Research On Velocity Determination Method Of Maglev Pipeline Logistics System Based On Multi-sensor Fusion

Logistics transportation industry is an important pillar of our economic development.The traditional logistics transportation mode has many problems,such as low transportation efficiency,high transportation cost and large carbon emission.With the goal of "double carbon" and the need to build eco-city intelligent logistics,it is imperative to study green and efficient logistics transportation technology,establish new logistics distribution system,and promote the high-quality development of logistics industry.Maglev pipeline logistics system is a new logistics distribution mode based on urban underground integrated pipeline corridor,which can reduce the cost of logistics transportation,improve transportation efficiency,reduce air pollution and carbon emissions,and relieve the pressure of urban surface traffic.Velocity measurement and positioning technology is one of the key technology of maglev pipeline logistics system,which is of great significance for the safety warning,operation control and efficient transportation of the whole system.Based on the maglev pipeline logistics system as the research background,this paper proposes a speed measurement and positioning method based on multi-sensor fusion of Maglev pipeline logistics system,and verifies the feasibility of the scheme through experiments.The main research contents of this paper are as follows:(1)Combining with the basic characteristics of the movement of maglev pipeline logistics system,the kinematic model is constructed,and the working principle and characteristics of Doppler radar,inertial sensor,induction loop and other common velocity measurement and positioning technologies are introduced in detail,focusing on the analysis of the reasons why Doppler radar and inertial sensor speed measurement errors occur.The multi-sensor combination strategy for velocity measurement and positioning of maglev pipeline logistics system is determined.(2)To solve the problem of abnormal Doppler radar speed measurement,Sparrow algorithm(SSA)was introduced to optimize the network of extreme learning Machine(ELM),and a multi-sensor correction compensation algorithm with SSA-ELM combined classification compensation algorithm as the main body was constructed.Doppler radar and inertial sensor are used for velocity measurement experiments,and Doppler radar velocity measurement data are classified.The abnormal data of Doppler radar velocity measurement is corrected and compensated by the inertial sensor velocity measurement data at the corresponding time.Through simulation and experiment,it is verified that the multi-sensor correction compensation algorithm has higher classification accuracy for abnormal data than ELM classification algorithm and BP neural network classification algorithm,and can improve the accuracy of velocity measurement and positioning.(3)A new Sage-Husa adaptive filtering algorithm is proposed as a multi-sensor filtering fusion algorithm,aiming at the problems of measuring noise statistical characteristics changes and data anomalies in complex working conditions.Based on Sage-Husa adaptive filtering algorithm,a fuzzy reasoning system is introduced to correct the covariance of measurement noise in real time.At the same time,the weight of the measured value and the state value can be adjusted by adjusting the Kalman gain adaptively,and the abnormal data can be compensated.Finally,by comparing with the Sage-Husa adaptive filtering algorithm and the traditional Kalman filtering algorithm through simulation experiments,it is verified that the new Sage-Husa adaptive filtering algorithm has higher accuracy and stronger suppression ability to random noise.(4)Based on the data processing strategies of two kinds of multi-sensor fusion technology,the overall design and implementation of the multi-sensor fusion velocity measurement and positioning scheme of the maglev pipeline logistics system are carried out.The simulation model of multi-sensor fusion velocity measurement and positioning is built,and the speed measurement experiment is carried out on the "red rail" maglev train,which verifies the feasibility and practicability of the scheme.The experimental results show that the velocity measurement and positioning method based on multi-sensor fusion has higher accuracy and anti-interference ability than that of a single velocity measurement sensor.The velocity measurement and positioning method of maglev pipeline logistics system based on multi-sensor fusion designed in this paper realizes the compensation of abnormal velocity measurement data of a single sensor and the filtering and fusion of multi-sensor velocity measurement data,fits the unique suspension structure and operating condition of maglev pipeline logistics system,and meets the requirements for velocity measurement and positioning of maglev pipeline logistics system.And to a certain extent,it improves the accuracy and reliability of velocity measurement and positioning technology of maglev pipeline logistics system.This technology provides key technical support for the development of maglev pipeline logistics system,has good engineering application value,and also has a certain reference significance for other rail transit system speed measurement and positioning.