Method of abnormal flight data correction without trend items monitoring sequence and its application

Abstract

Flight data can be divided into trend monitoring data and non-trend monitoring data according to trend components. The abnormal flight data with no trend item monitoring sequence affected the quality of flight data analysis. By introducing the interval of flight data interval, the isolated data cluster of flight data is established, sample cluster defined and Chebyshev inequality changed to Figure out the abnormal data, and the average value of the nearest normal data is used to make numerical correction. A modified example of the abnormal value of the fuel flow monitoring data of the Cessna172 aircraft verifies the effectiveness of the method, providing a reference for data-driven aviation safety risk management.