The Early Weak Signal Detection Of Mini Excavator Slewing Bearing Based On Chaotic Oscillator

In engineering applications, the slewing bearing is the key component of largelow-speed and heavy-load equipment, at the same time is also a kind of damageableparts. Because this type of equipment bears low-speed and heavy-load, it is easy tocause plastic deformation of the ball and raceway and other fatigue damage. When theslewing bearing exists potential small fault and long-term is operated, it may lead toaccident happened, such as effectting machine to work properly and even result toenormous economiclosses. Because it’s inconvenient to disassembled, maintenancecosts is high, easy to cause waste of resources, and even exists uncertain factors,Detectting whether slewing bearing has wear or other defects is very difficult. Thefault identification and diagnosis of slewing bearing has a great research significanceand practical application value. In order to detect the early weak fault signal inadvance, the major research of this paper is that intermittent chaos phenomenon ofDuffing oscillator is applied to detect Weak fault signal frequency in Mini excavatorslewing bearing.The main work of the subject includes the following:(1) The several typical chaotic dynamics model has been researched, Such asDuffing system, Lorenz system, Logistic system and deformation Rossler system, etc.Researched the damping, amplitude of Periodic perturbative force, initial conditions,and other parameters, which has a great influence for chaotic systems.(2) Researched the judgment criterion of chaotic oscillator. At the same time, weuse the Poincare section, Lyapunov index method to determining critical state of deformation Rossler system from a different angle.(3) Deformation Rossler system detects the amplitude of a weak signal withnoise. Through the analysis and comparison of several typical chaotic systems inweak signal detection, deformation Rossler system has certain advantages. Meanwhile,the methods of detection unknown frequency signal are introduced.(4) Because the traditional fault diagnosis method to detection the early weaksignal has disadvantages, In order to better detect the fault characteristic signal. Weuse chaotic system which its sensitivity to weak signal and the noise immunity, andcombination of wavelet analysis to detect Weak signal. The method used inengineering practice can effectively detect the weak fault signal.