漏磁检测中的缺陷重构方法

彭丽莎; 黄松岭; 赵伟; 王珅

彭丽莎,黄松岭,赵伟,王珅.漏磁检测中的缺陷重构方法[J].电测与仪表,2015,52(13):.
PENG Li - Sha,HUANG Song - Ling,ZHAO Wei,Wang Shen.Defect Reconstruction Method for Magnetic Flux Leakage Testing[J].Electrical Measurement & Instrumentation,2015,52(13):.

漏磁检测中的缺陷重构方法

Defect Reconstruction Method for Magnetic Flux Leakage Testing

DOI：

中文关键词: 漏磁检测缺陷重构有限元神经网络数据融合

英文关键词:magnetic flux leakage (MFL) testing, defect reconstruction, finit element neural network (FENN), data fusion

基金项目:国家“863”重大项目资助项目（2011AA090301）；国家重大科学仪器设备开发专项（2013YQ140505）

作者中文名	作者英文名	单位
彭丽莎	PENG Li - Sha	清华大学电机系电力系统国家重点实验室
黄松岭	HUANG Song - Ling	清华大学电机系电力系统国家重点实验室
赵伟	ZHAO Wei	清华大学电机系电力系统国家重点实验室
王珅	Wang Shen	清华大学电机系电力系统国家重点实验室

摘要点击次数: 1884

中文摘要:

漏磁检测技术中的缺陷重构方法是目前漏磁检测缺陷评估的研究热点与难点。在对漏磁检测缺陷重构进行概述的基础上,综述了现有的缺陷重构方法：开环逆向重构法和闭环伪逆重构法,并对这两类方法中常用的逆向模型、前向模型、优化算法及其特点进行了较为详细的介绍。指出了基于数据融合技术、图像处理技术和多缺陷综合评估的缺陷重构方法的研究发展方向。

英文摘要:

Defect reconstruction method for magnetic flux leakage (MFL) testing is a hot and difficult spot of MFL testing defect evaluation nowadays. Reviewing the contents of the MFL testing defect reconstruction research, two kinds of defect reconstruction methods: open loop reverse method and closed loop pseudo-reverse method have been summarized. And the reverse model, forward model and optimization algorithm which are commonly used in them were discussed here. Furthermore, the research direction of defect reconstruction such as data fusion technology, image processing technology and the comprehensive assessment of multi defects were proposed.

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