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基于多信息融合的带式输送机堆煤检测系统

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在煤矿行业中,带式输送机的运输通常会采用级联多台的方式,这会导致在转载点处经常出现煤炭堆积的情况.而传统的人工巡检和堆煤传感器无法及时准确判断输送机堆煤故障,这给煤矿生产的安全带来了潜在威胁.针对此问题,提出了一种基于多信息融合的带式输送机堆煤检测系统.在带式输送机转载点处安装雷达增强处理感知装置以及防尘高清工业相机,通过雷达获取煤堆的全方位状态参数,并结合经过图像算法处理后的高清工业相机拍摄的图像数据,综合判断带式输送机的堆煤状况,同时配备现场可编程的智能边缘一体机,根据监测结果实时反馈给控制系统,以调整设备参数或执行相应的控制策略.通过对雷达数据及机器视觉的多信息融合,提高了堆煤检测的准确性和可靠性,有效预测了潜在的堆煤风险,为煤矿生产提供了有效的安全保障.
Coal Stacking Detection System of Belt Conveyor Based on Multi-Information Fusion
In the coal mining industry,the transportation of belt conveyors usually adopts the method of cascading multiple units,which often leads to coal accumulation at the transfer point.However,traditional manual inspections and coal stacking sensors are unable to timely and accurately determine conveyor coal stacking faults,which poses a potential threat to the safety of coal mine production.A coal stacking detection system for belt conveyors based on multi information fusion is proposed to address this issue.Install radar enhanced processing and perception devices as well as dust-proof high-definition industrial cameras at the transfer point of the belt conveyor.Obtain the comprehensive state parameters of the coal pile through radar,and combine the image data captured by the high-definition industrial camera after image algorithm processing to comprehensively judge the coal stacking condition of the belt conveyor.At the same time,equip with an intelligent edge integrated machine that can be programmed on site,and provide real-time feedback to the control system based on monitoring results to adjust equipment parameters or execute corresponding control strategies.By integrating multiple information from radar data and machine vision,the accuracy and reliability of coal pile detection have been improved,and potential coal pile risks have been effectively predicted,providing effective safety guarantees for coal mine production.

coal stacking detectionmulti-information fusionradarmachine vision

涂多锐、李敬兆、陈瑞云、黄平

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安徽理工大学电气与信息工程学院,安徽 淮南 232001

淮南矿业集团煤业公司,安徽 淮南 232001

堆煤检测 多信息融合 雷达 机器视觉

2024

自动化应用
重庆西南信息有限公司

自动化应用

影响因子:0.156
ISSN:1674-778X
年,卷(期):2024.65(17)