焦炉机车定位系统的设计与温漂控制算法的研究

Design of coke oven locomotive locating system and research on temperature drift control algorithm

为提高焦炉机车的定位精度,同时提高定位系统的环境适应性,采用RFID技术进行炉号识别,利用对称安装有两霍尔效应传感器的定位装置电路板,经过磁场时产生的电流信号进行机车的精定位。由于环境的温度因素是影响系统定位精度的主要因素,故采用了神经网络算法对系统的温漂进行校正。其中,根据定位精度的要求和机车运行速度等因素确定了神经网络的训练参数。最后,通过实验验证,该系统的定位精度为-1~1mm,优于现有技术,且对温度具有较强鲁棒性。

In order to improve the positioning accuracy of coke oven locomotive and improve the environmental adaptability of the positioning system, the RFID technology is used to identify the door number of coke oven, and two Hall effect sensors are symmetrically mounted on the positioning device circuit board,which can generate a current signal when passing through a magnetic field. This current signal can be used for precise positioning of the locomotive.Temperature of its operating environment is the main factor that affects the system positioning accuracy,so a neural network algorithm is developed to correct the temperature drift of the system.In this process, according to the requirements of positioning accuracy and locomotive running speed and other factors, the neural network training parameters are determined.Finally,through the experimental verification, the positioning accuracy of the system is -1~1mm,which is better than the existing technologies.More importantly, the system has a strong robustness to temperature.