Paper Title:
Data Fusion for MFL Signal Characterization
  Abstract

The objective of data fusion is to be able to draw inferences that may not be feasible with data from a single sensor alone. In this paper, data from three sets of sensors are fused to estimate the defect profile from magnetic flux leakage (MFL) inspection data. The three sensors measure the axial, radial and tangential components of the MFL field. Data is fused at the feature level. Examples of signal features are amplitude, width, etc. A radial basis function network (RBFN) is then employed to map the fused features appropriately to obtain the geometric profile of the defect. The feasibility of the approach is evaluated using the data obtained from the MFL inspection of oil pipes. The results obtained by fusing the axial, radial and tangential components appear to be better than those obtained using the axial and radial component alone.

  Info
Periodical
Edited by
Ran Chen
Pages
3519-3523
DOI
10.4028/www.scientific.net/AMM.44-47.3519
Citation
Q. Song, "Data Fusion for MFL Signal Characterization", Applied Mechanics and Materials, Vols. 44-47, pp. 3519-3523, 2011
Online since
December 2010
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Price
$32.00
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