Statistical Feature Extraction in Machine Fault Detection using Vibration Signal

Gearbox faults are one of the most common types in the industrial factory environment. Early detection of these faults allows fast replacement rather than a costly emergency. Nowadays, early machine fault detection application is improving due to the improvement of the IoT network and real-time analysis. The vibration signal is collected from Spectra Quest's Gearbox Prognostics Simulator and analyzed for fault classification. The preprocessing includes fast Fourier transform and statistical feature extraction. The AI algorithms are Artificial Neural Network, Logistic Regression, and Support Vector Machine. The highest accuracy reached is 100%.