Design And Implementation Of A Multi-sensor Data Acquisition And Verification Platform

Train speed measurement and positioning is an important part of train operation control system.Multi-sensor fusion to achieve train speed measurement and positioning is the current mainstream method.A single sensor can not meet the needs of train speed measurement and positioning.Using the advantages of different sensors,we can learn from each other to provide more reliable and accurate information for the system.This paper designs and implements a multi-sensor data acquisition software and hardware platform for train speed measurement and positioning,which provides the basic environment and original data for the research of train positioning based on multi-sensor fusion methods and fusion algorithms.The main work of the paper is as follows:(1)Firstly,the platform system scheme is proposed.According to the platform system scheme,the requirements of the platform are analyzed from the functional requirements and interface requirements.According to the platform requirements,the overall design scheme of the hardware platform and the overall design scheme of the software platform are proposed.(2)According to the overall design of the hardware platform,complete the design and implementation of the hardware platform.Based on the existing train track and analog car,the hardware platform is built with E6C2-CWZ1 X Omron speed sensor,speed measurement radar,JY901 inertial measurement unit and UM220-IV NV positioning module.According to the speed measurement and positioning characteristics of each sensor,complete the reasonable layout of the sensor,complete the hardware design of hardware data acquisition circuit and its peripheral interface circuit.(3)According to the overall design of the software platform,complete the design and implementation of the software platform.The software platform realizes the software functions of the multi-sensor data acquisition platform based on the rich third-party libraries in Python.The data acquisition function of each sensor is realized through the third-party software.Using pandas,Matplotlib and other library functions in Python,the data preprocessing function is realized through the median filter algorithm.Using the wxpyron Library in Python,a good man-machine operation interface is designed.Pymysql library is used to realize the interaction between Python and My SQL database and realize the function of data storage.(4)Build software and hardware acquisition platform to collect data in real time.The Kalman filter algorithm is used to fuse the data of Omron speed sensor and speed measuring radar,and the data fusion results are analyzed to verify the effectiveness of the software and hardware platform.Through the joint debugging of software and hardware,and the data fusion operation of the collected data,it is verified that the multi-sensor data acquisition platform implemented in this paper can provide a test environment and original data for the subsequent research of data fusion algorithm,and it is usable.Through the hardware circuit test,the output voltage test result of the power module is within ± 2% of the nominal value,meeting the power supply requirements of the system;After the test signal receiving and isolating circuit,the transceiver signal is normal.The percentage of the difference between the speed value and the reference speed after the fusion of Omron speed sensor and speed measuring radar is less than0.4km/h,which verifies that the multi-sensor data acquisition platform realized in this paper can provide the test environment and original data for the subsequent research of data fusion algorithm.This paper includes 66 figures,8 tables,and 39 references.