Research on the transportation model and coal quantity calculation algorithm of scraper conveyor based on array
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摘要: 目前针对煤量检测的研究大多侧重于煤矿井下带式输送机的煤量检测和识别，对综采（放）工作面刮板输送机的煤量检测仅停留在转载机处安装红外扫描装置，检测技术单一，且由于转载机位于刮板输送机卸煤处，红外扫描装置检测的是转载机的载煤量，不能直接反映刮板输送机上的实时载煤量，存在较大滞后性。针对上述问题，提出一种基于数组的刮板输送机运载模型及煤量计算算法。该算法将刮板输送机设定为连续装煤的载体，通过连续数组建立刮板输送机运载模型，并表征单位长度的装煤量，结合综采（放）工作面采煤机运行速度、滚筒高度、截割深度、位置及刮板输送机运行速度与装煤系数等参数，通过多参数数学建模的方法，实现对刮板输送机单位煤量的实时模拟，进而直观反映煤矿井下采煤工艺并准确计算出刮板输送机的实时载煤量。井下工业性试验结果表明，该算法连续可靠，可以精确计算出刮板输送机实时载煤量，载煤量分布接近于理想状态，具有较高的收敛性和鲁棒性。Abstract: Currently, most research on coal quantity detection focuses on the coal quantity detection and recognition of underground belt conveyors in coal mines. The coal quantity detection of scraper conveyors in fully mechanized working (caving) faces only stays at the transfer machine, where infrared scanning devices are installed. The detection technology is single, and because the transfer machine is located at the coal unloading point of the scraper conveyor, the infrared scanning device detects the coal loading of the transfer machine and cannot directly reflect the real-time coal loading on the scraper conveyor, resulting in significant lag. In order to solve the above problems, a transportation model and coal quantity calculation algorithm of scraper conveyor based on array is proposed. This algorithm sets the scraper conveyor as a continuous coal loading carrier, establishes a scraper conveyor transportation model through a continuous array, and characterizes the coal quantity per unit length. Combining the operating speed, drum height, cutting depth and position of the shearer and the operating speed and coal loading factor of the scraper conveyor, the real-time simulation of the unit coal quantity of the scraper conveyor is realized through the method of multi-parameter mathematical modelling. It can intuitively reflect the coal mining process of the underground coal mines and accurately calculate the real-time coal quantity of the scraper conveyor. The results of underground industrial tests show that the algorithm is continuous and reliable, and can accurately calculate the real-time coal quantity on the scraper conveyor. The distribution of coal quantity is close to the ideal state, and it has high convergence and robustness.
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图 9 理论煤量与红外煤量检测装置测出的煤量对比
Figure 9. Comparison of theoretical coal quantity and coal quantity measured by infrared coal quantity detection device
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图 11 刮板输送机集中控制系统平台主界面
Figure 11. The main interface of centralized control system platform of scraper conveyor
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[1] 董立红,宋伟思,符立梅. 基于双目视觉的动态煤量测量方法[J]. 煤炭科学技术,2022,50(8):196-203. DONG Lihong,SONG Weisi,FU Limei. Dynamic coal quantity measurement method based on binocular vision[J]. Coal Science and Technology,2022,50(8):196-203.
[2] 代伟,赵杰,杨春雨,等. 基于双目视觉深度感知的带式输送机煤量检测方法[J]. 煤炭学报,2017,42(增刊2):547-555. DAI Wei,ZHAO Jie,YANG Chunyu,et al. Detection method of coal quantity in belt conveyor based on binocular vision depth perception[J]. Journal of China Coal Society,2017,42(S2):547-555.
[3] 王凯. 基于刮板输送机负载预测的采煤机调速技术研究[D]. 徐州:中国矿业大学,2015. WANG Kai. Research on shearer speed control technology based on scraper conveyor load Prediction[D]. Xuzhou:China University of Mining and Technology,2015.
[4] 郝洪涛,王凯,丁文捷. 基于超声阵列的输送带动态煤量检测系统[J]. 工矿自动化,2023,49(4):120-127. HAO Hongtao,WANG Kai,DING Wenjie. A dynamic coal quantity detection system for conveyor belt based on ultrasonic array[J]. Journal of Mine Automation,2023,49(4):120-127.
[5] 韩涛,黄友锐,张立志,等. 基于图像识别的带式输送机输煤量和跑偏检测方法[J]. 工矿自动化,2020,46(4):17-22. HAN Tao,HUANG Yourui,ZHANG Lizhi,et al. Detection method of coal quantity and deviation of belt conveyor based on image recognition[J]. Industry and Mine Automation,2020,46(4):17-22.
[6] 郝洪涛,杨庭杰,张超. 基于负载估计的带式输送机系统节能控制方法研究[J]. 煤炭科学技术,2021,49(7):139-146. HAO Hongtao,YANG Tingjie,ZHANG Chao. Research on energy saving control method of belt conveyor system based on load estimation[J]. Coal Science and Technology,2021,49(7):139-146.
[7] 胡而已. 基于激光扫描的综放工作面放煤量智能监测技术[J]. 煤炭科学技术,2022,50(2):244-251. HU Eryi. Intelligent monitoring technology of coal caving in fully-mechanized caving face based on laser scanning[J]. Coal Science and Technology,2022,50(2):244-251.
[8] 陈湘源,薛旭升. 基于线性模型划分的煤流体积测量[J]. 工矿自动化,2023,49(7):35-40,106. CHEN Xiangyuan,XUE Xusheng. Coal flow volume measurement based on linear model partitioning[J]. Journal of Mine Automation,2023,49(7):35-40,106.
[9] 张克亮. 基于MT−CNN的矿井带式输送机输煤量检测技术[J]. 中国矿业,2024,33(6):137-142. DOI: 10.12075/j.issn.1004-4051.20230577 ZHANG Keliang. Coal conveying quantity detection of mine belt conveyor based on MT-CNN[J]. China Mining Magazine,2024,33(6):137-142. DOI: 10.12075/j.issn.1004-4051.20230577
[10] 刘永刚,杨茗迪. 智能刮板输送机控制系统的应用研究[J]. 煤矿机械,2016,37(12):27-29. LIU Yonggang,YANG Mingdi. Application research on intelligent scraper conveyor control system[J]. Coal Mine Machinery,2016,37(12):27-29.
[11] 王利栋. 综放工作面放煤量激光扫描监测三维重建方法研究[J]. 煤炭工程,2022,54(5):125-130. WANG Lidong. Three-dimensional reconstruction method of coal flow laser scanning monitoring[J]. Coal Engineering,2022,54(5):125-130.
[12] 孙鹏亮,吴少伟. 基于红外扫描装置的转载机煤量监测技术研究[J]. 数字通信世界,2022(8):63-65. SUN Pengliang,WU Shaowei. Research on infrared scanning technology of coal transfer machine[J]. Digital Communication World,2022(8):63-65.
[13] 刘飞,张乐群,蒋伟,等. 基于深度图像的带式输送机煤量检测方法[J]. 西安科技大学学报,2023,43(5):1008-1014. LIU Fei,ZHANG Lequn,JIANG Wei,et al. Coal quantity detection of belt conveyor based on depth image[J]. Journal of Xi'an University of Science and Technology,2023,43(5):1008-1014.
[14] 胡而已,叶兰,孙益壮,等. 综放工作面放煤量激光扫描自适应监测技术研究[J]. 中国煤炭,2022,48(11):57-66. HU Eryi,YE Lan,SUN Yizhuang,et al. Study on laser scanning adaptive monitoring technology for coal caving volume in fully mechanized top-coal caving face[J]. China Coal,2022,48(11):57-66.
[15] 张耀. 煤矿运输系统煤量激光三角法监测技术研究[D]. 徐州:中国矿业大学,2022. ZHANG Yao. Study on monitoring technology of coal quantity by laser triangulation in coal mine transportation system[D]. Xuzhou:China University of Mining and Technology,2022.
[16] 杨光耀,毛开江,胡而已,等. 过煤量激光图像智能监测技术研究[J]. 中国煤炭,2021,47(10):49-55. YANG Guangyao,MAO Kaijiang,HU Eryi,et al. Research on laser image intelligent monitoring technology for coal passing quantity[J]. China Coal,2021,47(10):49-55.
[17] 彭丽,陈重,郝博南. 基于激光与视觉融合的煤量检测技术研究[J]. 煤炭技术,2023,42(3):259-263. PENG Li,CHEN Zhong,HAO Bonan. Research on coal quantity detection technology based on laser and vision fusion[J]. Coal Technology,2023,42(3):259-263.
[18] 吕剑铎,贺振华,王新宇. 基于激光雷达的带式输送机煤量检测技术[J]. 煤炭工程,2021,53(增刊1):54-59. LYU Jianduo,HE Zhenhua,WANG Xinyu. Coal quantity detection of belt conveyor based on laser radar[J]. Coal Engineering,2021,53(S1):54-59.
[19] 李学晖. 基于机器视觉和深度学习的带式输送机煤量识别方法研究[D]. 邯郸:河北工程大学,2022. LI Xuehui. Research on coal quantity identification method of belt conveyor based on machine vision and deep learning[D]. Handan:Hebei University of Engineering,2022.
[20] 崔振国. 基于机器视觉的带式输送机煤量监测系统研究[D]. 徐州:中国矿业大学,2021. CUI Zhenguo. Study on coal quantity monitoring system of belt conveyor based on machine vision[D]. Xuzhou:China University of Mining and Technology,2021.
[21] 贺杰,王桂梅,刘杰辉,等. 基于图像处理的皮带机上煤量体积计量[J]. 计量学报,2020,41(12):1516-1520. HE Jie,WANG Guimei,LIU Jiehui,et al. volume measurement of coal volume on belt conveyor based on image processing[J]. Acta Metrologica Sinica,2020,41(12):1516-1520.
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