基于偏差估计的漏磁信号缺陷三维轮廓重构算法

Defect 3D Profile Reconstruction Using Magnetic Flux Leakage Signals Based on Error Estimation

漏磁检测是一种广泛应用于在役管道检测中的无损检测技术,有效的缺陷轮廓三维重构方法对于漏磁检测非常重要。提出了一种基于偏差估计的随机森林缺陷三维轮廓重构方法。该方法利用随机森林,以漏磁信号偏差估计重构轮廓偏差,并根据估计信号和实际信号之间的偏差更新缺陷轮廓,最终实现缺陷的三维轮廓重构。试验结果表明:提出的方法具有良好的缺陷轮廓重构精度。

Magnetic leakage detection as a nondestructive testing technology,is widely used in in-service pipeline.Effective 3-D profile reconstruction of defect is very important for magnetic flux leakage(MFL)detection.In this paper,a novel 3-D profile reconstruction method using random forest(RF)based on error estimation is proposed.RF is developed to estimate reconstructed profile errors by inputting signal errors.Then errors between estimated signals and real signals are applied to update defect profiles.Finally,3-D reconstructed profiles are obtained.Experimental results show that the proposed method has good precision of defect reconstruction.