Intelligent identification model for four-tube leakage of power plant boiler

Abstract

The invention provides a power plant boiler four-tube leakage intelligent identification model. The power plant boiler four-tube leakage intelligent identification model comprises the following steps: S1, establishing boiler four-tube leakage monitoring indexes; s2, establishing boiler four-tube leakage monitoring index characteristics; s3, calculating a real-time risk coefficient of the boiler four-tube leakage monitoring index; and S4, calculating a boiler four-pipe leakage real-time comprehensive risk coefficient. The power plant boiler four-tube leakage intelligent identification model provided by the invention realizes early identification of four-tube leakage, and has the advantages of reducing the boiler damage scale, reducing the inspection and maintenance cost, properly making a maintenance plan and shortening the maintenance time.

Description

Technical field [0001] The present invention relates to the field of intelligent identification of electric plant boiler four-tube leakage, and in particular, there is an intelligent identification model of a factory boiler four-tube leakage. Background technique [0002] With the development of power generation technology, the boiler of modern power plant has entered a large capacity, high parameter era, and the pressure of boiler work tube is continuously improved, and the leakage of boiler four tubes is more serious. Once the boiler is leaked, the shutdown is inevitable, but not only directly affects the economic benefits of the power plant, but threatens that personal safety, and even affect the safe and smooth operation of the grid. There is statistics to indicate that the leakage of the fire power plant boiler four tube is gradually developed by tiny leakage. At the same time, high-speed jets formed by high temperature and high pressure steam in the leak development process...

AI Technical Summary

Problems solved by technology

Manual monitoring based on SIS / DCS disk data relies heavily on the work experience of managers, and objectively it is still impossible to achieve 24-hour continuous monitoring

The sensor-based sound explosion venting monitoring system is expensive and difficult to construct, and requires modification of the boiler body. However, in actual effect, among the more than 100 explosion venting records of several major power generation groups in China from 2017 to 2019, the sound monitoring system took the lead. The identified leakage incidents only reached about 33%

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