Data Fusion for MFL Signal Characterization

Abstract:

Article Preview

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

Authors:

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.