超宽带信号穿透塌方体衰减特性及生命特征检测方法研究

发布时间：2019-06-27 20:11

【摘要】：煤炭在中国的能源组成中有着重要地位,煤矿安全生产问题备注关注。事故发生后,如何尽快了解塌方体下面的情况,这对开展救援工作来说是十分重要和紧迫的。UWB信号穿透能力强、抗干扰、分辨力高、探测盲区小,因此适用于矿井下救援探测。利用UWB信号对塌方体下的生命进行探测,可提高救援效率。本文以煤矿巷道塌方为背景,分析了塌方体的电磁特性。对UWB电磁波的衰减特性进行理论分析。以平面电磁波理论以及菲涅尔公式为理论基础,分析了超宽带电磁波在岩石、混凝土,以及复杂塌方体介质中的传输损耗、反射损耗特性。数值仿真结果表明:入射角越大损耗越大;UWB电磁波随频率的升高,其损耗变大;平行极化波透射损耗由于入射角的增大,而先减后增;介电常数较大的塌方体介质,对UWB信号的衰减作用以反射损耗为主。在上述工作的基础上,研究了基于UWB信号的塌方体下生命特征检测算法。矿井下UWB信号杂波有较大的波动,故采用经验模态分解(EMD)与参考独立分量分析(R-ICA)混合算法。用R-ICA方法滤除杂波分量,应用EMD算法将回波信号分解为若干分量,并在时域上分析生命特性曲线,在高信干比的情况下提取呼吸和心跳信号。仿真结果表明该算法可以重构目标生命体呼吸、心跳的波形信息,可用于塌方体下的非接触式生命检测。
[Abstract]:Coal plays an important role in the energy composition of China, and the safety of coal mine production is concerned. After the accident, how to understand the situation below the collapse as soon as possible is very important and urgent for the rescue work. UWB signal has strong penetration ability, anti-interference, high resolution and small detection blind area, so it is suitable for underground rescue detection. The rescue efficiency can be improved by using UWB signal to detect the life under collapse. Based on the collapse of coal mine roadway, the electromagnetic characteristics of collapse body are analyzed in this paper. The attenuation characteristics of UWB electromagnetic wave are analyzed theoretically. Based on the theory of plane electromagnetic wave and Fresnel formula, the transmission loss and reflection loss characteristics of ultra-broadband electromagnetic wave in rock, concrete and complex collapse medium are analyzed. The numerical simulation results show that the larger the incident angle is, the greater the loss is; the loss of UWB electromagnetic wave increases with the increase of frequency; the transmission loss of parallel polarization wave decreases at first and then increases because of the increase of incident angle; the attenuation effect of collapse medium with large dielectric constant on UWB signal is dominated by reflection loss. On the basis of the above work, the life feature detection algorithm under collapse based on UWB signal is studied. The clutter of UWB signal in mine fluctuates greatly, so the hybrid algorithm of empirical mode decomposition (EMD) and reference independent component analysis (R-ICA) is used. The hash component is filtered by R-ICA method, the echo signal is decomposed into several components by EMD algorithm, and the life characteristic curve is analyzed in time domain, and the respiratory and heartbeat signals are extracted under the condition of high signal-to-interference ratio. The simulation results show that the algorithm can reconstruct the waveform information of breathing and heartbeat of the target life body, and can be used for contactless life detection under collapse.
【学位授予单位】：黑龙江科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN925

【参考文献】