Research on Temperature Compensation of Submersible Water Level Meter Based on BP Neural Network
WANG Yongwang
WANG Junlin
ZHANG Yucong
XU Shuoyan
Abstract：Through analyzing the working principle of the input water level meter,it was clear that temperature was the main source of error of submersible water level meter.Using the water data of reservoir,the correlation analysis of reservoir water level with water temperature,input depth and float water level was carried out by the Pearson correlation coefficient method,and on this basis,a BP neural network correction model was constructed.Finally,through training tests,it was found that the proposed method could effectively eliminate the nonlinear influence of water temperature on the accuracy of submersible water level meter.
Keywords：submersible water level metertemperature compensationBP neural network
Publication Date：2025-01-27
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 90-94 )