scholarly journals In-line Detection of Defects in Steel Pipes using Flexible GMR Sensor Array

2021 ◽  
pp. 101761
Author(s):  
Mathivanan Durai ◽  
Chou-Wei Lan ◽  
Ho Chang
Keyword(s):  
Sensor Array ◽  
Line Detection ◽  
Steel Pipes ◽  
Gmr Sensor ◽  
Detection Of Defects

scholarly journals An Automated Sensing System for Steel Bridge Inspection Using GMR Sensor Array and Magnetic Wheels of Climbing Robot

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Rui Wang ◽  
Youhei Kawamura
Keyword(s):  
Magnetic Field ◽  
Magnetic Flux ◽  
Giant Magnetoresistance ◽  
Sensor Array ◽  
Fatigue Cracks ◽  
Vertical Component ◽  
Steel Bridges ◽  
Steel Bridge ◽  
Sensing System ◽  
Gmr Sensor

Corrosion is one of the main causes of deterioration of steel bridges. It may cause metal loss and fatigue cracks in the steel components, which would lead to the collapse of steel bridges. This paper presents an automated sensing system to detect corrosion, crack, and other kinds of defects using a GMR (Giant Magnetoresistance) sensor array. Defects will change the relative permeability and electrical conductivity of the material. As a result, magnetic field density generated by ferromagnetic material and the magnetic wheels will be changed. The defects are able to be detected by using GMR sensor array to measure the changes of magnetic flux density. In this study, magnetic wheels are used not only as the adhesion device of the robot, but also as an excitation source to provide the exciting magnetic field for the sensing system. Furthermore, compared to the eddy current method and the MFL (magnetic flux leakage) method, this sensing system suppresses the noise from lift-off value fluctuation by measuring the vertical component of induced magnetic field that is perpendicular to the surface of the specimen in the corrosion inspection. Simulations and experimental results validated the feasibility of the system for the automated defect inspection.

Design of a GMR sensor array system for robotic pipe inspection

2010 ◽  
Author(s):  
Winncy Du ◽  
Hai Nguyen ◽  
Amitesh Dutt ◽  
Kevin Scallion
Keyword(s):  
Sensor Array ◽  
Pipe Inspection ◽  
Gmr Sensor

scholarly journals Flexible GMR Sensor Array for Magnetic Flux Leakage Testing of Steel Track Ropes

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
W. Sharatchandra Singh ◽  
B. P. C. Rao ◽  
S. Thirunavukkarasu ◽  
T. Jayakumar
Keyword(s):  
Sensor Array ◽  
Spatial Information ◽  
Three Dimensional ◽  
Element Model ◽  
Axial Component ◽  
Cross Sectional ◽  
Dimensional Finite Element ◽  
Gmr Sensor ◽  
Three Dimensional Finite Element ◽  
Induced Defects

This paper presents design and development of a flexible GMR sensor array for nondestructive detection of service-induced defects on the outer surface of 64 mm diameter steel track rope. The number of GMR elements and their locations within saddle-type magnetizing coils are optimized using a three dimensional finite element model. The performance of the sensor array has been evaluated by measuring the axial component of leakage flux from localized flaw (LF) and loss of metallic cross-sectional area (LMA) type defects introduced on the track rope. Studies reveal that the GMR sensor array can reliably detect both LF and LMA type defects in the track rope. The sensor array has a fast detection speed along the length of the track rope and does not require circumferential scanning. It is also possible to image defects using the array sensor for obtaining their spatial information.

HIGH RESOLUTION EDDY-CURRENT WIRE TESTING BASED ON A GMR SENSOR-ARRAY

2009 ◽  
Author(s):  
Marc Kreutzbruck ◽  
Kai Allweins ◽  
Chris Strackbein ◽  
Hendrick Bernau ◽  
Donald O. Thompson ◽  
...  
Keyword(s):  
High Resolution ◽  
Eddy Current ◽  
Sensor Array ◽  
Gmr Sensor

scholarly journals Flaw Classification Algorithm for Heat Exchanger Tubes Using a Bobbin-Type Magnetic Camera

2019 ◽  
Vol 9 (23) ◽  
pp. 5000
Author(s):  
Sim ◽  
Lee ◽  
Lee ◽  
Lee
Keyword(s):  
Giant Magnetoresistance ◽  
Sensor Array ◽  
Classification Algorithm ◽  
Frequency Change ◽  
Outer Diameter ◽  
Flaw Classification ◽  
Inner Diameter ◽  
Magnetic Camera ◽  
Gmr Sensor ◽  
Rotational Direction

This paper presents an algorithm that estimates the presence, location, shape, and depth of flaws using a bobbin-type magnetic camera consisting of bobbin probes and a bobbin-type integrated giant magnetoresistance (GMR) sensor array (BIGiS). The presence of the flaws is determined by the lobe path of the Lissajous curves obtained from bobbin coil with respect to the applied frequency. The location of the flaw, i.e., whether it is an inner diameter (ID) or outer diameter (OD) flaw, can be determined from the rotational direction of the lobe with respect to the frequency change. The shape of the flaw is then determined from the area of the lobe and the BIGiS image. At this stage, multi-site damage can be determined from the BIGiS image. The effectiveness of the flaw classification algorithm was evaluated using various types of artificial flaws introduced into small-bore tube test specimens made of austenitic stainless steel.

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