Diagnosis Method Research Of Oil-gas Pipeline Failure Mode

Pipeline transportation is the most economical and reasonable transport mode of oil and natural gas. With the large number of oil and gas pipeline laying and the growth of service time, the failure incidents of pipeline happened frequently, which brought great losses for peoples'life and property. There are many factors influencing pipeline failure. Some of them are random, fuzzy, incomplete and other characteristics, traditional diagnostic methods are often not adaptive for pipeline failure mode analysis. Intelligent information processing theory and technology is an artificial intelligence method which is researched and applied extensively in various engineering fields and science research in recent years, because its correlation model has highly nonlinear mapping capability, large-scale parallel processing and good adaptive learning mechanism, it is very suitable for solving the problems which the traditional pattern recognition and prediction methods are difficult to model. Therefore, it has good adaptability for the Intelligent information processing method and technology which are applied in the pipeline failure mode diagnosis.In view of some typical issues of pipeline failure mode diagnosis, the paper mainly researches the pipeline failure mode intelligent diagnosis theory and application technology. Combines the Artificial Neural Network theory and diagnosis theory, pattern recognition, fuzzy logic with system simulation methods which are widely used in pattern recognition and dynamic forecasting field, construt the intelligent diagnosis technology and model which are suitful for pipeline failure mode analysis, and carry on solution algorithm and application technology research.On the side of intelligent diagnosis method and model research, the paper summarize three types of pipeline failure mode diagnosis problems, they are numerical mode diagnosis, fuzzy information mode diagnosis and dynamic mode diagnosis on the basis of analyzing gas pipeline failure modes and fault diagnosis modeling technology, and construct different intelligent model to complete the solution of above-mentioned different problems.Aimed to the numerical mode diagnosis problem, we construct the adaptive method used to define BP networks structure and completing mechanism, and apply it into the failure modes of pressure pipes with defects;To the fuzzy information mode diagnosis problem, considering the unclear relationship between conditions and results and the importance degree of conditions impacting on results, a weighted fuzzy reasoning networks is constructed based on traditional fuzzy neural networks. It solves the fuzzy information of corrosion data impacting on pipeline corrosion degree better. To the dynamic mode diagnosis problem, process neural networks is combined with RBF neural networks, and the concept and model of RBF process neural networks are introduced, the model integrates the advantages of process neural networks which can express the cumulative effect of the dynamic process and the RBF networks nonlinear function has strong approximation capabilities, it has a good adaptability for the prediction problem of pipeline corrosion rate changing nonlinearly with time. At the same time, in view of the problem of process variables trend prediction, the structural ideas and methods of traditional support vector regression machines are extended to time-varying function space. We establish a process support vector regression machines, the model can solve the time prediction problem of dynamic system better.On the side of application technology, the paper gave the application methods and solution process of some typical pipeline failure mode diagnosis problems using intelligent diagnosis model. These problems include pipeline leak diagnosis, pipeline corrosion failure mode diagnosis, pipeline corrosion rate prediction, pipeline failure mode diagnosis with defective pressure and pipelines insulation fault diagnosis analysis,etc, and all of them get the better application results.The paper establishes the related intelligent diagnostic model and methods contrary to some typical problems of pipeline failure mode diagnosis, and carries on the practical application research. It provides a kind of scientific method for the oil-gas pipeline failure accident analysis and the integrity assessment of pipeline running, can provide scientific basis for risk assessment and management decision-making of pipelines, and it has important practical significance and application prospects.