|Table of Contents|

Application of PSO Algorithm to Nonlinear Characteristics Correctionof 3D Printing Nozzle Temperature Sensor(PDF)

南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2016年04期
Page:
57-
Research Field:
计算机与信息工程
Publishing date:

Info

Title:
Application of PSO Algorithm to Nonlinear Characteristics Correctionof 3D Printing Nozzle Temperature Sensor
Author(s):
Chen LiLiu YijianGuo AiqinCheng Jihong
School of Electrical and Automation Engineering,Nanjing Normal University,Nanjing 210042,China
Keywords:
particle swarm optimization(PSO)algorithm3D printing nozzleinverse modeltemperature sensornonlinear
PACS:
TP212
DOI:
10.3969/j.issn.1672-1292.2016.04.010
Abstract:
In this paper,the Particle Swarm Optimization(PSO)algorithm is applied to nonlinear characteristic adjustment of 3D printing nozzle temperature sensor. On the occasion that the nonlinear characteristic of the sensor is not available,a general method and an implementation procedure for linearization of the nonlinear sensor based on inverse model are proposed in this paper. Firstly,the sample data are obtained and analyzed. Then the inverse model of temperature sensor is given and the parameters in the inverse model are optimized by the PSO. And based on the optimized inverse model,the goal of the linearization of the sensor nonlinear characteristic is realized. At last,the experiments are conducted,and the inverse model of PSO parameters optimization and Matlab curve fitting solution of the experimental results are compared. The results validate the method proposed in this paper effective and it can be generalized to other nonlinear sensor applications.

References:

[1] 杨继全,戴宁,侯丽雅. 三维打印设计与制造[M]. 北京:科学出版社,2013:1-5.
YANG J Q,DAI N,HOU L Y. 3D printing design and manufacturing[M]. Beijing:Science Press,2003:1-5.(in Chinese)
[2]刘君华. 智能传感器系统[M]. 西安:西安电子科技大学出版社,2000:264-289.
LIU J H. Intelligent sensor technology[M]. Xi’an:Xidian University Press,2000:264-289.(in Chinese)
[3]张长利,张伶鳦,王叔文,等. 基于传感器校正与融合农用旋翼无人机姿态解算[J]. 东北农业大学学报,2015,46(11):70-76.
ZHANG C L,ZHNGA L Y,WANG S W,et al. Attitude algorithm research in the agricultural rotor that based on the sensor calibration and fusion[J]. Journal of Northeast agricultural university,2015,46(11):70-76.(in Chinese)
[4]靳莹瑞,许京雷. 传感器校正及融合的实现技术[J]. 中原工学院学报,2010,21(5):1-4.
JIN Y R,XU J L. The correction technology and data fusion of sensor[J]. Journal of Zhongyuan university of technology,2010,21(5):1-4.(in Chinese)
[5]唐家德. 基于MATLAB的非线性曲线拟合[J]. 计算机与现代化,2008(6):15-19.
TANG J D. Nonlinear curve fitting based on MATLAB[J]. Computer and modernization,2008(6):15-19.(in Chinese)
[6]林贤坤,覃柏英. 微粒群算法在传感器优化配置中的应用[J]. 控制工程,2013,20(1):84-92.
LIN X K,QIN B Y. Application of particle swarm optimization to optimal sensor placement[J]. Control engineering of China,2013,20(1):84-92.(in Chinese)
[7]程继红,刘益剑. 微粒群优化算法在传感器非线性自校正中的应用[J]. 传感器技术,2005,24(10):74-76.
CHENG J H,LIU Y J. Application of PSO algorithm in sensor nonlinear self rectification[J]. Journal of transducer technology,2005,24(10):74-76.(in Chinese)
[8]KENNEDY J,BLACKWELL T.Particle swarm optimization[C]. USA:IEEE,1995:1 942-1 948.
[9]夏桂梅,苏长慧. 基于Powell搜索法的简化微粒群算法[J]. 宁夏大学学报(自然科学版),2015,36(2):126-130.
XIA G M,SU C H. A simplified particle swarm algorithm based on powell search method[J]. Journal of Ningxia university(natural science edition),2015,36(2):126-130.(in Chinese)
[10]李厚儒,南敬昌. 拟牛顿粒子群算法在非线性电路谐波平衡方程中的应用[J]. 计算机应用与软件,2013,30(2):103-109.
LI H R,NAN J C. Application of Quasi-Newton particle swarm algorithm in nonlinear circuit harmonic balance equation[J]. Computer applications and software,2013,30(2):103-109.(in Chinese)
[11]郝武伟. 微粒群算法的性能分析与优化[J]. 济南职业学院学报,2016(2):102-105.
HAO W W. Performance analysis and optimization of particle swarm algorithm[J]. Journal of Jinan vocational college,2016(2):102-105.(in Chinese)
[12]朱学荣,邴淑琴. 微粒群算法在工程项目资源均衡优化中的应用[J]. 内蒙古工业大学学报(自然科学版),2013,32(1):16-20.
ZHU X R,BING S Q. The application of PSO in unlimited resource leveling optimization[J]. Journal of Inner Mongolia university of technology(natural science edition),2013,32(1):16-20.(in Chinese)
[13]曹弋,刘怀,王恩荣. MATLAB教程及实训[M]. 北京:机械工业出版社,2008:83-109.
CAO Y,LIU H,WANG E R. MATLAB tutorials and training[M]. Beijing:China Machine Press,2008:83-109.(in Chinese)

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Last Update: 2016-12-31