Abstract
Abstract In order to solve the difficult problem of fault diagnosis in aviation equipment, this paper uses a biomimetic pattern recognition method. Compared to traditional pattern recognition, biomimetic pattern recognition is able to construct closed, complex geometries to cover all kinds of samples. Biomimetic pattern recognition is a “cognitive” approach, where the process between two similar things is considered asymptotic. It mathematically means that all similar samples in the feature space are continuously indistinguishable. The paper establishes a dual-weighted neural network model of an aircraft auxiliary power unit. Comparing the diagnostic process and results with traditional manual neural networks. The results show that biomimetic pattern recognition is a feasible and efficient diagnostic method for the fault diagnosis of aviation equipment. It provides a new way of thinking and method for the practical application of aviation equipment fault diagnosis.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
