Advanced Fault Prediction Techniques Utilizing LSTMSA-Based Method in More Electric Aircraft Power Systems

In order to overcome environmental concerns and reduce aircraft operating cost, the concept of More Electric Aircraft (MEA) has been presented to in-crease aircraft efficiency and reduce maintenance requirement by increasing the use of electrical power. Given the pivotal role of electrical systems in ensuring aircraft safety and stability, fault prediction within these systems is paramount for mitigating malfunction risks and ensuring the secure operation of MEA. This paper explores fault prediction techniques for MEA power systems, proposing a novel Long Short-Term Memory and Self-Attention (LSTMSA)-based method that significantly outperforms conventional prediction techniques. The proposed method enhances the fault prediction capabilities of MEA power systems, providing more meaningful references during flight and bolstering overall flight safety.