煤矿四旋翼飞行机器人环境信息数据压缩算法

Environmental information data compression algorithm for coal mine four-rotor flying robot

  • 摘要: 针对四旋翼飞行机器人在煤矿巷道中的飞行路径与轨迹多变,导致其在动态空间中采集的环境信息数据有较大冗余的问题,提出了一种煤矿四旋翼飞行机器人环境信息数据压缩算法。采用小波分析中的默认阈值降噪方法对原始数据进行降噪处理,以提高信噪比;以甲烷监测为例介绍数据压缩算法,将巷道空间沿巷道方向拆分成若干个截面,选取每个拆分截面的甲烷浓度有效值,并通过有效值对甲烷浓度检测数据进行重构。实验结果表明,通过算法压缩和重构的甲烷浓度信号与人工检测结果相比误差很小,数据压缩算法能够提取出甲烷浓度数据有效值,去除机器人采集到的冗余环境信息,从而提高数据传输的有效性和实时性。

     

    Abstract: In view of problem that flight path and trajectory of four-rotor flying robot in coal mine roadway are changeable, which leads to great redundancy of environment information data collected by the robot in dynamic space, an environmental information data compression algorithm for coal mine four-rotor flying robot is proposed. The default threshold noise reduction method of wavelet analysis is used to reduce the noise of original data to improve signal-to-noise ratio; taking methane monitoring as an example to introduce data compression algorithm, the roadway space is split into several sections along the roadway direction, and the effective value of methane concentration of each split section is selected and used to reconstruct the detection data of methane concentration. The experimental results show that the methane concentration signal compressed and reconstructed by the algorithm has little error with the manual detection result, the data compression algorithm can extract the effective value of methane concentration data and remove the redundant environmental information collected by the robot, thereby improving the effectiveness and real-time performance of data transmission.

     

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