Soft and hard combined fly ash carbon content on-line monitoring method

Abstract

The invention discloses a soft and hard combined fly ash carbon content on-line monitoring method, which comprises the following steps: 1, obtaining a fly ash carbon content real-time measured value through a fly ash carbon content on-line detection device in the initial period of system commissioning; 2, collecting real-time measured values of the carbon content of the fly ash, establishing a database, and performing machine learning and data cleaning; 3, constructing a fly ash carbon content soft measurement model based on boiler characteristic parameters; 4, in the possible fault period of the fly ash carbon content online detection device, obtaining the fly ash carbon content and a sample for further cycle training by adopting a soft and hard measurement mutual correction method; 5, in the maintenance period of the fly ash carbon content online detection device, obtaining the fly ash carbon content soft measurement value through the fly ash carbon content soft measurement model; 6, after the fly ash carbon content online detection device is repaired, executing the step 1, according to the method, the fly ash carbon content online detection device and the fly ash carbon content soft measurement model are combined, and the fly ash carbon content is accurately measured.

Description

technical field [0001] The invention relates to the technical field of monitoring the carbon content of boiler fly ash, in particular to an online monitoring method for the carbon content of fly ash combined with soft and hard. Background technique [0002] Coal combustion is a very important primary energy source in my country, and 70% of the country's energy consumption depends on coal. At present, most of the power plants are in operation, and there are special energy-saving workers whose duties are to monitor the operating efficiency level of boilers and units, and calculate the reverse balance and positive balance according to some DCS data measured, the weight and characteristics of the coal into the furnace, etc. , to get the current thermal efficiency level of the boiler. [0003] The carbon content of fly ash is one of the main operating economic indicators and technical indicators of coal-fired boilers. It will not only directly affect the efficiency of the boiler...

AI Technical Summary

Problems solved by technology

[0007] However, soft sensing often requires a large amount of historical operating data of coal-fired power plants to build a model. The off-line detection data is matched with the real-time boiler operating characteristic parameters through artificial methods. The established prediction model also needs complex debugging and calibration on site. , after running for a period of time or when there is a big change in the combustion organization, the model correction and calibration are required again

Time-consuming, laborious and unsatisfactory test results

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