基于多源传感器的电力新材料智慧仓储系统设计

Design of Intelligent Storage System for Power New Materials Based on Multi source Sensors

针对电力新材料智慧仓储系统数据采集和定位精度需求,提出一种基于改进定位算法的仓储系统。其中,以温湿度传感器作为多源数据的主要来源,以MCU等为主控芯片,通过硬件和软件设计,实现仓储系统的数据采集;针对UWB定位中传统Taylor算法定位差的问题,提出采用位置指纹协同的定位方法,通过位置指纹算法对待测目标的位置进行初步估计,并以该结果作为初始值,然后再采用Taylor算法进行定位,从而提高定位精度,解决传统Taylor算法中初始值随机的问题。仿真结果表明,该定位方法在MATLAB仿真和LOS、NLOS视距环境下,表现出较好的定位精度和收敛速度。且本系统的仿真任务时间与真实任务时间的十分拟合,两者间的误差较小。由此得出,提出的仓储定位方法可提升系统仓储定位精度,具备一定的可行性和有效性。

A warehousing system based on an improved positioning algorithm is proposed to meet the data collection and positioning accuracy requirements of the smart warehousing system for power new materials.Among them,temperature and humidity sensors are the main source of multi-source data,and MCU and other main control chips are used to achieve data collection in the storage system through hardware and software design;In response to the problem of poor positioning using traditional Taylor algorithm in UWB positioning,a positioning method using position fingerprint collaboration is proposed.The position of the target to be tested is preliminarily estimated using the position fingerprint algorithm,and the result is used as the initial value.Then,the Taylor algorithm is used for positioning to improve positioning accuracy and solve the problem of random initial values in traditional Taylor algorithm.The simulation results show that the positioning method exhibits good positioning accuracy and convergence speed in MATLAB simulation and LOS,NLOS line-of-sight environments.Moreover,the simulation task time of this system is very close to the actual task time,and the error between the two is relatively small.From this,it can be concluded that the proposed warehouse positioning method can improve the accuracy of the system’s warehouse positioning,and has certain feasibility and effectiveness.