Integrated Modular Avionics Anomaly Detection Based on Symbolic Time Series Analysis
Traditional avionics systems are federated architecture,and they are gradually replaced by integrated module avionics(IMA),which can share hardware and software resources within one cabinet.As IMA in civil aircraft becomes more popular,the maintenance,safety and supportability have gradually revealed their importance.In order to ensure the safety operation of the system,it is essential to implement prognostics and health management(PHM)to detect anomalies in time so that the real-time prognostics can be achieved.In this paper,an IMA anomaly detection method based on symbolic time series analysis is proposed.Through the study of failure modes of IMA system,a simulation experiment system was designed to acquire data which can reflect the health status of IMA.The experiment data is symbolized to build upon the D-Markov model and then the anomaly can be measured.These results show that STSA can effectively detect the anomaly of IMA.Besides,this method is able to detect the anomaly that cant be detected by the threshold,which is of great value to guarantee the normal operation.
integrated modular avionics anomaly detection symbolic time series analysis
Sifan Lei Lin He Yang Liu Dong Song
School of Aviation,Northwestern Polytechnical University Aviation Industry Corporation of China the First Aircraft Institute Xian,China
国际会议
重庆
英文
2095-2099
2017-03-25（万方平台首次上网日期，不代表论文的发表时间）