Abstract

Power equipment deterioration occurs during operation, it causes loss in reliability and efficiency, unscheduled shutdowns, and accidents. Now predictive analytics is one of the promising directions in the field of power engineering which allows to control and analyze the technical condition of power equipment. The problems of localization of deviation of technological parameters and detection of anomaly in the operation of power equipment are consistently solved in the framework of predictive analytics. The problems of deviations localization and anomalies detection are solved by the methods of statistical modeling and the classification algorithms respectively. However, for steam turbines the localization of deviation and the detection of anomalies having slow-flowing character are a difficult problem. Therefore, the issue of development of a method for continuous monitoring of technical condition and maintenance diagnostics based on a mathematical model of the steam turbine section flow characteristics is worth noticing. The method allows us to consider the effect of changes in the open flow area of the individual sections of a steam turbine on the pressure distribution over the steam flow path. The model of a steam turbine has been developed within the matrix formalization methodology. The solution of the system of linear and nonlinear equations is carried out by methods of computational mathematics. The solution of the optimization problems of the steam flow path diagnostics is carried out by methods of mathematical programming. A mathematical model of the cogeneration steam turbine Т-250/305-23.5-DB and a method for continuous condition monitoring and maintenance diagnostics of steam turbine have been developed. It allows us to localize deviation and detect anomaly by recovery of the open flow area of the individual sections of a steam turbine based on the pressure distribution over the steam flow path. The results of the statistical analysis prove that a mathematical model of the cogeneration steam turbine Т-250/305-23.5-DB has been recognized adequate. The method for continuous condition monitoring and maintenance diagnostics of steam turbine has demonstrated consistency of the obtained results and ability to solve diagnostic problems in practice. The developed model and method can be used as a module in the development of a software package for predictive analytics of power equipment.

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