基于聚类分析方法的CCD测量原井下煤仓煤位改进测量模型研究

Research on improved measurement model of underground coal bunker height based on CCD measurement based on clustering analysis method

通过分析CCD测量的基本原理以及井下煤仓的工作环境,指出几种井下煤位CCD测量模型的不足,给出了一种改进的测量模型,并采用聚类分析方法改进Gauss-Laplachian算子图像分割算法,比较准确地提取了粉尘干扰以及煤炭表面漫反射干扰影响下的辅助光源成像光斑。模型整体降低了测量装置的安装要求和参数标定要求,提高了测量装置的抗干扰能力和测量误差。实验数据分析表明,本文所提出的测量方法能满足物位测量的要求,且能适应井下煤仓环境。

By analyzing the basic principle of CCD measure and working conditions underground of coal mine, noting that several shortage of coal mine height of coal CCD sensor model, and an improved measurement model has been given, that is improve Gauss-Laplachian counted using cluster analysis sub- image segmentation algorithm,more accurate edge of auxiliary light spot imaging has been extracted in the condition of disturbances by dust and coal surface diffuse, thus reducing the requirements of installations and parameters measuring device calibration,and noise immunity of measuring apparatus and measurement error has been improved. Experimental data analysis shows that the proposed measurement method can satisfy the requirements of level measurement,and can adapt to the underground bunker environment.