基于带约束粒子群的电容层析成像图像重建算法  

Capacitance Tomography Image Reconstruction Algorithm Based on Confined Particle Swarm

作　　者：焦园娜 左振华 张雷雷 郭志恒[1] 阚哲 JIAO Yuanna;ZUO Zhenhua;ZHANG Leilei;GUO Zhiheng;KAN Zhe(School of Information and Control Engineering,Liaoning Petrochemical University,Fushun Liaoning 113001,China;Fushun Petrochemical Company Olefin Factory,PetroChina Company limited,Fushun Liaoning 113001,China;Fushun Petrochemical Engineering Construction Co.Ltd.,Fushun Liaoning 113001,China)

机构地区：[1]辽宁石油化工大学信息与控制工程学院,辽宁抚顺113001 [2]中国石油天然气股份有限公司抚顺石化分公司烯烃厂,辽宁抚顺113001 [3]抚顺石化工程建设有限公司,辽宁抚顺113001

出　　处：《辽宁石油化工大学学报》2024年第2期91-96,共6页Journal of Liaoning Petrochemical University

基　　金：辽宁省教育厅一般项目(JYTMS20231448)。

摘　　要：粒子群工作时系统的鲁棒性很高,有助于解决图像重建的病态问题。但是,重建图像的像素较大,导致粒子维度较大,粒子在寻优过程中很难达到最优解。为了解决这一问题,对粒子的位置加入约束条件,以Tikhonov正则化图像重建算法成像作为粒子位置参考,约束粒子在Tikhonov正则化算法重建图像的一定范围内搜索,并用罚函数求解,提高粒子搜索速度;粒子群的惯性权重采用线性递减权值,从而实现惯性权值的自适应动态调整,提高算法的灵活性;将混沌算子加入粒子群位置搜索过程中,当粒子陷入局部最优时,混沌变量在一定范围内波动,降低最优解的错失率。仿真实验结果表明,与传统的LBP算法和Tikhonov算法相比,改进的粒子群算法的电容层析成像图像重建更精确,效率更高。The robustness of the particle swarm system is great,which is very helpful for solving ill-conditioned problems such as image reconstruction.However,the large number of pixels in the reconstructed image leads to a large dimension of particle and it is difficult for the particle to achieve the optimal solution in the optimization process.In order to solve this problem,a constraint is added to the particle position,imaging by Tikhonov regularization algorithm is used as the reference of particle position.The search for particles is constrained to the range of Tikhonov regularization algorithm reconstructs the image.Using the penalty function to solve the constraint problem to improve the particle search speed.Linearly decreasing weights as inertial weights for particle swarms optimization to realize the adaptive dynamic adjustment of the inertia weight and improve the flexibility of the algorithm;the chaotic operator is added to the position search process of the particle swarm optimization,when the particle falls into the local optimum,the chaotic variable will fluctuate within a certain range,reducing the missed rate of the optimal solution.The simulation results show that The improved particle swarm algorithm is more accurate and efficient than the traditional LBP algorithm and Tikhonov regularization algorithm.

关 键 词：电容层析成像 约束粒子群算法 罚函数 混沌算子 惯性动态权值 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]