Research on SVM Based Diagnosis System for Oil Tubing

Abstract

Oil tubing is one of the most used equipment in oil extraction operations. An effective diagnosis system for it can provide multifarious benefits such as improved safety, efficient production and reduced costs for maintenance. In this paper, a support vector machine (SVM) based diagnosis system for oil tubing is studied and designed. SVM method has many advantages in solving the problem of small sample, pattern recognition of high dimensionality and nonlinear problems, which is fitable to the situation of oil tubing diagnosis. The SVM based diagnosis system for oil tubing is consisted of two parts: The hardware system part, including the detector and conditioning circuit board, and the software system part, including the SVM based analysis system. The detector is disposed on the wellhead and detects the leakage of magnetic field. The conditioning circuit board focuses on signal amplification and noise removal. The SVM based analysis system diagnoses the faults by the features of detected signal. An experiment platform is designed to certify the whole system and prove it perform well with a high diagnosis accuracy.