基于最小二乘支持向量机的离子传感器自校正的研究  

Study of Self-Calibration for Ion Sensor Based on LS-SVM

作　　者：陈锋[1] 杨大福[1] 方科[1] 王兵[1] 

机构地区：[1]中国科学技术大学自动化系,合肥230027

出　　处：《模式识别与人工智能》2007年第1期115-118,共4页Pattern Recognition and Artificial Intelligence

基　　金：安徽省教育厅重点自然科学基金(No.2006KJ028A)

摘　　要：离子传感器是环境水质监测、污水处理、设施农业等领域的关键技术之一.由于离子传感器的非线性、漂移和交叉敏感性等影响其检测精度和可靠性,难以进行连续在线检测.本文研究硝酸根离子传感器的自校正方法,以适应动态环境的连续监测.根据实验数据,详细分析硝酸根离子传感器的响应特性,考虑零点和时间漂移,基于最小二乘支持向量机,提出一种硝酸根离子传感器的自校正方法,并给出详细描述和分析.实验结果表明其较显著地降低离子传感器的响应误差,验证本文所提方法的有效性.The ion sensor（ion selectivity electrode） is one of the key technologies in the water quality monitoring, wastewater treatment and factory agriculture. The non-linearity, drift and intercross sensitivity of the ion sensor impact on the accuracy and reliability obviously, therefore, it is difficult for majority of the ion sensors to continuously detect in situ. In order to detect dynamic environment on line, self-calibration of the ion sensor is investigated and its response properties are analyzed in terms of the experimental data. The zero and time drift are taken into account, and a self-calibration of ion sensor is proposed based on least squares support vector machines （LS-SVM）. The experimental results show response error of the ion sensor is decreased obviously and this approach is practical.

关 键 词：离子传感器 最小二乘支持向量机(LS-SVM) 自校正 漂移 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]