摘要
为了提高高分子PTC热敏电阻测温的准确性,采用BP神经网络对高分子PTC热敏电阻进行非线性校正。首先,对高分子PTC热敏电阻进行数据标定;然后建立BP神经网络模型;最后,应用此模型对高分子PTC热敏电阻进行非线性校正。经实验证明,该方法大大提高了PTC热敏电阻温度传感器的测温准确性,其测量误差在±0.08℃以内。
In order to improve the polymer PTC thermistor temperature measurement precision ,the BP neural network was utilized to rectify the nonlinear compensation of polymer PTC thermistor. Firstly,the polymer PTC thermistor calibration data;then a BP neural network model is established;finally,this model is used for nonlinear compensation of polymer PTC thermistor. Through the test shows,that method can more effectively improve polymer PTC thermistor temperature measurement precision. The measurement error was in the range of ±0.08℃.
出处
《自动化与仪表》
北大核心
2014年第10期20-22,45,共4页
Automation & Instrumentation
基金
国家重大科技成果转化项目(2012258)
国家创新基金资助项目(12C26216106801)
陕西省科技统筹创新工程项目(2013KTCQ01-50)