Application of self-organizing competitive neural network in fault diagnosis of suck rod pumping system

Abstract

This paper represents a study using Artificial Neural Network (ANN) to solve dynamometer cards auto recognition problem. A self-organizing competitive neural network model is constructed to achieve automatization of fault diagnosis by automatically clustering dynamometer cards. Model is trained and tested using data acquired from Jiangsu oil fields, China. Research results show that self-organizing competitive neural network model has good classification and generalization capabilities, and hence is applicable to the automatic fault diagnosis of suck rod pumping system.