Defect profile reconstruction from MFL signals based on a specially-designed genetic taboo search algorithm

摘要

This paper proposes an effective method for reconstructing the profiles of defects in pipelines from magnetic flux leakage (MFL) measurements, based on a specially-designed genetic taboo search algorithm (GTSA). In the proposed GTSA, a kind of variable mutation probability mechanism is introduced into the genetic algorithm (GA) in order to make it self-adaptive in the management of the balance between diversity and elitism during the genetic life. To make up for the weakness of lacking local search ability, a taboo search (TS) algorithm is applied to the potential optimal solutions. In addition, a fitness function with weights is designed and used to measure the distance or proximity of a candidate from the solution. The excellent performance of this method is demonstrated using both simulated and actual MFL data. The method presented exhibits high inverse speed, while maintaining high prediction accuracy when tested. These properties, together with the advantages of the GA itself, make this approach extremely promising for defect profile reconstruction.