CAJ | 학술논문

针对目前电阻层析成像图像重建算法存在成像精度较低的问题,以及为了满足应用于多相流领域的精度要求,提出一种基于遗传算法的组合算法,将线性反投影算法、修正的牛顿-拉夫逊类算法与区间剖分引入遗传算法种群初始化操作中,同时为了改善单纯遗传算法局部搜索能力差与未成熟收敛的问题,将粒子群算法引入遗传算法变异操作中.实验结果表明组合算法效果明显优于线性反投影算法,修正的牛顿-拉夫逊类算法,有效克服了遗传算法早熟收敛现象,提高了成像精度.
침대목전전조층석성상도상중건산법존재성상정도교저적문제,이급위료만족응용우다상류영역적정도요구,제출일충기우유전산법적조합산법,장선성반투영산법、수정적우돈-랍부손류산법여구간부분인입유전산법충군초시화조작중,동시위료개선단순유전산법국부수색능력차여미성숙수렴적문제,장입자군산법인입유전산법변이조작중.실험결과표명조합산법효과명현우우선성반투영산법,수정적우돈-랍부손류산법,유효극복료유전산법조숙수렴현상,제고료성상정도.
In order to resolve the low image reconstruction quality problem of electrical resistance tomography and fulfill the measurement precision requirement for multi-phase flow, a hybrid algorithm based on genetic algorithm was proposed. The hybrid algorithm introduces linear back projection, modified Newton-Raphson method and divided interval into the population initialization of genetic algorithm, and applies particle swarm optimization to the mutation operation in order to overcome the poor local searching ability and premature convergence of simple genetic algorithm. Experimental results show that the novel algorithm is superior to linear back projection and modified Newton-Raphson method, and can overcome the premature phenomena effectively and improve the reconstruction quality.