基于RBF神经网络的振弦式传感器在矿压测量中的温度补偿  

Temperature compensation of vibrating wire Sensor in mine Pressure measurement base on RBF nutrual network

作　　者：赵国材[1] 谭晓静[1] 王昊轶[1] 

机构地区：[1]辽宁工程技术大学电气与控制工程学院,辽宁葫芦岛125105

出　　处：《微计算机信息》2010年第34期137-138,158,共3页Control & Automation

摘　　要：煤矿风洞中由于环境温度变化较大,使振弦式传感器存在温度漂移现象。准确测量出矿压,具有重要的现实意义。利用径向基函数,并采用模糊K值聚类算法,构建RBF神经网络模型,对测量矿压进行补偿,取得理想效果。实现了精度的温度补偿,提高了传感器的精度及线性度。Coal mine tunnel has a large temperature change due to environmental,so that the vibrating wire sensor has the existence of temperature drift.Accurately measuring mine pressure has important practical significance.This paper uses radial basis funcition and K values of fuzzy clustering algorithm,and construres RBF netrual network model to compensates to mine pressure measurement and get desired effect.It achieves a precision temperature compensation and improves the sensor ＇s accuracy and linearity.

关 键 词：振弦式传感器 矿压 RBF神经网络 温度补偿 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]