| Gas is an important energy source in urban life,and gas pipelines play an indispensable role as a carrier for transporting and distributing gas.As gas is flammable,explosive,and toxic,once a gas pipeline accident occurs,it will have serious consequences and will have an important impact on people’s lives,property,economy,and society.Therefore,gas risk assessment is of great significance.However,most of the existing evaluation techniques are based on qualitative or semi-qualitative methods,relying on expert judgment,and the factors considered are not detailed enough,lacking accuracy and objectivity.Therefore,the construction of an accurate and quantitative risk assessment plan and a reasonable,efficient and strict risk assessment management system is an urgent problem to be solved.In view of the above problems,this paper investigated and analyzed the existing risk assessment plans,combined with a large amount of data provided by a gas company,used machine learning methods to refine risk factors,and proposed a risk assessment method based on pipeline points.The failure probability level and failure consequences of gas pipelines are considered.A large amount of data was analyzed in terms of failure probability.The random forest algorithm in machine learning was used.The algorithm was improved according to the characteristics of unbalanced gas risk data,and the cost was introduced.Based on the idea of sensitive learning,this paper added the compensation cost and damage cost after the gas risk failure to the misclassification cost,and performed weighted voting based on the performance of the base classifier.In terms of the consequences of failure,quantified the degree of harm to the human body caused by the gas explosion,and circled the nearby buildings within the affected area,analyzed the population of the buildings,and refined the scope of impact,making therisk assessment results more accurate.According to the above methods,this paper designed and implemented a risk assessment system for danger points of gas pipelines,and conducted detailed demand analysis and functional design for each module of the system.Based on the secondary development capabilities of ArcGIS,the core functions of the system are developed.The system used ReactJS and NodeJS to design and developed other functions,and the function and performance of the system were tested.The usability,versatility and practicability of the system were proved through various tests.The system can not only conduct a more accurate assessment of risks,but also standardizes the follow-up process of risks to ensure the safe operation of gas pipelines,which is of great significance for the management and maintenance of gas resources. |