Angle Domain Average and CWT for Fault Detection of Gear Crack

Abstract

Run-up and run-down are of particular interest in condition monitoring of gearbox as they highlight many unobservable system faults. However, varying speed machinery faults detection is fraught with difficulties due to non-stationary machine vibration. Fixed time sampling cannot cope with the varying rotational frequency of the machine, resulting in increasing leakage error and spectral smearing. In order to process the non-stationary vibration signals during run-up and run-down of gears drive effectively, the angle domain average (ADA) technique is combined with the continuous wavelet transform (CWT), which is applied to vibration analysis of gear for the detection of failure. Firstly, the vibration signal is sampled at constant time increments and then is re-sampled at constant angle increments. Therefore, the time domain non-stationary signal is converted into angle domain stationary one. In the end, the re-sampled signals are analyzed using continuous wavelet transform. The experimental results show that the presented method can effectively diagnose the faults of the gear crack.