Based On The Local Characteristic-scale Decomposition To Diagnose The Gear

Gear is the mechanical equipment indispensable connection and powertransmission parts.It has the vital role in the machinery and equipment. But because ofthe complexity of the structure of the gear, working conditions and human factors, thegear is particularly vulnerable to damage and malfunction parts. If the damage geardose not be found in time, it will cause great loss to the entire production and social.So the gear fault diagnosis is very important.The key of gear fault diagnosis is extracted the gear vibration signal fault feature.Signal analysis and processing is the most commonly used method of extracting faultfeatures. However, the gear fault vibration signals are mostly unstable, nonlinear andtime varying signal, so it is important to choose a suitable signal analysis method. Asgear vibration signal is closely related to the gear state, and which often contains agreat deal of fault information, for the non-stationarity, modulation andmulti-component properties of gear fault signal, in this paper, a new kind ofself-adaptive time-frequency analysis method—Local characteristic scaledecomposition (LCD) is applied to gear fault diagnosis. The paper is also introducedcespstrum method, Energy moment method and wavelet energy spectrum method. TheLCD method and the several methods are used in gear vibration signal analysis in thispaper. The experimental results are showed the effectiveness of these methods.The main research contents of this paper are as follows:1.In this paper, a new kind of self-adaptive time-frequency analysis method—Local characteristic scale decomposition (LCD) is proposed. By using LCDmethod,each complicated signal can be decomposed into a number of componentswhose instantaneous frequencies own physical meaning. So the analysis results showthat the LCD method is effective.But the LCD method also has some flaws andshortcomings.With the studying of the LCD method,some improvement isproposed.When used the improved LCD method to decompose the complicatedsignals, it is found that the components are more smoothness.2. Aiming at the characteristic that gear fault vibration signal is composed ofseveral AM(amplitude modulation)-FM (frequency modulation) components, the Bspline-based Local characteristic-scale decomposition method (BLCD) and cespstrummethod are applied to gear fault diagnosis. The analysis results show that BLCD method can be applied to the gear fault diagnosis effectively.3. The spline-based Local characteristic-scale decomposition method and energymoment are combined and applied to gear fault diagnosis. With the analysis of thenormal gear and the fault gear,the results show that this method can be applied to thegear fault diagnosis effectively.4. The gear vibration signals are decomposed adaptively into some intrinsic scalecomponents by using the rational spline-based local characteristic-scaledecomposition (RLCD) method. The experimental results show that based on theRLCD method and bispectrum method can be effectively applied to gear faultdiagnosis.It is also proposed a new method to analyse the gear vibration signals.