摘要
为了解决以往桥式起重机定位系统所存在的定位精度差的问题,在保留原有起重机结构的基础上,设计采用神经网络作为定位方法的系统。将起重机作业区域划分为横、纵、垂直三个运行方向,依据桥式起重机定位工作方式,设计可编程逻辑控制器,扩展定位点数量,控制起重机系统承受高倍电流。采用GY-530 VL53L0X型号激光测距传感器收集外界阻碍信息,区分目标横向或纵向移动。利用变频器改变电机工作电源频率,使用固定标志点,集合线性部件设计定位控制电路。依据神经网络层次分析结果输出模拟量信号,获取不同方向坐标。利用可编程逻辑控制器中的变量确定大小车区位,通过定位点编号捕获目标,确定大小车行驶方向,实现桥式起重机定位。由实验结果可知,该系统最高定位精度可达到96%,能够稳定运行。
Since the existing bridge crane positioning system is of poor positioning accuracy,a system using neural network as the positioning method is designed on the basis of retaining the original structure of crane. The operation area of crane is divided into three areas according to operation direction of transverse direction,longitudinal direction and vertical direction.According to the positioning mode of the bridge crane,a programmable logic controller is designed to increase the number of positioning points and control the crane system to be capable of bearing high current. The GY-530VL53 L0X laser ranging sensor is used to collect external obstruction information and distinguish the transverse or longitudinal movement of the target. The frequency converter is used to change the working frequency of the power supply of motor,and the fixed mark point is used in combination with the linear component to design the positioning control circuit. According to the results of neural network hierarchical analysis,analog quantity signals are output to obtain coordinates in different directions. The variables of the programmable logic controller is used to determine the location of large and small vehicles,and the target is captured by the number of positioning points to determine the driving direction of large and small vehicles and realize the positioning of the bridge crane. The experimental results show that the highest positioning accuracy of the system can reach 96%,and the system can run steadily.
作者
袁智
陶艺辉
YUAN Zhi;TAO Yihui(School of Logistics Engineering,Wuhan University of Technology,Wuhan 430063,China)
出处
《现代电子技术》
北大核心
2020年第11期106-110,共5页
Modern Electronics Technique
关键词
桥式起重机定位系统
起重机系统电流控制
定位控制电路设计
神经网络层次分析
定位系统仿真测试
定位精度对比
bridge crane positioning system
current control of crane system
design of positioning control circuit
neural network hierarchical analysis
positioning system simulation test
positioning accuracy contrast
