基于线性和非线性回归算法的湿度传感器校准研究  

Research on Calibration of Humidity Sensor Based on Linear and Nonlinear Regression Algorithm

作　　者：张鹏[1] 殷家璇 陶佰睿[1] ZHANG Peng;YIN Jiaxuan;TAO Bairui(College of Communications and Electronics Engineering,Qiqihar University,Qiqihar Heilongjiang 161006,China)

机构地区：[1]齐齐哈尔大学通信与电子工程学院,黑龙江齐齐哈尔161006

出　　处：《传感技术学报》2025年第3期421-425,共5页Chinese Journal of Sensors and Actuators

基　　金：黑龙江省省属本科高校优秀青年教师基础研究支持计划项目(YQJH2023105);黑龙江省高等教育教学改革研究项目(SJGZB2024187);黑龙江省自然科学基金项目(LH2023F052);齐齐哈尔大学教育科学研究项目(GJQTYB202301)。

摘　　要：电阻型湿度传感器在环境监测、农业、工业及家庭应用等领域具有广泛的潜力。由于制造过程、材料特性及环境因素等多重影响,传感器输出数据可能存在误差。提出运用线性回归和非线性回归算法对电阻型湿度传感器进行精确校准,以提升测量结果的准确性和可靠性。为验证所提方法的有效性,设计并实施一系列校准试验。结果表明,采用这些算法可以显著提高测量精度,并适用于各种类型的电阻型湿度传感器。这为传感器性能优化和误差校正提供了有效方法,有助于推动其技术发展与应用。Resistive humidity sensors have broad potential in environmental monitoring,agriculture,industry,and household applications.Due to multiple influences such as the manufacturing process,material properties,and environmental factors,there may be errors in the sensor output data.Linear regression and nonlinear regression algorithms are proposed to be used to accurately calibrate the resistive hu-midity sensor to improve the accuracy and reliability of the measurement results.To verify the effectiveness of the proposed method,a series of calibration experiments are designed and implemented.The results show that the measurement accuracy can be significantly improved by adopting these algorithms,and it is suitable for various types of resistive humidity sensors.This provides an effective meth-od for sensor performance optimization and error correction,which will help promote its technical development and application.

关 键 词：湿度传感器 校准算法 线性回归 非线性回归 

分 类 号：TN115[电子电信—物理电子学] TP212.1[自动化与计算机技术—检测技术与自动化装置]