Gear Fault Identification by using Vibration Analysis

Abstract

Nowadays it is becoming more essential and reliable to predict the performance of gear box without dissembling the gear box. It is possible to predict the fault and fault conditions in case of any rotary machinery by using vibration analysis with the help of FFT analyzer and its accessories. In this paper, the similar kind of experimental setup is prepared and the vibration analysis is carried out at different speeds to analyze the behavior of time waveform and FFT spectrum for three different fault conditions. The gear pair of Bajaj Pulsar gear box is taken and the faults are created on pinion and the vibration behavior is observed. The three fault conditions are single tooth damaged pinion, double teeth damaged pinion and worn pinion. Also some of the numerical techniques like RMS value and variance are used for comparing the behavior of faulty pinion with respect to healthy pinion. Vibration analysis using FFT successfully identifies gear faults including single tooth damage, double teeth damage, and wear. Time waveform and FFT spectrum analysis with RMS and variance values detect fault severity. At 300 rpm (5 Hz) for single tooth damaged pinion, the damaged tooth comes in mesh with the mating gear once in each revolution. As the pinion is rotating at 5Hz i.e.5 revolutions per seconds, means one revolution of pinion is completed in (1/5) seconds. As the damaged tooth comes in mesh, the large impact happens on the next tooth. Hence, the peak is observed after every 0.2 seconds. At 300 rpm (5 Hz) for double teeth damaged pinion, the damaged teeth come in mesh with the mating gear twice in each revolution. The magnitude of RMS value and variance is greater in case of worn pinion than the healthy pinion. It can be concluded that the fault like wear can be identified by using various computational techniques like RMS and variance.