摘要
为解决浊度在线监测中数据波动大、不稳定的问题,设计了一种基于90°垂直散射原理的投入式浊度传感器,采用光源脉冲宽度调制技术,消除环境光的影响,通过PGA增益放大电路实现量程的自动切换,采用卡尔曼滤波算法对输出电压信号进行处理。结果表明,建立合适的浊度传感器卡尔曼滤波模型,不仅能减小观测噪声的影响,而且可以精确估计浊度传感器的输出状态,兼具跟踪和滤波效果,适合浊度传感器的现场实时监测。综上,设计的浊度传感器可广泛应用于农业生产各种监测场景中,具有一定的实际应用价值和推广价值。
In order to solve the problem of large fluctuation and instability of monitoring data in turbidity on-line monitoring,an immersible turbidity sensor based on the principle of vertical scattering was designed.The pulse width modulation technology of light source was used to eliminate the influence of ambient light.Automatic range switching achieved through PGA gain amplifier circuit.The Kalman filter algorithm was used to process the output voltage signal.The experimental results showed that establishing a suitable turbidity sensor Kalman filter model could not only reduce the impact of observation noise,but also obtained an accurate estimate of the output status of the turbidity sensor,combining tracking and filtering effects.It was suitable for real-time monitoring of turbidity sensors.In summary,the designed turbidity sensor can be widely used in various monitoring scenarios of agricultural production,and has certain practical application value and promotion value.
作者
郝甜利
田孝平
张城振
贾小虎
胡博
HAO Tianli;TIAN Xiaoping;ZHANG Chengzheng;JIA Xiaohu;HU Bo(Zhengzhou Guan Ao Instrument and Meter Company Limited,Zhengzhou,Henan 450000,China;Henan Agricultural University,Zhengzhou,Henan 450000,China;Henan Institute of Metrology,Zhengzhou,Henan 450000,China)
出处
《天津农业科学》
2025年第9期71-78,共8页
Tianjin Agricultural Sciences
关键词
浊度
在线监测
卡尔曼滤波
turbidity
online monitoring
Kalman filtering
