RESEARCH ON SENSOR TEMPERATURE COMPENSATION SYSTEM BASED ON IMPROVED RBF NEURAL NETWORK

SONG RuiJuan

doi:10.16579/j.issn.1001.9669.2016.06.016

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RESEARCH ON SENSOR TEMPERATURE COMPENSATION SYSTEM BASED ON IMPROVED RBF NEURAL NETWORK

更新时间：2022-09-22

- RESEARCH ON SENSOR TEMPERATURE COMPENSATION SYSTEM BASED ON IMPROVED RBF NEURAL NETWORK
- Journal of Mechanical Strength Vol. 38, Issue 6, Pages: 1225-1228(2016)
- 作者机构：
  
  1. 广西机电职业技术学院电气工程系
- 作者简介：
- 基金信息：
- DOI：10.16579/j.issn.1001.9669.2016.06.016
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SONG RuiJuan. RESEARCH ON SENSOR TEMPERATURE COMPENSATION SYSTEM BASED ON IMPROVED RBF NEURAL NETWORK. [J]. 38(6):1225-1228(2016)
DOI：

SONG RuiJuan. RESEARCH ON SENSOR TEMPERATURE COMPENSATION SYSTEM BASED ON IMPROVED RBF NEURAL NETWORK. [J]. 38(6):1225-1228(2016) DOI： 10.16579/j.issn.1001.9669.2016.06.016.

摘要

考虑到目前常用的温度补偿方法是使用智能算法建立温度补偿模型,并使用群智能优化算法进行优化,提高补偿精度,对于传感器非线性温漂段具有较好的补偿效果,但是对于具有较好的线性使用这种方法的效率较低,而使用常规的线性最小二乘直线拟合方法即可得到较好的补偿效果,因此本文将最小二乘直线拟合方法与RBF神经网络模型进行融合,研究一种对压力传感器进行温度补偿模型,使用蚁群算法对常规RBF神经网络进行优化,提高补偿模型的性能。通过MPX53型压阻式压力传感器进行实验研究,结果表明,使用本文研究的温度补偿方法后,传感器在各个温度下同样基本不受温度的影响,与使用全程蚁群优化RBF神经网络温度补偿方法效果相差不大,但是由于中间温度区域采用直线拟合方法,整体温度补偿的效率有所提高。

Abstract

Considering the current temperature compensation method is used to establish the temperature compensation model using intelligent algorithm,and use swarm intelligent optimization algorithm to optimize and improve the compensation precision,has good compensation effect for nonlinear sensor temperature drift,but for the low efficiency of this method has good linearity,and the use of linear least squares fitting method the routine can get better compensation effect,so this will be the least squares fitting method and RBF neural network model integration,a model of temperature compensation of pressure sensor,using ant colony algorithm to optimize the conventional RBF neural network,improve the performance of compensation model. Through the MPX53 pressure piezoresistive pressure sensors were studied. The results showed that after using the temperature compensation method,sensor at various temperatures is basically the same temperature,with the use of the whole ant colony optimization RBF neural network method of temperature compensation effect is similar,but the intermediate temperature region due to the linear fitting method,the efficiency of the whole temperature compensation improved.

关键词

温度补偿压力传感器RBF神经网络蚁群算法

Keywords

Temperature compensationPressure sensorRBF neural networkAnt colony algorithm

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School of Mechanical Engineering, Liaoning Technical University

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