Gears and bearings are critical components in rotating machinery, which are responsible for many malfunctions or failures of related equipment. In this solution, the signal processing, feature extraction and selection processes are implemented for these components, which are the important preprocessing steps before delving into diagnosis and prognosis. case studies are presented using the vibration signals in normal and faulty condition collected for various gears and bearings.