Semi-structured Real-time Data Acquisition Technology Based on Big Data Cross-platform
Aiming at the problem of the single function and low clock frequency of traditional data acquisition technology cannot meet the needs of current development,this paper designs a semi-structured real-time data acquisition system.It uses FPGA for parallel data processing,and adopts the nested ping-pong cache method for data caching,which realizes real-time data pro-cessing and FLASH storage,and enhance the reliability and stability of data transmission and storage.The remote collection system for semi-structured real-time data is designed.The REMOTE process is adopted to improve the fault diagnosis ability through the fire big data algorithm model.Experiments show that the proposed system takes at least 22 s to collect 20 000 pieces of data,the accuracy of the collected data reaches up to 98％.The fire fault diagnosis speed is faster and the auuracy is higher,which greatly improves the diagnosis efficiency and response ability of fire fault.
data acquisitionbig dataFPGAsemi-structuredremote acquisitionfault diagnosis
万方数据
维普
