Remaining Useful Life Prediction Based on the Bayesian Regularized Radial Basis Function Neural Network for an External Gear Pump

被引：11
|
作者：
Guo, Rui [1 ,2 ]
Li, Yongtao [1 ,3 ]
Zhao, Lijiang [1 ,3 ]
Zhao, Jingyi [1 ,4 ]
Gao, Dianrong [1 ,4 ]
机构：
[1] Yanshan Univ, Hebei Prov Key Lab Heavy Machinery Fluid Power Tr, Qinhuangdao 066004, Hebei, Peoples R China
[2] Zhejiang Univ, State Key Lab Fluid Power & Mechatron Syst, Hangzhou 310027, Peoples R China
[3] Yanshan Univ, Key Lab Adv Forging & Stamping Technol & Sci, Qinhuangdao 066004, Hebei, Peoples R China
[4] Yanshan Univ, Hebei Key Lab Special Delivery Equipment, Qinhuangdao 066004, Hebei, Peoples R China
来源：
IEEE ACCESS | 2020年 / 8卷
基金：
中国国家自然科学基金;
关键词：
Degradation; Gears; Pumps; Predictive models; Hydraulic systems; Bayes methods; Prediction algorithms; External gear pump; RUL; Trainbr-RBFNN; VMD; parameter fusion; FAULT-DIAGNOSIS; DECOMPOSITION; MODEL;
D O I：
10.1109/ACCESS.2020.3001013
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A remaining useful life (RUL) prediction method for an external gear pump is proposed by Bayesian regularized radial basis function neural network (Trainbr-RBFNN). The variational mode decomposition (VMD) algorithm has been used to denoise the vibration data of accelerated degradation test, followed by which, using the Hilbert modulation the reconstructed signal has been demodulated. After which, compared with the ensemble empirical mode decomposition (EEMD) algorithm and the modified ensemble empirical mode decomposition (MEEMD) algorithm. Subsequently, factor analysis (FA) has been selected to realize the fusion of various characteristic parameters, after which, the external gear pump& x2019;s degradation evaluation index established and analyzed. Finally, the degradation evaluation index has been used to train the Trainbr-RBFNN model, and achieve gear pump degradation evaluation model for RUL prediction. Experiment results evidence that the RUL of the external gear pump can be accurately evaluated with the method used.
引用
收藏
页码：107498 / 107509
页数：12
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