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 (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.
Highlights
After the long-time operation of railway tracks or oil pipelines, many sorts of defects, like mechanical damage or cracks, may occur on their surfaces, which may trigger terrible accidents and lead to great financial losses and even personal casualties
The information of defect profiles is clearly contained in Magnetic flux leakage (MFL) signals
The Hall sensor probe is located at the centre of the two magnetic poles of the magnetizing yoke at a 0.5 mm distance away from the edge surface, aiming to acquire MFL signals
Summary
After the long-time operation of railway tracks or oil pipelines, many sorts of defects, like mechanical damage or cracks, may occur on their surfaces, which may trigger terrible accidents and lead to great financial losses and even personal casualties. MFL signals are acquired by an array of Hall effect sensors closely distributed above the surface of a measured object when the object is magnetically saturated by strong permanent magnets. For some facilities, such as an oil pipeline and railway track, inspections may be conducted at a large scale or a long distance.
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