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智能天线是第三代移动通信的关键技术之一,也是当前信号处理和通信领域的研究热点.在对智能天线算法进行理论分析和仿真的基础上,有必要构建一个灵活、通用的实验平台,用以验证各种智能天线算法的有效性和实用性.探讨了一种基于自适应麦克风阵的智能天线实验平台的实现方法,介绍了该系统的原理、结构和各部分的作用. 相似文献
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Transport measurement with a horizontal and a vertical pipe microphone in a mountain stream: taking account of particle saltation 
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下载免费PDF全文 The pipe microphone has been shown to be an effective means for monitoring bedload transport in mountain streams. It is commonly installed perpendicular to the flow direction on a stable river bed, such as that of a check dam. Acoustic pulses caused by bedload collisions with the pipe are detected by a microphone. However, bedload particles saltating over the pipe remain undetected. To overcome this disadvantage, we installed a horizontal as well as a vertical pipe microphone in the Ashi‐arai‐dani supercritical channel located in the Hodaka mountain range, Japan. The vertical pipe was installed on the wall of the channel and the horizontal pipe was installed on the channel bed. The acoustic response of the horizontal pipe is expected to be larger than that of the vertical pipe, because the bedload concentration decreases with increasing height above the bed. However, at high amplifications, the peak pulse value from the vertical pipe is higher than that from the horizontal pipe. We explain this observation as follows: under high bedload discharge conditions, the pulses of the horizontal pipe are saturated but those of the vertical pipe are not. We proposed a ratio (Rhv) between the pulses detected by these sensors, and applied this ratio for calibrating the contemporaneous pulses detected by a microphone located immediately upstream of a bedload slot sampler. Indeed the Rhv‐corrected pulses correlated well with the bedload discharge calculated from the sampler, supporting our explanation. We conclude that bedload monitoring using concomitant vertical and horizontal pipe microphones can be used to calibrate centrally located pipe microphones when the bedload concentration is approximately homogeneous laterally across the width of the channel cross‐section, and thereby represent bedload discharges more accurately than with only a single pipe microphone. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
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设计了一个三维声源定位系统,提出了一个新的系统模型,并对传统的基于声波到达时间差TDOA的算法进行了优化。通过检测麦克风接收到信号的时间差,结合已知的阵列元的空间位置确定声源的位置。该系统声源采集部分由4个阵列成正四面体的麦克风组成。算法的硬件实现由TMS320C5416DSP芯片完成''整个系统实现了声源定位的功能。 相似文献
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Eran Halfi Dror Paz Kyle Stark Uri Yogev Ian Reid Michael Dorman Jonathan B. Laronne 《地球表面变化过程与地形》2020,45(14):3510-3524
The monitoring of bedload flux under flash flood conditions has been successfully achieved since 1992 using slot samplers in the semiarid Nahal Eshtemoa. In the present study, a surrogate bedload monitoring technique - the Japanese plate microphone - has been deployed and calibrated against data from the slot samplers. Since a slot sampler has a sensitivity threshold that becomes especially important when transport rates are low, different averaging periods should be considered for high and low fluxes. In order to overcome the deficiencies of time-based aggregation used hitherto, we have developed a new method involving mass aggregation and commensurably variable intervals, thereby enabling a more accurate analysis and optimizing the bedload sampler's capabilities. The data derived with this new method has then been utilized to calibrate the Japanese plate microphone. The Eshtemoa is an ephemeral gravel bed channel with a high proportion of fine gravel (< 0.02 m); for these conditions, acoustic sensors have not been calibrated as yet. Two multiple linear regression models incorporating the effect of median bedload grain size on pulse rate have been established to predict bedload flux and cumulative transported bedload mass. The coefficients in these models are statistically significant. Good predictions are obtained for bedload flux (adj. r2 = 0.83) and for cumulative bedload mass (adj. r2 = 0.98) during flood recession. Overall, the multiple linear regression models, used in conjunction with the mass aggregation method of estimating bedload flux, suggest that field calibration of acoustic devices is feasible under these conditions for ca. 90% of the duration of bedload transport. © 2020 John Wiley & Sons, Ltd. 相似文献
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针对实际环境中因麦克风阵列失配误差导致宽带波束形成器性能下降的问题,提出基于线性约束最小方差对角加载的稳健频率不变波束形成算法.该算法首先在线性约束最小方差准则的基础上,结合空间响应偏差函数,并对波束形成器权矢量的二范数施加不等式约束,再通过拉格朗日乘子法和凸优化工具箱CVX(ConVeX)分别在不等约束条件下求得权矢量的解析解和全局最佳解,以有效解决麦克风的增益、相位和位置等的不确定性造成的失配误差问题,提高频率不变波束器的稳健性.仿真结果表明:采用拉格朗日乘子法求解该算法的最优权矢量所得到的波束形成器对失配误差最不敏感,性能最稳健. 相似文献
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针对现有无损检测技术在钢-混组合结构界面混凝土脱空损伤识别问题上普遍存在的测试成本高、识别精度有限及操作过程复杂等不足之处,提出了一种基于麦克风冲击共振测试的非接触式检测方法。首先,基于四边约束矩形薄板振动理论,将钢-混凝土板局部脱空处钢板简化为四边固支约束的板壳模型进行分析。通过在ABAQUS中建立考虑流-固耦合的钢-混凝土板有限元模型,将模拟所得脱空处钢板自振频率值与理论解析结果进行对比,证明该经验公式可有效适用于脱空区域处局部钢板自振频率的估计当中。其次,依据相关声学理论研究成果,利用所建立的有限元模型进行了外部激励下钢-混组合结构声压场信号分布特征研究,结果表明设置及未设置脱空损伤的有限元模型所产生的声压响应存在明显不同,且未脱空模型中信号响应具有幅值大、周期长等特征;同时,针对一钢-混凝土板设置了8种不同类型的损伤工况,并利用麦克风传感器分别进行了基于冲击共振测试的脱空损伤识别。试验结果表明,麦克风摆放位置对测试所得声压信号频响函数基本特征的影响程度并不显著;且针对本试验所设置的损伤工况,该方法基本均能实现有效识别,但对平面尺寸在60 mm以下区域的测试效果并不明显。最后,在对一特定损伤区域进行栅格化处理的基础上,通过开展基于麦克风冲击共振法的损伤成像测试,对该脱空区域的平面轮廓进行了有效识别。除此之外,将试验测试效果分别与传统红外热像检测法、超声波探测法进行了对比分析,验证了该麦克风冲击共振法能够较好地适用于钢-混组合结构的脱空损伤识别问题当中,且具有非接触式、测试成本低、识别效果显著及操作便捷等优点。 相似文献
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