Bearing Breakdown Diagnosis of Rough Collection Theory Optimization Neural Network Method
Zhou De-lian · Coal Mine Machinery · 2005
There are many kinds of the methods to diagnose the bearing breakdown,such as the method of base frequency test,the axle center trajectory diagram and the response signal power spectrum analytic method and so on,but it is often difficult to realize the real-time monitor and the diagnosis.Owing to the greatly strengthened non-linear insinuation,the artificial neural network technology can obtain the widespread application in the breakdown diagnosis,but the ability of association is limited.When it surpasses the demarcation line,it usually associates in the wrong way and the decision system will have the phenomena of misjudging or without judging.This article proposes a usage of rough collection theory by optimizing the BP nerve network model method,and will apply the optimized network model in the rolling bearing breakdown diagnosis.