A Novel Likelihood Gradient-Based Incipient Fault Detection Approach for Avionics Systems

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Authors: K. Sun, Zhongmei Li, Bing Wang, Jialiang Wang, Hongtian Chen, Bin Jiang
Cited by: 4
References: 24

Abstract

This paper presents a gradient-based fault detection method for pitch control systems in avionics. On the basis of the dynamic model of the airplane, the proposed method detects both operator and sensor faults by monitoring the online data. By integrating fault-related behaviors over an extended time window, the method effectively amplifies small changes caused by incipient faults, improving detectability. Theoretical analysis reveals that under normal flight conditions, the gradient has a zero expected value and a finite, analytically tractable variance. These characteristics make the method compatible with traditional fault detection approaches. Sufficient tests on real flight data verify its ability to detect hard-to-identify faults.

Fields of Study & Subjects

Fault Detection and Control Systems Engineering and Test Systems Air Traffic Management and Optimization

Publication details

Journal / source
IEEE Transactions on Automation Science and Engineering
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
23
Pages
7880–7892
Publication date
1 January 2026