Research on Fault Prediction Technology of Air Compressor Based on Wavelet Neural Network

The air compressor supply is the main gas source equipment for the water supply system of civil aviation aircraft. As a piece of complex electromechanical equipment, various faults become apparent with the increase in usage time. If the faults are not dealt with promptly, they will affect the equipment's performance and system function. In this paper, based on the working principle and structural characteristics of the air compressor, the main fault modes are analyzed, and the characteristic parameters are determined. The wavelet neural network algorithm is used to establish a fault prediction model. Based on the collected characteristic parameters, the service life of the air compressor is predicted, which improves the proactivity, guidance, and efficiency of maintenance support, enhances the availability of equipment, and provides technical support for airlines to reduce operating costs and improve customer satisfaction.