Fault Diagnosis of Sucker Rod Pumping Wells Based on Wavelet Packet Energy and CS-ELM
Currently,the manual analysis method for fault diagnosis of rod-pumped oil wells is inefficient,a fault diagno-sis method of sucker rod pumping wells based on wavelet packet energy and cuckoo algorithm optimized extreme learning machine(CS-ELM)is proposed in this paper.Firstly,the electric power data is decomposed by wavelet packet to obtain multiple sub-bands,and the energy values of each band are calculated and normalized to form a feature vector.Then,the CS algorithm is used to optimize the ELM to obtain the optimal input weight and hidden layer threshold.Finally,the CS-ELM model is used to diagnose the fault of the rod pumping well with the extracted feature vector and compared with the diagnosis results of SVM,BP and ELM.
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