Defect Width Assessment Based on the Near-Field Magnetic Flux Leakage Method

被引：8

作者：

Li, Erlong ^{[1
]}

Chen, Yiming ^{[1
]}

Chen, Xiaotian ^{[2
]}

Wu, Jianbo ^{[1
]}

机构：

[1] Sichuan Univ, Sch Mech Engn, Chengdu 610065, Peoples R China

[2] Newcastle Univ, Sch Elect & Elect Engn, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England

来源：

SENSORS | 2021年 / 21卷 / 16期

基金：

中国国家自然科学基金;

关键词：

magnetic flux leakage (MFL); near-field effect; magnetic dipole; quantitative assessment; DIPOLE MODEL; SIMULATION; IDENTIFICATION; PROFILES; SIGNALS;

D O I：

10.3390/s21165424

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

Magnetic flux leakage (MFL) testing has been widely used as a non-destructive testing method for various materials. However, it is difficult to separate the influences of the defect geometrical parameters such as depth, width, and length on the received leakage signals. In this paper, a "near-field" MFL method is proposed to quantify defect widths. Both the finite element modelling (FEM) and experimental studies are carried out to investigate the performance of the proposed method. It is found that that the distance between two peaks of the "near-field" MFL is strongly related to the defect width and lift-off value, whereas it is slightly affected by the defect depth. Based on this phenomenon, a defect width assessment relying on the "near-field" MFL method is proposed. Results show that relative judging errors are less than 5%. In addition, the analytical expression of the "near-field" MFL is also developed.

引用

页数：15

共 35 条

[1] Automatic flaw detection in NDE signals using a panel of neural networks [J].

Christen, R. ;

Bergamini, A. .

NDT & E INTERNATIONAL, 2006, 39 (07) :547-553

[2] 3-d FEM simulation of velocity effects on magnetic flux leakage testing signals [J].

Du Zhiye ;

Ruan Jiangjun ;

Peng Ying ;

Yu Shifeng ;

Zhang Yu ;

Gan Yan ;

Li Tianwei .

IEEE TRANSACTIONS ON MAGNETICS, 2008, 44 (06) :1642-1645

[3] THE MAGNETIC LEAKAGE FIELD OF SURFACE-BREAKING CRACKS [J].

EDWARDS, C ;

PALMER, SB .

JOURNAL OF PHYSICS D-APPLIED PHYSICS, 1986, 19 (04) :657-673

[4] Analysis on Spatial Spectrum of Magnetic Flux Leakage Using Fourier Transform [J].

Li, Erlong ;

Kang, Yihua ;

Tang, Jian ;

Wu, Jianbo ;

Yan, Xizi .

IEEE TRANSACTIONS ON MAGNETICS, 2018, 54 (08)

[5] A Sensor Liftoff Modification Method of Magnetic Flux Leakage Signal for Defect Profile Estimation [J].

Feng, Jian ;

Lu, Senxiang ;

Liu, Jinhai ;

Li, Fangming .

IEEE TRANSACTIONS ON MAGNETICS, 2017, 53 (07)

[6] Fast Estimation of Defect Profiles from the Magnetic Flux Leakage Signal Based on a Multi-Power Affine Projection Algorithm [J].

Han, Wenhua ;

Shen, Xiaohui ;

Xu, Jun ;

Wang, Ping ;

Tian, Guiyun ;

Wu, Zhengyang .

SENSORS, 2014, 14 (09) :16454-16466

[7] Evaluation of a Magnetic Dipole Model in a DC Magnetic Flux Leakage System [J].

Hosseingholizadeh, Samaneh ;

Filleter, Tobin ;

Sinclair, Anthony N. .

IEEE TRANSACTIONS ON MAGNETICS, 2019, 55 (04)

[8] A Basic Signal Analysis Approach for Magnetic Flux Leakage Response [J].

Huang, Song Ling ;

Peng, Lisha ;

Wang, Shen ;

Zhao, Wei .

IEEE TRANSACTIONS ON MAGNETICS, 2018, 54 (10)

[9] Serial MTJ-Based TMR Sensors in Bridge Configuration for Detection of Fractured Steel Bar in Magnetic Flux Leakage Testing [J].

Jin, Zhenhu ;

Mohd Noor Sam, Muhamad Arif Ihsan ;

Oogane, Mikihiko ;

Ando, Yasuo .

SENSORS, 2021, 21 (02) :1-10

[10] Wavelet transform and neural network based 3D defect characterization using magnetic flux leakage [J].

Joshi, Ameet .

INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS, 2008, 28 (1-2) :149-153

← 1 2 3 4 →