Design on internet of things for remote monitoring and fault diagnosis in deep mine shaft freezing construction

According to the technical difficultes of the internet remote monitoring and fault diagnosis for over 1 000 m deep mine shaft freezing construction,based on the rich internet RIA technology,an internet of things framework was provided. In the sensing layer,an"adaptive optimization driving- bus" 18B20 thermometry algorithm and node module were researched and developed with a measuring depth over 1 000 m. In the network transmission layer,a collection and recombination of site real time sensi ng data were realized and then the data would be transmitted to the middle ware of the internet of things in the cloud environment. In the application layer,based on the self learning probability statistics,a fault recognition and diagnosis algorithm was provided and the middleware of internet of things and the data center Web Service were devel oped based on the Flex agent and the Web application system of Java EE as well as based on the Flex strong interactivity Web man- machine interface. Finally,the internet of things and software were successfully applied to the deep mine shaft freezing construction project of Hetaoyu Mine with depth of 1 200 m,Shaanxi. The practices showe d that the internet of things system could remotely monitor and measure the real time data of the 1 200 m depth in freezing project with the internet. A fault recognition and diagnosis was conducted and visualization of the data curve diagram could be realized. A statistical analysis and management of the historical data could be effectively app lied to the remote guidance of freezing construction.