Year: 2024
Type: article
Abstract: For the temperature drift phenomenon of SF6 gas concentration sensor in high-voltage electrical equipment, the compensation accuracy of the sensor is improved by establishing the temperature compensation model of gas concentration sensor with RBF neural network, and combining the particle swarm optimization algorithm for the optimization of parameters of RBF temperature compensation model. The experimental results show that the method can better compensate the temperature of the gas concentration sensor, and the output of the compensated sensor is less affected by the ambient temperature, with a maximum error of 20 ppm over the full scale range.
Authors: Qing Wang, Md Gapar Md Johar, Jacquline Tham
Institutions: Management and Science University, Anhui Xinhua University
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4401769782