【作者】 孙玉玲；

【导师】 杨洪涛；

【作者基本信息】 安徽理工大学 ， 机械制造及其自动化， 2012， 硕士

【摘要】 地雷的探测是一项具有危险性和挑战性的工作。经实验验证,采用高压水射流进行切雷,效率高,安全性好。因此可以将高压水射流技术,传声器阵列和声音识别技术相结合,实现探雷排雷一体化,提高探雷的效率和安全性。探雷的本质就是靶物识别,要实现这一功能,首先需从高压水射流冲击靶物产生的反射声音信号中,将环境噪声和靶物反射声音信号进行有效分离,这涉及到了声源分离研究。另一方面,当完成靶物识别后,还应能实现对声源的准确实时定位。本文针对探雷方法中涉及到的声源分离和声源定位展开了以下几方面工作：分析了高压水射流技术、声源分离以及声源定位的国内外研究现状；阐述了独立成分分析和基于到达时间差的声源定位的基本理论；利用传声器阵列、数据采集卡和计算机接口技术等搭建了一定的硬件系统；编写了独立成分分析和声源定位的测试软件和程序,推导了线性传声器阵列的定位公式；对采用的独立成分分析中的FastICA以及基于到达时间差的定位中的互功率谱相位时延估计法进行了仿真验证；采集了室内和室外两种实验数据,对两种实验数据均进行了声源分离和声源定位的分析处理。仿真和实验结果表明,采用的FastICA能够实现对环境噪声和不同靶物反射声音信号的有效分离,重构探测线上的声音分布；采用的互功率谱相位时延估计法能够较准确地估计出传声器阵列间的时延,根据推导的定位公式能够实现对声源的准确定位。这些研究结果为项目的顺利进展提供了前提,为反射声音信号的特征值提取以及靶物的识别奠定了坚实的基础。图[42]表[8]参[58]更多还原

【Abstract】 Detecting mines is full of danger and challenging. It is experimentally verified that the high pressure water-jet cutting the mines is efficient and safe. Therefore, the mines detection and mines exclusion can be integrated by combining high pressure water-jet technology, microphone array and sound identification, which improves the efficience and security of the mines detection. The mines detection essence is targets recognition. To realize the function, the first step is separating the environment noise from the target refelective sound signals produced when the targets are attacked by high pressure water-jet. On the other hand, it is a necessary to locate the sound source accurately and in real time after the targets identification.The sound source separation and soud source localization related to the mines detection have been done the following jobs in the paper. The present research states at home and abroad of high pressure water-jet technology, sound source separation and sound source localization were analyzed. The theory of independent component analysis and sound source localization based on time difference was described. The hardware system was composed of microphone array, data acquisition card, computer interface and so on. The measurement software of independent component analysis and sound source localization was programmed. The localization formulas based on linear microphone array were deduced. The simulation experiments about FastICA belonged to independent component analysis and cross-power spectrum phase time delay estimation of sound source localization based on time difference were done. The indoor and outdoor experiment datas were acquired. What’s more, the two experiment datas were both processed with the sound source separation and sound source localization.The simulation and experiment results show that the environment noise can be separated from the different targets reflective sound signals effectively by FastICA, which reconstructs the detecting-line sound distribution, and that the time delay between the microphone array can be estimated approximately by cross-power spectrum phase time delay estimation. The sound source localization was realized by the deduced localization formulas too. All of the results provide premises to the progress of the project and do spade work for the eigenvalues extraction of reflective sound signals and target recognition.Figure [42] table [8] reference [58]更多还原