综放工作面放煤量激光扫描监测三维重建方法研究

Three-dimensional reconstruction method of coal flow laser scanning monitoring

目前我国厚煤层主要采用综放开采技术,而放煤过程中经常出现过放或者欠放等问题,因此放煤过程中刮板机上部煤量三维重建是实现特厚煤层综放开采的核心技术问题之一。针对该问题,设计了一种放煤量激光扫描智能监测系统,利用激光扫描法获取临近放煤口位置的刮板输送机上煤流轮廓的点云数据,根据刮板输送机上的煤流特征信息实时构建堆煤量的高精度三维模型;提出了一种适用于综放工作面的放煤量三维重建方法,结合最近迭代点算法(ICP)求解每帧激光数据之间的变换关系,设计高次回归滤波消除拼接误差和环境噪音,使模型效果更贴合工作面实际工况;利用了峰值信噪比和平均结构相似性的调和数评价方法,对不同算法的去噪性能进行合理地打分和对比,证明了该算法具有更强的适用性。

At present,the fully mechanized caving technology is widely used for thick coal seams in China,and problems such as over-caving or inadequate-caving often occur during the coal caving process.Therefore,the 3D reconstruction of the coal volume on the upper part of the rear scraper during the coal caving process is one of the core technical problems of realizing the fully-mechanized caving of extra-thick coal seams.Aiming at this problem,a laser scanning intelligent monitoring system for coal discharge is designed.The laser scanning method is used to obtain the point cloud data of the coal flow profile on the scraper conveyor near the coal discharge,the high-precision 3D model of piled coal volume can be constructed in real time according to the coal flow characteristic information on the scraper conveyor;a 3D reconstruction method of coal caving volume is proposed for fully mechanized caving face,combining with the nearest iterative point algorithm(ICP)to solve the transformation relationship between each frame of laser data.Secondary regression filtering eliminates splicing errors and environmental noise,so that the model effect is more suitable for the actual working conditions of the working face;the harmonic number evaluation method of peak signal-to-noise ratio and average structural similarity is used to reasonably score the denoising performance of different algorithms.And the comparison proves that the algorithm in this paper has stronger applicability.