Gear fault assessment based on continuous wavelet transforms

A gear system transmits power by means of meshing gear teeth and is conceptually simple and effective in power transmission; thus typical applications include electric utilities, ships, helicopters and many other industrial applications. Monitoring the condition of large gearboxes in industries has attracted increasing interest in recent years owing to the need for decreasing the downtime on production machinery and for reducing the extent of secondary damage caused by failures. Currently there are three different approaches to the detection of faults in geared systems: vibration analysis, oil/wear particle analysis and acoustic signal analysis. The use of vibration and acoustic signals is quite common in the field of condition monitoring of rotating machinery. This paper focuses on the application of wavelet transforms for detection of the local faults of the gear teeth of the helical gear transmission system. Seven conditions of the gear were investigated: healthy gear and gear with six stages of depth wise wear induced on the gear tooth by grinding operation. The experiments were conducted on a gear box with good gear and gears with various stages of gradual depth wise removal of tooth surface and the signals have been processed using wavelet transforms. Diagnostics has been done using wavelet transform of not only the vibration signals, but also wavelet transform of acoustic signal and wavelet transform of the cross correlation between the vibration and acoustic signals. The latter has not been reported earlier in literature and gives conclusive diagnostic information. © KRISHTEL eMAGING SOLUTIONS PRIVATE LIMITED.