In this paper, the mechanical sensitivity of a vibration sensor is investigated by developing a mathematical model with the function of a relative movement modulus and measurement error. This model enables mechanical sensitivity to be improved by enhancing the performance of the vibration sensor. The purpose of the present work is to reduce measurement error by choosing the right damping rate that enables vibration sensor sensitivity to be optimized. The presented model is validated by computer simulation and experimental tests. The obtained results have shown that correct choice of damping rate and frequency range keeps the mechanical sensitivity constant.
The present paper deals with healthy and improper bearing lubrication signals analysis using Discrete Wavelet Transform (DWT) enhanced by MATLAB/ Wavelets toolbox analysis. The identification of bearing faults from the time or the frequency domain are difficult due to non stationary vibration signal. Therefore, for more accurate faults information and identification of bearing with lubrication defects (improper or absence of lubrication), the DWT is used. The validation of this procedure is conducted by an experimental setup designed for vibration signal acquisition and the complete analysis is finalized by MATLAB/ Wavelets toolbox. The recorded data used for the validation are the signals of healthy and un-lubricated bearing driven at a rotation speed of 1500 rpm by 0.78 KW three phase induction motor. From the obtained results it can be observed that, for medium speeds DWT decomposition enhanced by MATLAB Wavelets Toolbox procedure is efficient for improper lubricated bearing related faults diagnosis and detection.
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