Russian Journal of Nondestructive Testing

, Volume 41, Issue 12, pp 809–814 | Cite as

2D defect reconstruction from MFL signals by a genetic optimization algorithm

  • W. Han
  • P. Que
Magnetic Methods


The magnetic-flux-leakage (MFL) method has established itself as the most widely used inline inspection technique for the evaluation of gas and oil pipelines. An important problem in MFL nondestructive evaluation is the signal inverse problem, wherein the defect profile and its parameters are determined using the information contained in the measured signals. This paper proposes a genetic-algorithm-based inverse algorithm for reconstructing a 2D defect from MFL signals. In the algorithm, a radial-basis-function neural network is used as a forward model and a genetic algorithm is used to solve the optimization problem in the inverse problem. Experimental results are presented to demonstrate the effectiveness of the proposed inverse algorithm.


Neural Network Genetic Algorithm Inverse Problem Optimization Algorithm Structural Material 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© MAIK “Nauka/Interperiodica” 2005

Authors and Affiliations

  • W. Han
    • 1
  • P. Que
    • 1
  1. 1.Institute of Automatic DetectionShanghai Jiaotong UniversityShanghaiChina

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