Comparación de Señales de Vibración y Emisión Acústica para la Detección de Diente Roto Mediante la Transformada Rápida de Fourier, Transformada Hilbert y Cepstrum

In industry gearboxes are widely used as power transmission systems. Therefore, it must be in nominal operating conditions, hence the need to monitor the condition using predictive techniques such as: acoustic emission and vibrations. Consequently, the early detection of possible failure modes and the assessment of their severity in these equipment is a significant field of research. This article takes advantage of condition monitoring techniques (acoustic emission, vibration analysis), to compare them in the detection of broken tooth with three levels of severity by comparing vibration spectra resulting from signal processing using the fast Fourier transform, Hilbert transform and Cepstrum. For this, a methodology composed of two phases is used: the first of acquisition of vibration signals and acoustic emission, which goes from the conditioning of the vibration bank to the lifting of the databases under normal conditions and with failure. The second phase corresponding to the comparison of signals begins with the entry of the signal into the data processing software (MatLab), which allows to compare the spectra in terms of frequencies and amplitudes between vibration signals and acoustic emission through the visual comparison of spectra and tabulation of data. The results show that more information was obtained for the identification of the severity of failure in broken tooth through the use of the Hilbert transform and Cepstrum analysis for vibration signals and acoustic emissions, because the gear amplitude (GMF) increases as the level of severity increases.