An Intelligent Prediction Water Quality Dosing System Based on Historical Data
A technology for intelligent forecasting and historical data, applied in general control systems, control/regulation systems, water pollutants, etc.
Active Publication Date: 2022-04-22
心鉴智控(深圳)科技有限公司
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Problems solved by technology
However, it is still necessary to manually operate the amount of chlorine, monitor emergencies and take corresponding measures
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[0028] In order to make the purpose, technical solution, design method and advantages of the present invention clearer, the present invention will be further described in detail through specific embodiments in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0029] refer to Figure 1 to Figure 3 , the present invention provides a system for intelligently predicting water quality dosing based on historical data, including: acquiring historical water quality monitoring data;
[0030] Call the pre-established prediction model, which is a prediction model obtained by training based on historical water quality monitoring data. The prediction model is used to judge the amount of chlorine added in real time, and collect the residual chlorine data generated by the amount of chlorine added. The model analyzes the residual chlorine data t...
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The invention provides a system for intelligently predicting water quality dosing based on historical data, including: a prediction model, which is a prediction model obtained by training according to historical water quality monitoring data, and the prediction model is used for real-time judgment on the amount of chlorine added, AI regression The device carries out intelligent training according to the real-time relevant data of residual chlorine impact recorded in the cycle T time, and obtains at least one optimized prediction model subunit, and the comparator is used to compare the optimized prediction model subunit obtained by the cycle T time training with the previous cycle The optimized prediction model subunits obtained by T time training are compared to obtain whether there is a difference outside the set deviation threshold, and analyze whether the difference outside the set deviation threshold is a positive difference, and the cycle T time training The obtained optimized prediction model sub-units are packaged and sent to the control terminal of the prediction model, and the control terminal updates the optimized prediction model sub-units obtained from the period T time training to the prediction model to optimize the prediction model.
Description
technical field [0001] The invention relates to the technical field of water treatment, in particular to a system for intelligently predicting water quality dosing based on historical data. Background technique [0002] Residual chlorine in tap water is an important indicator in tap water. Existing water plants are usually equipped with online residual chlorine detectors to control the residual chlorine standard in water within the national, industry or water plant’s own internal control standards. According to its fluctuation range adjust. Because the water quality of various water bodies is different, it is impossible to use the formula to measure accurately, and it can only be adjusted according to the operation experience over the years. Although the current water plants are basically controlled automatically, the operator only needs to operate the chlorine dosage on the computer in the central control room. However, it is still necessary to manually operate the chlori...
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IPC IPC(8): G06N20/00G05B13/02G05B19/05C02F1/58C02F101/12
CPCG06N20/00G05B13/0265G05B19/05C02F1/58C02F2209/005C02F2209/06C02F2209/14C02F2209/02C02F2209/22C02F2101/12
Inventor 肖罗罗晓忠孙海航
Owner 心鉴智控(深圳)科技有限公司