采煤机作业区域人员精确检测方法研究
Study on the method of personnel accurate detection in shearer operating space
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摘要: 采煤机作为综采工作面的关键装备之一,其智能化是实现少人化、无人化开采的必要条件。当前的智能化采煤机已经具有三维定位、记忆截割和远程监控等功能,但缺少采煤机作业区域误入人员的检测和预警保护功能,一旦出现井下人员误入其作业区域,将会带来严重的安全事故。为实现采煤机作业区域人员的安全保护,如何建立一套精确有效的人员检测系统是当前亟待解决的关键问题之一。针对综采工作面具有低照度、工况环境复杂多变的特点,提出了基于红外热成像技术的采煤机作业区域人员精确检测方法。分析了综采工作面红外图像噪声特征,提出了基于高斯掩码改进的多级导向滤波模型;基于Lucas-Kanade光流法和模糊分割理论,实现了动态背景下的移动前景目标运动信息提取并对红外场景信息进行分割;结合移动目标运动信息和红外场景分割结果,构建了基于形态学理论的权重投票法,实现了采煤机作业区域人员的精确检测。最终,在河南大有能源有限公司义煤集团耿村矿21208综采工作面进行了井下工业性试验,试验结果表明:采煤机作业区域人员检测系统于实际综采工作面的人员跟踪偏差低至0.1065像素宽度,重合比为96.10%。采煤机作业区域人员精确检测是实现有效人员安全保护的前提,该系统的建立为智能化综采工作面的安全生产提供技术支撑。Abstract: Shearer is one of the key equipment in fully mechanized working face, and its intelligence is the necessary condition to realize less-human and unmanned mining. Unfortunately, although shearer has functions including three-dimensional positioning, memory cutting, remote monitoring and etc., the detection and pre-warning function for errant personnel who straying into the shearer operating space has not yet been realized. The lack of this function may lead to serious safety accidents once underground personnel straying into the shearer operating space. Hence, it is necessary to research the key technologies of personnel detection in shearer operating space to realize the safety production when shearer operating and achieve safe and efficient production of coal mine. In view of the characteristics of low illumination and complex operating environment of fully mechanized working face, an accurate personnel detection system in shearer operating space based on infrared thermal imaging technology is proposed. By analyzing the characteristics of infrared image noise in fully mechanized working face, a multi-level guided filtering model based on Gaussian mask is proposed; Based on Lucas-Kanade optical flow and fuzzy segmentation theory, the motion information extraction for moving foreground target in dynamic background and the segmentation for infrared scene information are realized, respectively; Combined with the moving-target motion information and infrared-scene segmentation results, a weight voting method based on morphology theory is constructed to realize the accurate detection of personnel in shearer operating space. Finally, the underground industrial test was carried out in the 21208 fully mechanized working face of Gengcun Coal Mine of Henan Dayou Energy Co., Ltd. the test results show that the tracking deviation of the proposed personnel detection system in the shearer operating space in the actual fully mechanized working face is as low as 0.1065 pixel width, and the coincidence ratio is 96.10%. As accurate personnel detection in shearer operating space is the premise of effective personnel safety protection, the establishment of the personnel accurate detection system provides technical support for the safety production of intelligent fully mechanized working face.
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