Design Of Monitoring System For Hazardous Chemical Vehicles And Research On Multi-Sensor Fusion State Judgment

With the rapid development of the economy,the demand for chemicals in various industries is increasing,and the resulting transport accidents are also on the rise.In the process of transferring hazardous chemicals from the production site to the consumption site,road transport is mainly used.Once a road accident occurs,it will cause great damage to the ecological environment and the safety of human life and property.In addition,hazardous chemicals have toxic,corrosive,explosive and other properties,and if rescue is not carried out in time,the damage will be increased.Therefore,research on the monitoring system for hazardous chemical transport vehicles,real-time monitoring of vehicle data and safety state,has profound significance for accident prevention and rescue.Firstly,taking hazardous chemical transport tank trucks as the research object,the overall scheme of the monitoring system is designed,and the system is divided into two parts: vehicle terminal and remote monitoring terminal.Based on the on-board terminal,the data collected by sensors is transmitted to the One NET Io T platform,which achieves the goal of data security and convenient expansion in the cloud.Secondly,it analyses the functional requirements of the remote monitoring system,builds the front and back services of the Web monitoring system based on the mainstream Spring boot and Vue.js frameworks,analyses,stores and displays the data pushed by the One NET platform,realises vehicle monitoring,data statistics and other functions,and builds a We Chat applet monitoring system to form a complete system that can monitor both the computer side and the mobile phone side.Finally,research is conducted on multi-sensor data fusion algorithms,and an SVM-DS vehicle state judgment algorithm model based on Support Vector Machine(SVM)and D-S evidence theory is constructed.The model takes roll angle,liquid level height,internal temperature,tank pressure,combustible gas concentration,and vehicle speed as data indicators,selects normal,rollover alarm,and tank alarm as target state sets,and uses grid search algorithm,genetic algorithm,and particle swarm optimization to optimize the parameters of SVM to obtain three optimization models,and then constructs the evidence body of D-S evidence theory for fusion.The test results show that the SVM-DS model can fully utilize multiple sensors to achieve state judgment on hazardous chemical transport vehicles,with a decision accuracy of 96.67%.And after deployment,the model can be integrated with remote monitoring systems to achieve real-time state judgment,which has practical application value.