Research And Application On Intelligent Diagnosis Big Data System Of Turbo-generator Unit

With the deepening of China’s electric power constitutional reform,the share of new energy in the power grid composition is increasing year by year.In order to reduce the influence of randomness and uncontrollability of new energy on the operation stability of power grid and ensure the quality of power supply,it has become normal for large-capacity steam turbine units to participate in peak and frequency regulation of power grid.The intervention of more operating condition factors brings great challenges to the stable operation of the steam turbine set.The thermal power industry has put forward higher requirements for the monitoring and diagnosis of the running state of the steam turbine set.The development of information technology promotes the intelligent diagnosis of power generation equipment to enter the era of big data.The academic thought of "data is king" is expected to become the mainstream,and it is possible to fully grasp the operating state of the whole machine or system.Big data technology provides favorable conditions for digging the deep rules of equipment operation,comprehensively analyzing the rules of equipment deterioration,and grasping the health condition of the unit has become a new trend.First of all,combined with the characteristics and business scenarios of intelligent diagnosis big data of power generation equipment,the application technology route of diagnosis big data is established,and the key issues in the construction of big data analysis system are studied,forming the application system of big data in the field of intelligent diagnosis of power generation equipment,laying a theoretical foundation for subsequent research.Secondly,from the perspective of the system structure of the steam turbine unit,a comprehensive description of the turbine body and generator component equipment information is made to clarify the main functions and operating characteristics of each equipment.Based on the method of Failure Mode and Effects Analysis and Fault Tree Analysis,this paper analyzes the mechanism of typical faults of turbo-generator sets,sorts out the information of unit fault symptoms,causes,effects,risks,maintenance measures and so on,forms the data information sources of unit status monitoring and maintenance.Next,based on the actual user and monitoring system functional requirements,determine the main functional modules and specific content of the operation status monitoring and maintenance system of the turbogenerator set.The big data system is constructed to meet the functional requirements for the operation monitoring,fault diagnosis and maintenance decision-making of the steam turbine unit.From the point of view of data flow,it explains the invocation and realization of the database content in the system running.Finally,the technical framework of the big data system is applied to engineering practice,and the entity system of the operation state monitoring and maintenance of the steam turbine generator set is developed and completed.The analysis work of the condition monitoring,diagnosis and maintenance of the steam turbine generator set is carried out,so as to realize the transformation of technical achievements of the research work and engineering application.