Flight operations quality assurance based on clustering analysis

Abstract

Flight operations quality assurance (FOQA) can be applied to monitoring and analyzing the data recorded in a flight to improve line operations and safety. In view of the requirements of FOQA and the shortage of general data processing algorithms, clustering analysis and density-based spatial clustering of applications with noise (DBSCAN) algorithm are studied depending on data mining, and FOQA based on clustering analysis is presented. The process of flight data analysis is discussed with this algorithm. The practicability and universality of DBSCAN algorithm is validated by the clustering analysis instance of an abnormal data during takeoff. © 2014 Springer-Verlag.