Prognostic algorithm based on the relative entropy fusion and modified ESN
WANG Haotian1,2,DUAN Xiusheng3，SHAN Ganlin2,SUN Jian4 ,QIU Jintao1
1.61716 Troops,Fuzhou 350000，China；
2.The Army Engineering University of PLA,Shijiazhuang 050003，China；
3.Shijiazhuang Tiedao University,Shijiazhuang 050003，China；
4.Luoyang Electronic Equipment Test Center of China,Luoyang 471003，China
Abstract：To deal with the shortcomings of high dimensional features and unsatisfying fault predicting effect in conventional hydraulic pumps fault diagnosis methods,a novel prognostic method based upon the relative entropy fusion and modified echo state network(ESN) was proposed.On the basement of relative entropy,a features fusion algorithm was presented for making full use of degradation feature informations for the sake of improving the prognostic feature performance based on the simplifying of features.Furthermore,the structure of the reserve pool in ESN was modified,and neighboring matrix elements were redefined.Then,a modified ESN predicting model was established to raise the network performance and increase the predicting accuracy.The proposed method was verified by its application in hydraulic pump performance degradation experiments.
王浩天1,2，段修生3，单甘霖2，孙健4，邱锦涛1. 一种基于关联熵融合与改进回声状态网络的故障预测方法[J]. 振动与冲击, 2019, 38(2): 226-233.
WANG Haotian1,2,DUAN Xiusheng3，SHAN Ganlin2,SUN Jian4,QIU Jintao1. Prognostic algorithm based on the relative entropy fusion and modified ESN. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(2): 226-233.
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