Research On Fault Strength Prediction Of Machinery Based On Full Vector Spectrum

Under the machinery at high-speed operation, once the key moving parts fault which will bring huge economic losses and personal injuries. In order to reduce losses to a minimum, fault strength need to be known early. Thus prediction of machinery fault strength is particularly important. Considering vortex dynamic characteristics of the rotor itself, vibration information that is achieved by different direction on the same section has differences. For this reason different spectral structures will be got. Therefore single-channel information cannot reflect the real vibration of rotor accurately. Considering incomplete vibration information that leading to poor consistency of predictive results, single-channel prediction method cannot realize accurate prediction of machinery fault strength. While by obtaining spectral structure with unique characteristics, full vector spectrum(FVS) can well make up for the deficiency of single-channel. On this basis, the prediction method of FVS-ARMA model was proposed, which combined ARMA model with full vector spectrum technology. It was applied to predict machinery vibration strength and fault strength. Experiments showed that predictive results of this method were identical with the practical effects.The research content and main results are as follows:(1) Research on the prediction method of FVS-ARMA model and the modeling process. The modeling process of FVS-ARMA model which combined ARMA model of time-series forecasting method with full vector spectrum technology was given. A series of specific theoretical calculation formula and complete prediction flowchart were given.(2) Research on the prediction of machinery vibration strength based on FVS-ARMA model and application. This method was applied to predict machinery vibration strength, and the predictive process of machinery vibration strength was given. Experiments showed that predictive results of this method were fairly good, and this method had high forecasting accuracy in the prediction of machinery vibration strength.(3) Research on the prediction of fault strength of gear tooth broken based on FVS-ARMA model and application. On the basis of the above, this method was applied to predict spectral structure in the case of fault. So it can realize prediction of fault strength. And the predictive process of fault strength was given. Experiments showed that predictive results of this method were fairly good in every frequency. Make sure the accuracy of the forecasting spectral structure, this method well realized the prediction of fault strength of gear tooth broken.