Hardware Development Platform For Vehicle Operation Condition Monitoring And Fault Early Warning System Based On Cloud Computing

In many industries,such as the automotive industry,predictive maintenance is becoming more and more important.Since most of the sensors are single-signal variables,it is difficult to diagnose faults in advance during vehicle operation.Vehicle repair companies such as 4S shops can only analyze and maintain vehicle faults through on-site inspections.In this paper,a hardware development platform for vehicle braking system fault prediction is proposed.As the vehicle assembly system such as transmission,hydraulics,entertainment,etc.,is highly homogenized for data acquisition,analysis,warning,and transmission.Therefore,the author expands the hardware development platform for vehicle operating condition monitoring and fault early warning system based on cloud computing by analyzing the status of vehicle brake condition monitoring and fault early warning.In the future,reference can be made to the condition monitoring and fault early warning hardware of the brake system.The vehicle brake warning system can be well extended to other systems.This article is based on the MC9S12DG128 microcontroller to complete the road slope,temperature and humidity environment,the operation of the collection,and ultimately will generate a road braking friction coefficient.Then through the vehicle load,front and rear brake temperature acquisition,vehicle acceleration,vehicle speed and brake pedal trigger timer data acquisition.This paper mainly includes the application of Internet of Things technology in automobiles.Based on the analysis of the failure status of automobile brakes,this paper introduces the data transmission chain of automobile body sensor network and the auto OBD-CAN interface to complete the extraction of effective vehicle information.The final generation of a dynamic braking distance model compares with normal to produce an early warning effect.In the early warning process of brake aging or excessive braking distance under a line(single-chip microcomputer processing),the data is stored in EEPROM in a software manner during this process.At the same time,the data is transmitted to the data storage cloud through Zigbee or 4G wireless mode.,or through the wireless network to upload data to the PC(analog cloud)for third party analysis and use.This article focuses on hardware design and implementation.It also uses software to collect sensors and analyze and process data.The cloud is only used as a cut-in point.In the future,it can be analyzed andcompared based on the collection of a large number of vehicle data to determine whether there is a potential fault in the vehicle.Stores and other car maintenance companies feedback early warning information.