Research On Detection And Location Technology Of Gas Leakage Point

The application of gas in various fields such as daily life,aerospace,industrial and agricultural production,national defense,and medical care is common,and the accompanying gas leakage accidents occur from time to time.In the backdrop of storage leakage of N₂O₄ gas in a relatively confined warehouse,this paper presents a study on the monitoring and localization of gas leakage by using Zig Bee wireless sensor network technology,combining weighted centroid positioning algorithm and Genetic Algorithm（GA）based on gas turbulence model,and improving the Genetic Algorithm.While completing gas leak monitoring,it optimizes the positioning performance and provides technical support for timely handling of gas leaks.The main work carried out was as follows:1.Taking static sensor networks as the research direction of gas monitoring and positioning technology,the relevant theories and technologies were analyzed,and the overall technical solutions was designed.The monitoring nodes of the wireless sensor network were constructed by connecting the Zig Bee wireless module with the gas sensor.Information interaction was carried out between the coordinator and the upper computer,and monitoring data display,storage and positioning functions are completed on the monitoring platform designed by the upper computer.The localization function was realized based on the gas turbulence model and genetic algorithm was used as the main algorithm of inversion localization.2.The gas leakage location algorithm was studied.The formulas of the gas turbulence model were analyzed and derived.The weighted centroid positioning algorithm combined with genetic algorithm was used for positioning calculation.Meanwhile,to further improve the positioning performance,the initialization of the population is optimized by using chaotic mapping,the adaptive genetic operator ensures the good search performance,and finally the convergence speed of the algorithm is improved by combining with the particle swarm optimization algorithm,so as to ensures the stability and accuracy of the algorithm.In the simulation,a Gaussian white noise of 5%of its own concentration was added to simulate the error of the real leakage environment.The simulation results show that the relative localization error based on the improved genetic algorithm is less than 4%,and the average relative error is about 2.5%,which is more accurate than the weighted centroid positioning algorithm and the genetic algorithm-based localization.3.The experimental system was designed and built.Due to the highly toxic characteristics of N₂O₄gas and the particularity of monitoring environment,the experimental gas was determined to be ethanol gas by comparison.The experimental system included the design of hardware nodes and the development of software programs,and finally the commissioning of the experimental system was completed.Each hardware node can realize the effective collection and transmission of data,and the upper computer monitoring platform can complete the display,storage and query,alarm and positioning of gas concentration data.Multiple ethanol positioning experiments were conducted in a closed laboratory using a humidifier.The average relative positioning error is about 4%,which is less than the simulation experimental results and can achieve the positioning requirements.