Anomaly detection of aviation data bus based on SAE and IMD

Li, Huang; Sang, Yiqin; Ge, Hongjuan; Yan, Jie; Li, Shijia

doi:10.1016/j.cose.2023.103619

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2024

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Cited by 3 publications

References 24 publications

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Anomaly Detection for Aviation Cyber-Physical System: Opportunities and Challenges

Ain,

Aftab Ahmed Jilani,

Azhar Butt

et al. 2024

IEEE Access

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Anomaly Detection for Aviation Cyber-Physical System: Opportunities and Challenges

Ain,

Aftab Ahmed Jilani,

Azhar Butt

et al. 2024

IEEE Access

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Anomaly Detection Model-Based Analysis of Aircraft Flight Data

Wang,

Huang,

Chen

et al. 2024

2024 IEEE 2nd International Conference on Control, Electronics and Computer Technology (ICCECT)

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Artificial Intelligence for Real-Time Tolerance to Critical Flight Data Errors in Large Aircraft

Koopman,

Zammit-Mangion

2024

Journal of Aerospace Information Systems

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The environment in the cockpit of large transport aircraft is highly complex due to an increasing number of automation systems. This complexity can cause pilots to become less aware of how systems interact. It becomes a severe issue when sensor or data failures occur, as such failures can contribute to a situation in which it is difficult for a pilot to assess what actually is happening and, possibly, how to resolve the problem. This paper presents a method, based on artificial intelligence, for identifying incorrect critical flight control data in real-time. A novel combination of reinforcement learning and a denoising autoencoder is proposed to identify failures and to provide inputs to the aircraft’s flight control and guidance systems, allowing for the correct maneuver to counter the failure and/or to avoid or recover from flight upsets. Tests in stall conditions with a partially blocked pitot tube show that the proposed method results in successful detection and recovery. The performance of the system without an autoencoder is compared to highlight the significant advantages, how this relates to creating systems with AI to improve situational awareness for pilots, and to execute appropriate automatic maneuvers to successfully counter the effect of sensor failures.

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Anomaly detection of aviation data bus based on SAE and IMD

Cited by 3 publications

References 24 publications

Anomaly Detection for Aviation Cyber-Physical System: Opportunities and Challenges

Anomaly Detection for Aviation Cyber-Physical System: Opportunities and Challenges

Anomaly Detection Model-Based Analysis of Aircraft Flight Data

Artificial Intelligence for Real-Time Tolerance to Critical Flight Data Errors in Large Aircraft

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