Advanced Fault Detection in Aircraft Motors Using Vibration Analysis Through Floating-Point FFT

Aircraft motor faults pose significant risks to safety and operations, necessitating precise and proactive detection methods. Traditional maintenance approaches often fail to identify such faults early, highlighting the need for advanced solutions. This paper presents a high-precision, real-time floating-point Fast Fourier Transform (FFT) algorithm designed for fault detection in aircraft motors via vibration analysis. By converting time-domain signals into the frequency domain, the proposed algorithm identifies faults with exceptional accuracy, leveraging floating-point arithmetic to enhance precision and reliability. Optimized for FPGA implementation, the algorithm supports continuous monitoring of motor components, enabling predictive maintenance strategies that reduce failure risks and enhance operational safety. The project establishes a comprehensive framework for early fault detection, paving the way for advancements in aviation safety and maintenance technologies of aircraft.