Landing Tail-Strike Risk Pattern Identification and Prediction Based on Functional QAR Data

Tail striking is a typical safety event in the area of civil aviation, which is directly related to the aircraft pitch angle at landing. Based on 2933 A319 flights’ non-exceedance quick access recorder (QAR) data from Dali airport, the relationship between key flight parameters during the final approach and landing pitch angle is explored. Functional data analysis and the Group Lasso method are used to select the most important flight parameters, and cluster analysis and weighted logistic regression are used to identify and predict a “high-risk” flight pattern. Here, “high risk” refers to a flight pattern associated with a higher probability of large landing pitch attitude, which is used as a proxy indicator of potential tail-strike risk rather than as evidence of an actual tail-strike event. Finally, flight operation recommendations are provided. The research results indicate that the airspeed, pitch angle and engine speed are most closely related to the landing pitch angle. An unusually high-risk flight pattern is identified, characterized by “high airspeed, high attitude, low thrust” caused by improper energy management of light-load flights. About 32.4% of flights in this pattern land with “large landing attitude”, which means the landing pitch angle is larger than the 95% sample percentile. A prediction model for the high-risk pattern is established using QAR parameters at the heights of 500 ft, 450 ft, and 400 ft, with an accuracy rate of 99.7% on the test data. The prediction in advance at 400 ft can provide pilots with sufficient time to take necessary operations.