Defect profile estimation from magnetic flux leakage signal via efficient managing particle swarm optimization.
Defect profile estimation from magnetic flux leakage signal via efficient managing particle swarm optimization.
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通过有效管理粒子群优化从漏磁信号估计缺陷轮廓
DOI：
10.3390/s140610361
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发表时间：
2014-06-12
期刊：
影响因子：
--
通讯作者：
Tian G
中科院分区：
文献类型：
--
作者：
Han W;Xu J;Wang P;Tian G
提出了一种基于高维问题的高效管理粒子群优化算法（EMPSO），从漏磁信号中估计缺陷轮廓。在该模型中，为了加强粒子间的信息交换，建立了粒子对模型。为了在面对不同景观的问题时更高效地进行搜索，提出了包含三种速度更新模型的速度更新方案。此外，为了有更多的机会搜索出最优解，实现了重新初始化的粒子自动选择。六个基准函数的优化结果表明，EMPSO在优化100-D问题时具有良好的性能。缺陷仿真结果表明，基于EMPSO的反演技术优于基于自学习粒子群优化器（SLPSO）的反演技术，在存在低噪声的情况下，估计轮廓仍然接近期望轮廓。利用基于empso的反演技术对实际漏磁信号的反演结果也表明，该算法能够用实际信号精确求解缺陷轮廓。仿真和实验结果表明，基于empso的反演技术的计算时间比基于slpso的反演技术减少了20% ~ 30%。
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.
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