Differential pressure sensor temperature compensation method and system based on GA-BP neural network

• Main Authors: HAM CHEOLYONG, WANG TIANYI, XIA TIAN, MAO ZHIPING, ZHANG CHAOFENG, HUANG CHEN, KANG WEN, YI RUI, HUANG LIBIN, ZHANG YUYANG, REN RUIWU, HUANG JINJUN, XU AO, WANG QING, XIA XIANGYANG
• Format: Patent
• Language: Chinese; English
• Published: 21.06.2024
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; MEASURING; MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER,MECHANICAL EFFICIENCY, OR FLUID PRESSURE; PHYSICS; TESTING

The invention discloses a differential pressure sensor temperature compensation method based on a GA-BP neural network, and the method comprises the steps: training a model based on the GA-BP neural network through preset data, and obtaining a first model; acquiring a real-time pressure value through a differential pressure sensor to obtain a first pressure, and acquiring a temperature value through a temperature sensor in real time to obtain a first temperature; converting the first pressure to obtain a first voltage; the first voltage and the first temperature are input into a first model, and the first model outputs a second voltage; and the second voltage is converted to obtain second pressure, and differential pressure sensor temperature compensation is completed. The invention further discloses a differential pressure sensor temperature compensation system based on the GA-BP neural network. 本发明公开了一种基于GA-BP神经网络的差压传感器温度补偿方法，包括：使用预设数据训练基于GA-BP神经网络的模型，得到第一模型；通过差压传感器采集实时压力值，得到第一压力，并通过温度传感器实时采集温度值，得到第一温度；将第一压