Research on Fault Diagnosis and Intelligent Maintenance Technology of Airborne Electronic Equipment

© 2026 by the Authors. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )

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Abstract

With the increasing integration and complexity of avionic systems, fault diagnosis and intelligent maintenance technologies for airborne electronic equipment have become critical supports for ensuring flight safety and improving equipment integrity. This paper systematically reviews the research status and development context of fault diagnosis technologies for airborne electronic equipment. It summarizes major research achievements and technological advances in the field from the perspectives of traditional fault diagnosis methods, integrated intelligent diagnosis strategies, artificial intelligence-driven technologies, data-driven methods, and intelligent maintenance assistance systems. On this basis, core bottlenecks in current research are analyzed, including data dependency, poor model interpretability, and insufficient generalization ability. Future development directions are prospected, such as few-shot learning, explainable AI, digital twin, and edge intelligence.

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