Research On Vibration Signal Of Rolling Bearings Based On Wavelet Theory

Rolling bearings are one of the most widely used mechanical parts in rotating machines but they are also easily to be damaged. Quality of rolling bearings affects the stability of the whole system. Nowadays when checkers in the companies that manufacture the rolling bearings for normal use distinguish the faulty bearings from eligible ones they based nearly on their personal sense. So personal subjective affect is hard to be eliminated. And the result will not be very good. It makes some faulty bearings enter the market and give birth to some safety hidden trouble. It makes sense to make a standard between broken bearings and eligible ones to prevent faulty bearings from entering the market. In this paper, characteristic information of faults is gained from rolling bearings outside vibration signals by using wavelet translation analysis method on the basis of former achievements and valid results are obtained.First, from the start point of formation of vibration signals, this paper discusses the rolling bearings'instinct vibration, nonlinear stiffness of inner, outer race and rolling elements, vibration caused by assemble error. Then we build up the theory model for each component of rolling bearing when they have a defect on them, analyze the character of the vibration signal for each type of rolling bearings. It provides theory foundation for fault diagnosis.Then, contrast with the traditional method of fault diagnosis, we introduce the energy-fault method. This method classifies the bearings into two categories: eligible ones and faulty ones. Then we extract the characteristic signal of faulty bearings through spectrum analysis.Finally, after we analyze a large number of experimental data, the result is satisfactory It proves that the method we used is correct and it also means that wavelet analysis is one of the most useful methods on faults diagnosis of rolling bearings.