列进行航空声学测试所涉及的挑战，并开发了许多新的信号处理技术来克服这些挑战。所提出的算法通过使用佛罗里达大学航空声流设施（UFAFF）的63元素麦克风阵列获得的仿真和实验数据进行了验证;标准延迟和和（DAS）波束形成器是应用最广泛的波束形成算法尽管它具有高旁瓣水平和低分辨率的问题，但由于其简单性和鲁棒性。去卷积可用于从DAS估计中消除阵列响应函数的影响。本文将反卷积问题应用于稀疏信号表示区域，并提出了稀疏约束反卷积方法（SC-DAMAS）和稀疏保留协方差矩阵拟合方法（CMF）。这些算法显示出比几种现有方法更好的性能。接下来，对DAS进行系统的实验分析，基于空间源相干性（CLEAN）的声源（DAMAS），SC-DAMAS，CMF和CLEAN映射的反卷积方法-SC）是使用不相关且相干的数据源以及NACA Mod 63-215 Mod B机翼模型提出的。分析了上述算法的源定位和绝对信号功率估计性能。为了处理相关源，提出了对CMF的扩展CMF-C算法，作为对DAMAS-C的替代方案。 DAMAS到相关案例。由于DAMAS-C和CMF-C在计算上不切实际，因此还提出了另一种算法，称为声相关源映射（MACS）。已显示MACS在合理的时间内可以处理包含相关（或相干）源的模拟和实验数据。此外，本文还对DAS波束形成器进行了系统的不确定性分析，并提出了一种广泛使用的阵列校准程序。使用实验数据表明，DAS波束形成器集成水平的不确定性可以期望大于大约+/- 1 dB。还显示出，当假设的转向矢量预期包含误差时，阵列校准程序是必不可少的。大多数用于航空声学噪声测量应用的现有阵列处理算法都假设存在单极子源。论文的最后一章解决了具有未知转向矢量的指令源的问题。本章还介绍了一种估计非对角线测量噪声协方差矩阵的算法，作为对角线去除的一种替代方法。

著录项

  • 作者

    Yardibi, Tarik.;

  • 作者单位

    University of Florida.;

  • 授予单位 University of Florida.;
  • 学科 Engineering Aerospace.;Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 148 p.
  • 总页数 148
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:24

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