Abstract：The traditional physic health indicator(PHI) has poor monotonicity and is insensitive to the incipient fault.Aiming at this, a virtual health indicator(VHI) construction model, was proposed based on the information entropy of a specific frequency band and the restricted Boltzmann machine(SEI-RBM).The model consists of two layers: physic health indicator construction layer and features fusion layer.In the physic health indicator construction layer, a method based on the information entropy of a specific frequency band was proposed to construct the physic health indicator.In the features fusion layer, the monotonicity metric was used to select parts of the PHIs to form feature sets, which were then fused by the restricted Boltzmann machine to get a VHI.The experiment results show that the proposed model could make a VHI, being able to effectively enhance the monotonicity of the degradation assessment curve and promote the remaining useful life prediction accuracy of rolling element bearings.
张钢，田福庆，佘博，梁伟阁. 一种基于特定频段信息熵和RBM的健康因子构建方法[J]. 振动与冲击, 2020, 39(6): 147-153.
ZHANG Gang,TIAN Fuqing,SHE Bo,LIANG Weige. Health indicator construction method based on the information entropy of a specific frequency band and the RBM. JOURNAL OF VIBRATION AND SHOCK, 2020, 39(6): 147-153.
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