Research And Application On Condition Monitoring Of Gearbox Based On LCD And Its Improved Algorithm

Gearbox is a vital part of the rotary machine,the fault of gearbox always leads to the failure of entire rotary machine and equipment.Hence,as for gearbox,it's of great significance to monitor its operating condition and study its fault diagnosis.The first essential in gearbox fault diagnosis is to extract its fault features.Generally speaking,when a gearbox breaks down,the signal of the gearbox part is nonlinear and non-stationary.Cubic Hermite interpolation—Local characteristic-scale decomposition(CHLCD)is an adaptive signal processing method which can extract fault features of the non-stationary signal effectively.Therefore,CHLCD can be applied to process the nonlinear and non-stationary signals.As a consequence,this paper apply CHLCD method in the fault diagnosis of gearboxes.The main work of this paper is as follows:According to the main structure characteristics of gearbox,failure modes of gear and rolling bearing have been analyzed,failure mechanism and causes have been studied intensively.The gearbox fault diagnosis method based on vibration signals has also been probed.The basic theory of CHLCD has been studied.According to the simulation,it can draw a conclusion that CHLCD has advantages over LCD.The effectiveness of CHLCD in the rolling bearing fault diagnosis has also been verified by the experiment.Aimed at the characteristics of the gearbox composite fault,application of CHLCD in the gearbox composite fault diagnosis has been studied.Combining CHLCD method and Blind source separation,this paper has proposed the CHLCD-BSS method.The effectiveness of CHLCD-BSS has also been verified by the simulated signals and the real tests of the gearbox composite fault diagnosis.In allusion to the mode mixing of the CHLCD method,the high frequency harmonic signal has been introduced in the decomposition of CHLCD method.Thus the problem of mode mixing has been solved effectively.According to the simulated signals,it is shown that the improved CHLCD method has advantages over original method.Meanwhile the combination of the improved CHLCD method and neural network has been applied in the real fault diagnosis of the rolling bearing.Finally,summary of this paper has been made and suggestions for following work has also been given.