Design And Implementation Of Avionics Comprehensive Analysis System Based On Big Data

In modern warfare,the operational environment of aircraft is becoming more and more complex,and various combat missions are increasingly inseparable from the support of avionics systems.A stable and well-functioning avionics system is the core of enhancing aircraft combat performance.In order to ensure the stability and safety of the avionics system,the avionics system needs to be simulated and tested before the avionics system is officially applied to the aircraft.During the analysis of the test data for many years,experts and engineers have summarized a lot of analytical experience,There are still problems with traditional test data monitoring and analysis techniques,cumbersome procedures,and strong dependence on personnel-related experience.In this study,we used the big data experiment platform to replace the Fibre Channel data monitoring card and the Fibre Channel simulation card.In addition,the K-means algorithm was used for data mining to provide a method for the knowledge acquisition of the expert system The fault tree analyzes abnormal data.The main work of the full text is as follows:1.In view of the inconsistency of the avionics data protocol adopted by the Avionics Research Institute,the data of each protocol type needs to be analyzed separately.A data preprocessing method based on a big data center is proposed to be compatible with data monitoring and data analysis in a multi-protocol format.2.Aiming at the development of avionics systems and the problem of the exponential growth of data to be transmitted and processed in the sharing of airborne resources,a big data experiment platform was proposed to replace the Fibre Channel data monitoring card and the Fibre Channel simulation card.So as to realize the timely and orderly classification storage and management of the data sent by the fiber channel.3.Adopt the concept of an expert system to transform expert expertise and technical documents in related fields into knowledge in the knowledge base,so that the system can analyze test data and perform fault diagnosis and processing based on the expert's knowledge experience and thinking mode.Through analysis and processing of test data,and capture abnormal data.Analyze the data to determine the type of anomaly and the cause.4.The system visualizes the test data based on various bus protocols.Users can consult real-time and historical test data,and can perform flow rate statistics on the monitoring data,and monitor and display the working status of the simulated device on the network.5.It is proposed to use the K-means algorithm for data mining,which provides a method for the knowledge acquisition of the expert system and reduces the dependence of the experimental data analysis system on the staff's field experience.The above work has been verified through system function testing,and the system has realized multi-protocol test data monitoring and analysis,flow statistics,and abnormal data monitoring.