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Time Series ARIMA Model for Failure Prediction of Landing Gear Retraction/Extension System

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DOI: 10.23977/icasit.2019.026


Yanda Chen, Jian Gu, Zheng Han

Corresponding Author

Yanda Chen


Airplane equipment failures will bring hidden dangers to flight safety. Timely detection and maintenance of problems can not only better ensure flight safety, but also enable airlines to avoid huge losses caused by accidents. Therefore, it is necessary to scientifically predict system failures and provide data support for maintenance. This paper calculates the historical data of the main landing gear retraction and extension cycle time of the A320 fleet, and establishes a seasonal ARIMA model to predict the possibility of failure of the landing gear retraction/extension system. Finally, it is found that the retraction time of the left main landing gear of an aircraft has a tendency to slow down recently, and will exceed the time range required by the AIRBUS manual after half a year, which may bring the risk of unretractable after takeoff. Through inspection, it is caused by the fatigue wear of the actuator, and the normal working level is restored after timely replacement. The research results show that the SARIMA model is feasible and effective for predicting the failure of landing gear retraction/extension system.


Landing gear, system failure, seasonal ARIMA model, retraction/extension system

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