摘要
阐述污水处理生物池曝气状态的监控和识别,基于机器视觉的曝气监控系统的设计,集成摄像头接入、样本采集、模型训练和工控及业务系统的数据对接,建立基于卷积神经网络的曝气图像识别模型并进行了模型验证。此系统在污水厂生物池应用,建立曝气图像获取、识别、报警的联动机制,从而实现水厂智能化巡检。
This paper expounds the monitoring and identification of the aeration state of the sewage treatment biological tank, the design of the aeration monitoring system based on machine vision,the integration of camera access, sample collection, model training and data docking of industrial control and business systems, the establishment of an aeration image recognition model based on convolutional neural network and the model verification. This system is applied in the biological tank of the sewage plant to establish the linkage mechanism of aeration image acquisition, recognition and alarm, so as to realize the intelligent inspection of the water plant.
作者
沈彦
SHEN Yan(Shanghai SIPAI Intelligent Systems Co.,Ltd.,Shanghai 200233,China)
出处
《集成电路应用》
2022年第8期50-53,共4页
Application of IC
基金
上海市青年拔尖人才计划项目。
关键词
智能化控制系统
曝气
机器视觉
卷积神经网络
intelligent control system
aeration
machine vision
convolutional neural network