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Sensors 2014, 14(6), 10361-10380; doi:10.3390/s140610361

Defect Profile Estimation from Magnetic Flux Leakage Signal via Efficient Managing Particle Swarm Optimization

1
College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China
2
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
3
School of Electrical and Electronic Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK
*
Author to whom correspondence should be addressed.
Received: 21 April 2014 / Revised: 30 May 2014 / Accepted: 30 May 2014 / Published: 12 June 2014
(This article belongs to the Section Physical Sensors)

Abstract

In this paper, efficient managing particle swarm optimization (EMPSO) for high dimension problem is proposed to estimate defect profile from magnetic flux leakage (MFL) signal. In the proposed EMPSO, in order to strengthen exchange of information among particles, particle pair model was built. For more efficient searching when facing different landscapes of problems, velocity updating scheme including three velocity updating models was also proposed. In addition, for more chances to search optimum solution out, automatic particle selection for re-initialization was implemented. The optimization results of six benchmark functions show EMPSO performs well when optimizing 100-D problems. The defect simulation results demonstrate that the inversing technique based on EMPSO outperforms the one based on self-learning particle swarm optimizer (SLPSO), and the estimated profiles are still close to the desired profiles with the presence of low noise in MFL signal. The results estimated from real MFL signal by EMPSO-based inversing technique also indicate that the algorithm is capable of providing an accurate solution of the defect profile with real signal. Both the simulation results and experiment results show the computing time of the EMPSO-based inversing technique is reduced by 20%–30% than that of the SLPSO-based inversing technique. View Full-Text
Keywords: magnetic flux leakage; profile estimation; efficient managing particle swarm optimization; high dimension optimization problem magnetic flux leakage; profile estimation; efficient managing particle swarm optimization; high dimension optimization problem
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Han, W.; Xu, J.; Wang, P.; Tian, G. Defect Profile Estimation from Magnetic Flux Leakage Signal via Efficient Managing Particle Swarm Optimization. Sensors 2014, 14, 10361-10380.

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