Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (2)

Search Parameters:
Keywords = online MFL (magnetic flux leakage) testing

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
13 pages, 2750 KiB  
Article
An Online MFL Sensing Method for Steel Pipe Based on the Magnetic Guiding Effect
by Jianbo Wu, Hui Fang, Xiaoming Huang, Hui Xia, Yihua Kang and Chaoqing Tang
Sensors 2017, 17(12), 2911; https://doi.org/10.3390/s17122911 - 15 Dec 2017
Cited by 24 | Viewed by 7400
Abstract
In order to improve the sensitivity of online magnetic flux leakage (MFL) testing for steel pipe, a sensing method based on the magnetic guiding effect is proposed and investigated in this paper. Compared to the conventional contact sensing method using a non-ferromagnetic support, [...] Read more.
In order to improve the sensitivity of online magnetic flux leakage (MFL) testing for steel pipe, a sensing method based on the magnetic guiding effect is proposed and investigated in this paper. Compared to the conventional contact sensing method using a non-ferromagnetic support, the proposed method creatively utilizes a ferromagnetic one to guide more magnetic flux to leak out. Based on Hopkinson’s law, the principle of the magnetic guiding effect of the ferromagnetic support is theoretically illustrated. Then, numerical simulations are conducted to investigate the MFL changes influenced by the ferromagnetic support. Finally, the probe based on the proposed method is designed and developed, and online MFL experiments are performed to validate the feasibility of the proposed method. Online tests show that the proposed sensing method can greatly improve the MFL sensitivity. Full article
(This article belongs to the Section Physical Sensors)
Show Figures

Figure 1

13 pages, 767 KiB  
Article
Fast Estimation of Defect Profiles from the Magnetic Flux Leakage Signal Based on a Multi-Power Affine Projection Algorithm
by Wenhua Han, Xiaohui Shen, Jun Xu, Ping Wang, Guiyun Tian and Zhengyang Wu
Sensors 2014, 14(9), 16454-16466; https://doi.org/10.3390/s140916454 - 4 Sep 2014
Cited by 13 | Viewed by 6208
Abstract
Magnetic flux leakage (MFL) inspection is one of the most important and sensitive nondestructive testing approaches. For online MFL inspection of a long-range railway track or oil pipeline, a fast and effective defect profile estimating method based on a multi-power affine projection algorithm [...] Read more.
Magnetic flux leakage (MFL) inspection is one of the most important and sensitive nondestructive testing approaches. For online MFL inspection of a long-range railway track or oil pipeline, a fast and effective defect profile estimating method based on a multi-power affine projection algorithm (MAPA) is proposed, where the depth of a sampling point is related with not only the MFL signals before it, but also the ones after it, and all of the sampling points related to one point appear as serials or multi-power. Defect profile estimation has two steps: regulating a weight vector in an MAPA filter and estimating a defect profile with the MAPA filter. Both simulation and experimental data are used to test the performance of the proposed method. The results demonstrate that the proposed method exhibits high speed while maintaining the estimated profiles clearly close to the desired ones in a noisy environment, thereby meeting the demand of accurate online inspection. Full article
(This article belongs to the Section Physical Sensors)
Show Figures

Back to TopTop