Design And Implementation Of Wireless Monitoring And Control System For SF6 Gas In Substation

With the large use of SF6 gas,the gas leakage is increasingly prominent,and the effective regulation of this gas has become more stringent.The gas regulation was clearly defined in the electrical safety work regulations.Nowadays,the corresponding monitoring equipment has certain limitations,the detection error is greatly affected by the outside influence,data acquisition is not timely and transmission by cable mode,which cause the prediction of future data and the line setting at the scene bring great restraint.How to achieve the data acquisition and wireless transmission in real time,making full use of mass monitoring data to analyze,and prediction reliably,will improve the early-warning ability of leakage.Based on the above problems,a SF6 gas wireless monitoring and control system is designed in this paper,the main contents are as follows.Through the analysis of existing equipment and detection principle,the bottom sensor for data acquisition and the concentrator for data forwarding are designed in this paper.In this paper,a dual-light and dual-wavelength differential detection model is constructed on the basis of the infrared spectrum detection principle,which has less characteristics of external influence and high sensitivity.On the basis of the optical system,the corresponding optical elements are selected and analyzed,at the same time,the temperature compensation circuit based on PT100 is designed to reduce the error caused by temperature disturbance.Based on LoRa wireless spread spectrum technology,using SX1278 chip,to achieve data transmission through the wireless.On the basis of low power consumption of the equipment,improving transmission distance and anti-interference ability,ensuring the safety of on-site equipment.Prediction analysis of SF6 gas concentration at monitoring points.Through the pretreatment of SF6 gas concentration,and using prediction validity as evaluation criterion,combining the grey relational clustering analysis to classify the data time series,dividing different groups,judging the prediction data and the correlation degree of each group.Finally,the concentration is predicted by Gaussian process regression model,achieving adaptive prediction of the future trend of concentration.Finally,the software and hardware are designed to analyze the function of each function modules,to achieve the SF6 gas wireless monitoring and control.