Wavelet transforms coefficients and autocorrelation of gear system for early damage detection

In the last few years, numerous new methods have been proposed to overcome the complexity of the signals generated by complex machines and those generated by faults. Monitoring and fault diagnosis methods based on signal processing have proved effective in fault identification. The present paper introduces the theory of wavelet transforms coefficients (WTC) processes and autocorrelation as powerful tools for the diagnosis of rotating machines. This method is applied to for the analysis of vibration signals produced from a gear system under test in order to early detect the presence of faults. An early indication of the presence of a gear defect is obtained at the 10th day of experimentation.