声波/振动生命探测系统数理模型的研究

【作者】 简兴祥；

【导师】 王绪本；

【作者基本信息】 成都理工大学 ， 固体地球物理学， 2003， 硕士

【摘要】 地震应急与救助技术一直是世界各国研究和探索的一个重大课题。本文在国家‘十五’科技攻关课题“地震救助生命搜索与定位技术研究”中，承担并完成了声波／振动生命搜索定位技术数理模型的研究。 本文首先从最基本的声波／振动信号分析着手，通过现场模拟实验的方式，分析了地震救助现场可能的声波／振动信号及其特征。参照经典的地震定位方法(Geiger法)，提出了一种基于能量追踪和时差定位的生命搜索定位技术方案，并且通过模拟实验和计算，论证了该方案的可行性。 由于地震救助现场的复杂性，提高声波／振动信号的信噪比的研究是本文的一个重点。由于小波变换具有良好的信噪分离能力，本文将小波理论引入到了声波／振动信号去噪处理中，重点研究了几种常用的小波去噪方法和传统的滤波技术，通过对比分析证明了该方法的有效性。 在实际测量过程中，除了过滤干扰信号，提取有效信号外，多振动源信号分离是本文研究的一个难点。本文在声波／振动信号分析基础上，引入了一种基于独立分量分析的盲源分离方法，在理论数据和实际信号的分离实验中取得了理想的效果。更多还原

【Abstract】 The Earthquake Emergency Response Rescue Technology always is a vital problem in worldwide research. In this paper, the author undertook and completed the study on mathematical and physical model of the life detection system based on sound wave and vibration theory. It is a branch of National Fifteen Tackling Key Problem-Life Detection And Orientation Of Earthquake Emergency Response System.The study begins with the analysis of the basic theory about sound wave and vibration signals, and analyses several possible signals and their Characteristic in earthquake site through a series of experiments. Referring to the classical location method attributed to Geiger, this paper brings up a scheme according to energy tracking and time difference of arrival(TDOA) theory to the position location of the survivor. And proves the feasibility of this scheme through a series of experiments.Because of the complexities of the earthquake site, it is especially important to study the improvement of the Signal-to-Noise Ratio. This is an important point in this paper. For the good property of separation between signal and noise, Wavelet analysis is introduced to the denoising of sound wave and vibration signals in this paper. The emphasis is placed on the contrasts filtering methods of several wavelets with that of tradition technique. Thereout, conclusion obviously is that wavelet is better in filtering.Beside filtering interference signals and extract effective signals, it is a difficult problem to study the separation of multi-signal of sound wave and vibration. In this paper, the author introduces the Blind Source Separation(BSS) method-Independent Component Analysis(IC A) to the separation of multi-signal of sound wave and vibration, and get ideal result in separation of theoretical and experimental data.更多还原