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来自声学摄像头的声音地图中评估源定位有效性的功能

Luca Fredianelli¹, Gregorio Pedrini², Matteo Bolognese³

¹National Research Council (CNR), a Moruzzi 1, 56124 Pisa, Italy.

Sensors (Basel, Switzerland)

|July 27, 2024

概括

本研究介绍了一种分析声学摄像头 (AC) 声音图的方法,提取可量化的数据,如源位置和不确定性. 这推动了AC技术在各种应用中可靠的噪声排放分析.

科学领域:

声学声学在声学方面
信号处理信号处理
环境监测环境监测

背景情况:

声波摄像头 (AC) 越来越多地用于环境声学中的噪声源识别.
目前的AC结果缺乏可认证性,原因是不同条件下的光束成形算法和硬件的变化.
没有足够的研究解决了这些测量条件问题的澄清.

研究的目的:

开发一种方法来从AC产生的声音图中提取分析和定量特征.
为了能够客观地比较不同AC和beamforming算法的数据.
在现实世界声学场景中为未来的比较研究提供基础.

主要方法:

在自由场条件下使用具有已知的声音源的交流器进行了测量活动.
开发了一种方法来从视觉声音地图中提取最大声音发射点的坐标.
计算了已识别的排放点与实际源位置之间的距离,以及相关的不确定性.

主要成果:

提出的方法成功地从声音地图中收集了最大排放点的坐标.
从实际源位置的距离和测量的不确定性量化.
提取的分析特征为在不同设置中比较交流性能提供了基础.

结论:

开发的方法允许从交流声图中提取客观的分析数据.
这种方法促进了标准化的比较,提高了交流技术的可靠性和适用性.
这种方法可以适应在声学之外的领域分析强度图.

关键词:

声波摄像机的声音摄像机波束成形算法的算法.环境噪声环境噪声麦克风阵列是一系列的麦克风阵列.噪声测量噪声测量声音地图声音地图声音信号声音信号声音信号源代码本地化源代码本地化

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