Ambient temperature compensation of infrared temperature sensor based on PSO-BP

ZHAO Bin; WANG Jian-hua

doi:10.13873/J.1000-9787(2015)02-0047-03

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Ambient temperature compensation of infrared temperature sensor based on PSO-BP

更新时间：2025-09-11

- Ambient temperature compensation of infrared temperature sensor based on PSO-BP
- Vol. 34, Issue 2, Pages: 47-49(2015)
- 作者机构：
  
  江苏科技大学电子信息学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2015)02-0047-03
  CLC： TP212.11
- Published：2015
- 稿件说明：
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[1]赵斌,王建华.基于PSO-BP的红外温度传感器环境温度补偿[J].传感器与微系统,2015,34(02):47-49.

ZHAO Bin, WANG Jian-hua. Ambient temperature compensation of infrared temperature sensor based on PSO-BP[J]. 2015, 34(2): 47-49.
[1]赵斌,王建华.基于PSO-BP的红外温度传感器环境温度补偿[J].传感器与微系统,2015,34(02):47-49. DOI： 10.13873/J.1000-9787(2015)02-0047-03.

ZHAO Bin, WANG Jian-hua. Ambient temperature compensation of infrared temperature sensor based on PSO-BP[J]. 2015, 34(2): 47-49. DOI： 10.13873/J.1000-9787(2015)02-0047-03.

摘要

针对红外温度传感器的测温精度易受环境温度的影响

提出了一种基于粒子群优化（PSO）BP（PSO-BP）神经网络的温度补偿方法。所提出的PSO-BP算法解决了一般BP算法迭代速度慢、且易陷入局部最优的问题

以热电堆传感器的环境温度补偿为例

进行算法实现

并以单纯的BP算法做对照。仿真结果表明:提出的PSO-BP算法对环境温度有明显的补偿效果

且优于单纯的BP算法补偿。所构建的补偿模型具有较高的补偿精度和实用价值。

Abstract

Aiming at precision of infrared temperature sensor is affected by ambient temperature

a new method is put forward for temperature compensation based on particle swarm optimize（ PSO） BP（ PSO-BP） neural network.The proposed PSO-BP algorithm solves problem that iteration speed of general BP algorithm is slow

and prone to local optimum

take ambient temperature compensation of thermopile sensor for example to realize algorithm

and compare with pure BP algorithm. Simulation results show that the proposed PSO-BP algorithm has obvious compensation effect on ambient temperature

and the effect is better than that of pure BP algorithm. The constructed compensation model has high compensation precision and practical value.

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references

粒子群优化BP神经网络的激光铣削质量预测模型 [J]. 许兆美,刘永志,杨刚,王庆安. 红外与激光工程 . 2013(09)

光纤传感器的神经网络光强补偿及非线性校正 [J]. 袁楚明,廖圣华,刘繄,张冈,陈幼平. 仪表技术与传感器 . 2012(02)

基于PSO-BP神经网络的网络流量预测与研究 [J]. 赵振江. 计算机应用与软件 . 2009(01)

环境温度对红外图像非均匀性影响的研究 [J]. 隋修宝,陈钱,顾国华. 光子学报 . 2008(12)

红外热像仪精确测温技术 [J]. 李云红,孙晓刚,原桂彬. 光学精密工程 . 2007(09)

混合神经网络技术[M]. 科学出版社 , 田雨波, 2009

PSO-based intelligent integration of design and control for one kind of curing process [J] . Xin Jiang Lu,Han-Xiong Li,Xiang Yuan. Journal of Process Control . 2010 (10)

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