Intelligent Detection Method of Variable Load Gearbox Fault Signal
SHI Pei-ming1,ZHAO Na1,SU Guan-hua1,SONG Tao2,HAN Dong2
1. School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
2. Qinhuangdao Audiovisual Machinery Research Institute, Qinhuangdao, Hebei 066000, China
Abstract：Aiming at the problem of gear fault feature extraction and classification under variable load excitation, an intelligent detection method of gearbox based on empirical mode decomposition (EMD) and deep belief network (DBN) is presented. Therefore, the intrinsic mode function (IMF) of the meshing frequency and the frequency doubling is selected to reconstruct the signal, and obtain the spectrum of the reconstructed signal, which is the input of the deep belief network. In the deep belief network, the pre-training and feature learning of input spectrum are carried out, and the classification model of gear fault recognition based on variable load excitation is established. Finally, fault diagnosis is carried out by using the constructed deep belief network. The experimental results show that the proposed method can effectively identify gear failure types under variable load excitation.
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2018, Vol. 39 
