The adaptive intelligent dosing system based on machine vision applied to industrial water treatment was introduced in detail. By automatically adjusting the dosage of water treatment chemicals,the alum generation efficiency was optimized and the overall cost was reduced. The system used an underwater high-definition camera to capture the alum flower image in real time,and combined the depth-resistance migration learning technology and U-net model to accurately detect the alum flower shapes,and optimized the coagulant dosing strategy through the LSTM model and the adaptive control algorithm. So this control strategy not only enhanced the adaptability of the system to changeable water quality conditions,but also significantly improved the generalization ability of the model. As a result,the experimental and applied results showed that the system could effectively improve the water treatment efficiency,reduced the dosage of chemical agents,reduced the manual intervention,enhanced the ability of automatic operation,and thus confirmed the application value of intelligent technology in the field of industrial water treatment.
关键词
工业水处理/智能加药/机器视觉/深度学习/自动化控制
Key words
industrial water treatment/intelligent dosing/machine vision/deep learning/automatic control
维普
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