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电容层析成像传感器结构参数粒子群优化算法

发表时间:2011-04-30  浏览量:1368  下载量:613
全部作者: 李岩,朱艳丹
作者单位: 哈尔滨理工大学计算机科学与技术学院
摘 要: 电容层析成像(electrical capacitance tomography, ECT)技术是一种基于电容传感器机理的过程成像技术。以12电极电容阵列传感器ECT系统为背景,介绍敏感场的计算方法,借助大型ANSYS有限元分析工具,建立电容传感器结构模型,并得到电极间敏感场的分布,分析电容传感器在不同参数下的电容变化情况。为避免粒子在全局附近振荡和粒子陷入局部最优,提出改进粒子群算法(particle swarm optimization, PSO)与改进混沌搜索策略的混合新算法。以敏感场整体灵敏度大小系统性能为目标,优化电容传感器结构,寻找传感器最优结构参数,为电容层析成像系统图像重建提供新的思路。
关 键 词: 计算机系统结构;电容层析成像;敏感场;传感器;粒子群算法
Title: A parameter particle swarm optimization algorithm for sensor of electrical capacitance tomography
Author: LI Yan, ZHU Yandan
Organization: School of Computer Science and Technology, Harbin University of Science and Technology
Abstract: Electrical capacitance tomography (ECT) is a process imaging technology based on the mechanism of capacitive sensor. Based on 12 electrode capacitance array sensor ECT system, this paper describes the calculation of sensitivity field, using large-scale ANSYS finite element analysis tool, establishes capacitance sensor structural model, and gets the distribution of sensitivity field between the electrodes, analyzes the capacitance changes of the capacitance sensor under different parameters, in order to avoid oscillation of particle globally and falling of particle into local optimum, proposes the mixed new algorithm of improved PSO and improved chaotic search strategy. For the goal of the system performance of the sensitivity field's overall sensitivity size, optimizes the structure of capacitive sensor, finds out the optimal structural parameters of the sensor. This paper provides a new way of thinking for the electrical capacitance tomography image reconstruction.
Key words: computer system architecture; electrical capacitance tomography; the sensitivity field; sensor; particle swarm optimization
发表期数: 2011年4月第8期
引用格式: 李岩,朱艳丹. 电容层析成像传感器结构参数粒子群优化算法[J]. 中国科技论文在线精品论文,2011,4(8):718-723.
 
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