A HERTZ-LEONARDO VINCI MODEL REVISITED-BEARING BALL RACE NON CONFORMITY SPINNING FRICTION AND FAULT PREDICTION BY USING VIBRATION ANALYSIS AND INTELLIGENT METHODS

摘要

Leonardo da Vinci had numerous designs for mechanical engineering developments. He spent much of his time analyzing bearings, linkages, gears and numerous other mechanical transmission modes. Many of Da Vinci's ideas are still memorable in the engineering world today. Hertz stress-life advocates for ball and roller bearings respectively, The Lundberg-Palmgren prototypical was recycled to predict the life of commercial. In recent year roller bearings will goes under predict bearing lives. Tests were conducted with bearing No.6204, Accelerometer used in the experiment is ADXL335 3-Axis Accelerometer works on 3V power supply, and it is an analog device and having a bandwidth range of 0.5Hz to 1600Hz. The microcontroller to be used is Aurdino UNO DAQ's which is needed to use the ADXL 335 accelerometer for getting the data of Vibration of Faulty Bearings. Empirical mode decomposition (EMD) is a self-adaptive investigation method for signal process. The EMD method is highly efficient in non-stationary and nonlinear data analysis. It has been widely applied to fault diagnosis of rotating machine. In this paper, a classification technique based on correlation coefficient was present, which can originate a one-on-one relationship between IMFs which decomposed from dissimilar signals by EMD method. And then, the feature of each IMF is extracted and calculated by using Support vector machines (SVMs). That will mark the intelligent fault diagnosis.