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Research On Monitoring Method Of Accuracy Degradation Process Of Planetary Cycloid Reducer

Posted on:2022-12-09Degree:MasterType:Thesis
Country:ChinaCandidate:M X LinFull Text:PDF
GTID:2518306788958149Subject:Automation Technology
Abstract/Summary:PDF Full Text Request
The precision degradation experiment of the planetary cycloidal pinwheel reducer for industrial robots is carried out by using the reciprocating swing method,which can better reflect the accuracy degradation of the reducer in actual work.However,during the reciprocating swing experiment,the speed and direction of the reducer are changing at any time.Therefore,it is difficult to locate the fault source of the reducer by using traditional spectrum analysis to analyze the vibration signals collected during the experiment.In this paper,based on the experimental condition of the reducer swing fatigue,the monitoring method of the reducer in the process of accuracy degradation is studied.The specific contents are as follows:(1)In order to meet the monitoring requirements of the planetary cycloidal pinwheel reducer during the fatigue test process,an order tracking analysis method is proposed in this paper.The non-stationary vibration signal is equiangularly resampled by programming with MATLAB,and the stationary angle domain signal of the vibration signal is obtained,and then the order analysis diagram is obtained by performing Fast Fourier Transform(FFT)on it.;At the same time,according to the working transmission principle of the reducer,the order characteristics of the planetary gear,cycloidal wheel,crankshaft,needle roller and crankshaft bearing of the reducer are calculated.By comparing the vibration signal order diagram of the reducer before and after the failure,the failure of the planetary cycloidal pinwheel reducer at the needle roller can be accurately located.The monitoring of the precision degradation process of the planetary cycloid reducer is realized.(2)In the process of precision degradation experiment of the reducer,in order to obtain more intuitive and accurate monitoring results,this paper uses the analysis method combining Empirical Mode Decomposition(EMD)and order tracking analysis.The angular domain stationary envelope signal is obtained by resampling the collected time domain signal in the equiangular domain.The empirical mode decomposition of the stationary envelope signal in the angular domain is performed to obtain multiple intrinsic mode functions(IMFs)for kurtosis calculation and reconstruction.Perform order analysis on the reconstructed equiangular domain signal.The results show that the method can more accurately and intuitively locate the failure of the needle roller part of the planetary cycloid reducer.(3)In order to save the monitoring cost,the order tracking analysis method without tachometer is used to monitor the accuracy degradation process of the planetary cycloidal pinwheel reducer.Using MATLAB programming to perform low-frequency filtering and short-time Fourier transform(stft)on the time-domain vibration signal to determine the instantaneous rotational frequency of the reference shaft,the expression of the rotational speed pulse signal of the planetary cycloidal pinwheel reducer is obtained by fitting Mode.Then,through the order tracking analysis,the envelope order analysis diagram of the vibration signal can be obtained,which can accurately locate the obvious wear on the needle roller.This method can monitor the planetary cycloidal pinwheel reducer without arranging the speed sensor,which saves the monitoring cost.(4)In view of the problem that the fault signal of the planetary cycloidal reducer has a lot of noise and it is difficult to extract the fault features,this paper uses the method of improving wavelet threshold noise reduction and order tracking analysis to analyze the fault signal.The results show that the method can effectively improve the signal-to-noise ratio of the fault signal,the noise reduction effect is obvious,and the fault at the needle roller can be accurately located.
Keywords/Search Tags:planetary cycloid reducer, order tracking analysis, empirical mode decomposition, Wavelet Threshold Noise Reduction, fault diagnos
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