Intelligent gate control method based on artificial intelligence

Abstract

The invention discloses an intelligent gate control method based on artificial intelligence, and relates to the field of gate control. The method comprises the following steps: 1 acquiring historical operation data in a period of time from a sluice integrated automation system database; standardizing the data, and dividing the data into a training set and a test set; 2 establishing a static analysis model; 3 establishing a dynamic analysis model; 4 establishing a short-term prediction model; and 5 enabling operating personnel to start the deduction values of the static analysis model and the dynamic analysis model to issue a gate opening height operation command according to the actual situation of the site. The method can effectively solve the problems of large workload and low intelligence degree of a gate operation mode depending on artificial experience, improves the intelligence level of a water gate operation management unit, reduces the workload of the operating personnel, and has a high practical value.

Description

Technical field [0001] The present invention relates to a shutter control, and more particularly it is an intelligent control gates artificial intelligence based methods. Background technique [0002] In a river, canal hydraulic engineering, etc., is generally adjusted by controlling the height of the shutter opening river level and flow; now adjust the water level, flow rate mainly depends on human experience and judgment to operate the shutter, is not high degree of intelligence; north River sluice, for example, take the gate current control strategy is as follows: [0003] When the upstream water level exceeds a certain set level, the height of the lift portion of the gate to drain until the water level falls below a predetermined level; this point is running in the current art typically binds and downstream water flow, the height of the shutter opening empirically exploratory adjustment, observed during the whole required level changes, and make the appropriate adjustments; ...

AI Technical Summary

Problems solved by technology

[0004] Through the analysis of historical operation data, it is found that in most cases, the entire process of gate adjustment lasts from a few minutes to a few hours, and multiple adjustments may be made in a day, and the adjustment time often occurs at night or in the early morning. The workload is large; in addition, in the seasons when floods and typhoons occur frequently, the water level changes frequently, and operators need to monitor the water level changes and control the gate at all times, and the workload increases significantly; therefore, the traditional gate control strategy that relies on manual experience is time-consuming Power-consuming and the control effect cannot be optimal

Images