| With the enactment and implementation of increasingly stringent emission regulations,diesel particulate filter,which is the most effective technical means of controlling diesel particulate matter emissions,has become a widely used and indispensable after-treatment product for diesel particulate matter emissions control.If the diesel particulate filter breaks down in the process of working,which is not found and dealt with in time,it will lead to the decrease of the working efficiency of the diesel engine and the exceeding of the emission of particulate matter.At the same time,the owner may tamper the diesel particulate filter for cost reasons,such as dismantling it.Aiming at the remote monitoring requirements of pollution control devices in some national standard documents like GB17691-2018,and based on the domestic and international research on the development of diesel particulate filter status parameters and remote monitoring systems,this subject realized the condition monitoring and analysis system of diesel exhaust particulate filter which used Embedded technology,Internet of Things technology and Web application development technology.The system is composed of two parts,one is the on-board data acquisition terminal,and the other is the big data display and analysis platform.The on-board data acquisition terminal was developed through the integration of Embedded technology and Internet of Things technology.The terminal realized the condition monitoring of diesel particulate filter and uploaded the data to the cloud for storage.The on-board data acquisition terminal is composed of the following modules:main controller,diesel particulate filter status information collection unit,location collection module,power module,SD card storage module,wireless transmission module,LCD display module and warning unit.This subject select STM32F103RCT6 as the main controller of the terminal.The diesel particulate filter status information collection unit collects three status characteristic parameters,including the pressure difference at both ends of the diesel particulate filter,the different temperatures at the ends of the diesel particulate filter and the particle concentration at the exhaust port.If the abnormal information of diesel particulate filter is detected,the owner will be warned by the warning unit.The collected data is displayed in the LCD display module,stored by the SD card storage module,and then uploaded to the Internet of Things cloud platform through the 4G wireless transmission module.According to the interference problem of pressure difference signal and temperature signal,a filtering algorithm combining Median filtering and First-order hysterical filtering is used to reduce the noise and burr interference in those signal,so that the data can reflect the state of the diesel particulate filter more truly.The big data display and analysis platform is based on B\S architecture,and adopts the separation mode of front-end and back-end for segmented development.The database of the platform is composed of My SQL and Redis.The back-end project of the platform is constructed by Spring Boot and My Batis Plus,and the front-end project of the platform is constructed by Vue and Element UI.The platform is designed with four functional units: data center,track management,information maintenance and system setting,which realize diversified display of cloud data,vehicle position monitoring and over-area judgment combined with Baidu Map,maintenance of relevant data in the platform and other functions.The diesel exhaust particulate filter status monitoring and analysis system designed by this project was tested.The test results show that the system meets expectations and can run stably.The system has practical significance for reducing the probability of diesel engine working efficiency decrease and particle matter overdischarge caused by diesel particulate filter failure or tampering,and is conducive to improving the safety of diesel particulate filter.The diesel exhaust particulate filter status monitoring and analysis system can access the supervision platform according to required,and form a more refined and complete supervision network of particulate matter emission,making substantial contributions to energy conservation and emission reduction. |