Vibration monitoring and analysis of ball bearing using GSD platform

Abstract

Today, rotating machines plays an important function in foundry and forging plant. In these cases, the most significant elements of rotating machinery is bearing. Maintenance methods namely preventive maintenance, breakdown maintenance and predictive maintenance are carried out in the rotating machines. Fault diagnosis of machine bearing is done through vibration analysis of the bearing under preventive maintenance. The main purpose of the present work is to identify the faults of the bearing in a mechanical device by the acquisition of vibration signals from the bearing using Data Acquisition system. This analysis is done at different speeds and load conditions along with the different proportions of contaminants. The vibration signal is acquired by a modular hardware setup comprising piezoelectric accelerometer. The signals are analyzed by using the Laboratory Virtual Instrumentation Engineers Workbench (LabVIEW) software. The challenges in the time domain analysis are solved by using frequency domain analysis with power spectrum module. Power spectrum is used for comparison between the good and defective or bad bearing that are based on the various proportions of contaminant (Green Sand (0.2%,0.6%, and 1%)) included in the bearing.