Development of magnetic flux leakage pipe inspection robot using hall sensors

Abstract

Pipeline safety evaluation is an important problem of industry, and this paper presents an automated pipe inspection robot to inspect pipeline defects. Based on magnetic flux leakage (MFL) method, the robot utilizes established mechatronic principles to produce a low-cost device capable of detecting inner pipe defects. The pipe inspection robot's design mainly includes its mechanical design, electronic design and data processing. It can be used to multi-radius pipelines and variational work conditions. The paper also discusses the inspection robot signal processing. Utilizing noise signals and testing signals having different representation to various scale spectrum, get rid of the noise of MFL signal applying orthogonal wavelet. It describes an algorithm to recognize defect parameters based on wavelet basis function (WBF) neural network, and applying the theory to predict defect profiles from experimental MFL signals is presented.