Research On Data Fusion Of Safety Operation Monitoring Of Special Carrier Vehicles

In the context of domestic Internet,electronic technology,big data,and China's smart manufacturing,this paper sets up an operation monitoring platform for the safety of the special vehicle transporting weapons.As a driver,the monitoring value of each sensor at the current operating state and the safe operating parameters after data fusion can be viewed in real time through the vehicle display;as a rear-base staff,you can log in to web pages and remote APP terminals to view real-time data of currently running special carrier vehicles.The main contents of this paper are as follows:(1)The hardware design of data acquisition system in transportation process f special carrier vehicles.To study various methods currently used in multi-sensor data acquisition systems,select the ARM core board as its hardware,and the ?C/OS operating system as the underlying operating system of the entire acquisition system.According to the actual needs of the selection of a variety of appropriate sensors,equipped with an operating system on the hardware to achieve a collection of multiple data acquisition vehicle sensors,the data collected in accordance with certain requirements for analysis and preservation.(2)Software design based on monitoring platform for safe operation of spcial carrier vehicles.The software design mainly includes the real-time analysis of the underlying acquisition data and the real-time display of the upper terminal device.The acquisition of the data from the bottom layer to the server is based on the c language socket communication module.The terminal display includes the smart terminal such as the Web side and Android APP.(3)This paper focuses on the data fusion algorithm for multi-sensor data in the entire transportation process.In this paper,the data mining algorithm is used for data fusion.The collection of a large number of vehicle operating parameters is analyzed and studied,and the processing method suitable for this data is a clustering algorithm K-means algorithm.The traditional K-means is introduced.The basic concepts,algorithms and examples of the clustering algorithm are analyzed,and the traditional K-means are improved.Through example analysis and comparison of results,it is found that the improved K-means algorithm is significantly superior to the traditional algorithm in terms of classification effect.Then,the improved K-means algorithm is integrated with the monitoring platform system to evaluate the real-time status of the vehicle.In the end,this paper tests the monitoring platform,realizes multi-sensor data acquisition,data transmission,low-level interface display and two different remote display interfaces.At the end,the deficiencies and improvements of this paper are proposed.