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离子传感器是环境水质监测的关键技术之一。由于传感器制备技术的局限性以及应用环境的复杂性,严重影响了传感器的测量精度以及可靠性,难以用于在线检测。为了给水质在线检测提供有效的分析手段,以铵离子传感器为背景,在深入研究传感器响应特性后,根据实验数据,使用支持向量机回归建立传感器响应的离线模型;进一步使用在线支持向量机回归建立传感器的漂移校正模型。实验结果表明:建立的模型能较好地拟合响应过程曲线,有效地补偿了传感器的漂移。
Ion sensor is one of the key technologies of environmental water quality monitoring. Due to the limitations of the sensor preparation technology and the complexity of the application environment, the measurement accuracy and reliability of the sensor are seriously affected, making it difficult to be used for on-line detection. In order to provide an effective method for on-line water quality testing, taking the ammonium ion sensor as the background, after in-depth study of the sensor response characteristics, an offline model of the sensor response was established by using support vector machine regression based on the experimental data. Furthermore, the online support vector regression Sensor drift correction model. Experimental results show that the established model can well fit the response curve and effectively compensate the sensor drift.