Status Recognition for Electrical Parameters of ESPCP Based on Biomimetic Pattern Recognition

Abstract

Various fault types and difficult diagnosis restricted the improvement of economic benefit and system efficiency of electrical submersible progressing cavity pump (ESPCP) production system. A novel method for status recognition of electrical parameters in fault diagnosis of ESPCP based on biomimetic pattern recognition (BPR) is presented. Application results show the proposed BPR classifier produces significant accuracy for classification of ESPCP electrical parameters. Compared with the results based on support vector machine (SVM), the proposed method is more efficiency.