摘要
刮板输送机输送量受物料横截面积与链条运行速度影响,若其无法按额定转速运转或物料堆积厚度不合理,会出现非满负荷运转问题,这会使确定最超前和最滞后推溜点位置困难,增大直线度控制误差。为此提出基于传感器数据融合算法的直线度控制方法。先在刮板输送机上设置传感器采集数据,利用卡尔曼滤波算法对数据进行筛选校正,削弱噪声干扰与不确定性;再采用自适应加权平均法融合修正后的数据,消除传感器差异。基于融合结果分析运行轨迹,对比不同时间点轨迹图,确定推溜点位置变化并计算直线度误差。接着用PID控制算法依误差计算结果控制,同时用鲸鱼优化算法优化PID控制参数,通过调整链条速度和物料横截面积,保障输送机满负荷运转。实验表明,该方法直线度误差计算精度高,能精准控制煤矿刮板输送机直线度,有效解决非满负荷运转带来的控制难题。
The conveying capacity of scraper conveyor is affected by the cross-sectional area of the material and the running speed of the chain.If it cannot operate at the rated speed or the material stacking thickness is unreasonable,it will cause non full load operation problems,which will make it difficult to determine the position of the most advanced and lagging sliding points and will increase the straightness control error.A straightness control method based on sensor data fusion algorithm is proposed for this purpose.Firstly,sensors are installed on the scraper conveyor to collect data,and the Kalman filtering algorithm is used to filter and correct the data,reducing noise interference and uncertainty.Then this paper uses the adaptive weighted average method to fuse the corrected data and eliminate sensor differences.Based on the fusion results,analyze the running trajectory,compare the trajectory diagrams at different time points,determine the changes in the position of the sliding point,and calculate the straightness error.Then,the PID control algorithm is used to control based on the error calculation results,and the whale optimization algorithm is used to optimize the PID control parameters.By adjusting the chain speed and material cross-sectional area,the conveyor can operate at full load.Experiments have shown that this method has high accuracy in calculating straightness errors and can accurately control the straightness of coal mine scraper conveyors,effectively solving the control problems caused by non full load operation.
作者
刘明明
潘国柱
李棚
Liu Mingming;Pan Guozhu;Li Peng(College of Electronics and Information Engineering,Lu′an Vocational Technical College,Lu′an,Anhui 237000,China;School of Electrical and Photoelectronic Engineering,West Anhui University,Lu′an,Anhui 237012,China)
出处
《黑龙江工业学院学报(综合版)》
2025年第11期112-116,共5页
Journal of Heilongjiang University of Technology(Comprehensive Edition)
基金
安徽省教育厅自然科学重点项目“红外气体传感器在智能穿戴装备上检测矿区甲烷的研究”(项目编号:KJ2021A1352)。
