Extracting periodically repeating shocks in a gearbox from simultaneously occurring random vibration
Abstract
Periodically repeating shocks are a quite common indication of certain defect in machinery. Detecting these shocks in early stage, before the defect is severe enough to cause failure, can provide a huge advantage in maintenance planning. The earliest possible warning of a defect may be highly important, especially in targets where failure can lead to vast loss of production or a safety risk. Shock-like vibrations are, however, usually rather faint when the defect is a minor one. This simply means that the shocks may often be too low in magnitude to be easily detected. In this paper we use different techniques based on real order derivative to detect gear defects.
Higher real order derivative, discrete Fourier transform, and Hilbert transform are discussed.
Higher real order derivative, discrete Fourier transform, and Hilbert transform are discussed.
