Three‐dimensional magnetic flux leakage signal analysis and imaging method for tank floor defect. Issue 17 (31st October 2018)

• Record Type: Journal Article
• Authors: Peng, Lisha; Huang, Songling; Wang, Shen; Zhao, Wei
• Is Part Of: Journal of engineering. Volume 2018:Issue 17(2018)
• Page Start: 1865
• Page End: 1870
• Publication Date: 2018-10-31
• Subjects: flaw detection -- edge detection -- tanks (containers) -- magnetic flux -- finite element analysis -- inspection -- nondestructive testing -- magnetic leakage -- structural engineering computing; dimensional magnetic flux leakage signal analysis -- tank floor defect -- magnetic flux leakage detection -- defect analysis -- one‐dimensional MFL signals -- two‐dimensional contour identification -- three‐dimensional MFL signals -- signal intensity -- defect depth -- defect imaging method -- defect edge -- finite element method; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2018.8344
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : The magnetic flux leakage (MFL) detection of defect in tank floor is of great significance to ensure the safety of the tank. The existing methods for defect analysis are based on one‐dimensional MFL signals, which lead to simple quantification or two‐dimensional contour identification of defect. In this study, the characteristics of the three‐dimensional (3D) MFL signals of the bottom of the tank floor have been analysed. The sensitivity and correspondence of the components of MFL signals to various types of edge of defect have been studied, along with the correlation between signal intensity and the defect depth. This study also proposed a defect imaging method based on 3D MFL signals. This method adopts the Prewitt operator to detect the defect edge. Then, a finite element method is used to establish the corresponding relationship between defect depth and signal intensity, to solve the depth of a real defect. The method proposed in this study can achieve the contour recognition and depth estimation of the defect accurately, and further realise defect imaging. The finite element simulations test has verified the feasibility of the proposed method.