Intelligent calibration method and system for reflection type water level gauge in front of gate based on edge calculation
An edge computing, reflective technology, applied in the field of intelligent calibration of reflective water level gauges in front of the gate, to reduce the impact
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Embodiment 1
[0042] Such as Figure 1-2 As shown, this embodiment provides an intelligent calibration method and system for reflective water level gauges in front of gates based on edge computing, using on-site embedded computers, high-precision water level calibration platforms, multi-element sensors combined with thermal-mechanical coupling theory and machine learning methods, By sensing the output signal of the water level gauge and the environmental information at the same time, and adopting the strategy of establishing a measurement error correction model offline regularly and outputting it online in real time, the intelligent calibration of the water level in front of the gate is realized.
[0043] The method can be extended to occasions where reflective water level gauges are used behind gates, in front of dams, in channels, etc., to realize high-precision monitoring of water levels.
[0044] Self-check the system equipment to determine whether the system equipment is normal. If not...
Embodiment approach
[0054] As an implementation, the underwater tray is used as the reference plane for calibration, and after the optimal measurement error correction model is determined, the underwater tray is vertically put away until it is close to the wall where the upper and lower vertical guide rails are located, Then measure the water level in front of the gate online.
[0055] As an implementation, during the calibration process, the vertical movement of the water level measuring device and the bracket is within the range of the reflective water level gauge; mid-range of the meter.
[0056] As an implementation, correlation vector machine (SVM), long short-term memory (LSTM), encoding-decoding neural network model and gated recurrent unit (GRU) are selected as the measurement error correction model.
[0057]As an implementation, the method for comprehensively evaluating the trained measurement error correction model includes: by randomly selecting multiple sets of input combinations, ca...
Embodiment 2
[0063] Such as Figure 1-2 As shown, this embodiment provides a system for intelligent calibration of the reflective water level gauge in front of the gate based on edge computing. Device 4, leveling mark 5 and reinforced concrete pier surface 6, wherein the measuring device and support 1 are used to measure the water level in front of the sluice as well as meteorological and transparency data; the support precision lifting control device 2 is used to drive the water level measuring device and support to a fixed interval height Move up and down and fix it; the reference surface providing device 3 is used to provide a stable water surface reference during calibration and ensure that the water flow and water surface will not be affected during measurement; the measurement communication control device 4, the measurement device and the bracket 1, the bracket precision lifting control device 2 and the reference surface Provide device 3 connection for measuring sensors, controlling ...
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