Prediction of Fault Detection Based on Vibration Analysis for Motor Applications

Vibration Analysis on motor parts has been done before fitment to detect minute surface and sub-surface cracks and other defects. While there are many other fault detection methods, vibration analysis has been used due to its low requirements in equipment, resources and fast data acquisitions. Vibration Condition Monitoring is the process through which the current working condition of a machine can be ascertained by using vibration analysis. This paper deals with the condition monitoring and prediction of faults in a two- motor. Since each part in the motor is distinct, during working, each part produces its own distinct vibration signature. Using accelerometers an ADXL 335 and an in- built Smartphone accelerometer, the vibrations produced were recorded. Faults were introduced into the motor by replacing the normal parts with faulty parts. These data were imported to MATLAB software. From the vibration data recorded before and after the introduction of the faults, time and frequency domain plots were created. This work present a method for fault detection of motor using vibration signals and with use of FFT, location of fault can be detected.