Research On Equipment Condition Monitoring And Early Warning System Based On Big Data Technique

Currently, most power plants have deployed power plant control systems, supervisory information system(SIS) and a wide variety of manager information systems. These systems have accumulated mass data of equipments. How to translate these data into the decision information of the production and operation of the power plant by means of the big data analysis technology is the key to the information data, the state and the intelligent decision of the modern thermal power plant.This paper describes the equipment status online monitoring and early warning diagnosis system is based on big data technology. From the massive historical data of equipment operation, the various operation conditions and parameters of the equipment were analyzed to establish the dynamic state monitoring model, The abnormal change of equipment is more accurate and more sensitive in the process of equipment operation, To discover the DCS and artificia l inspection equipment, The realization of enterprise and plant production data mining and fault early warning device.In this paper, the application of equipment condition monitoring system based on large data in a 300 MW unit in C hina is introduced in detail. Through in- depth study of large data technology, comb ined with the actual operation of thermal power plant equipment, select the appropriate data mining algorithm to establish the model of the key equip ment of the power plant. In the modeling process, whether it is data integration, data cleaning or data min ing, has reflected the combination of large data technology and power plant professional. At the same time, this paper mainly introduces the modeling process of the key equip ment of the power plant, such as the oxidation fan, the condensate pump and the coal mill, and the actual monitoring situation after the model construction, And the monitoring and early warning of these devices in the form of a case analysis of the key analysis.