Dynamicand static characteristic collaborative analysis on-line monitoring method for mega-kilowatt ultra-supercritical unit

Abstract

The invention discloses a dynamicand static characteristic collaborative analysis on-line monitoring method for a mega-kilowatt ultra-supercritical unit to solve the problems of the mega-kilowatt ultra-supercritical unit that process variables are numerous and controller regulation is complex. Typical variables are used for analyzing and extracting time series related information of process data.The slow feature analysis algorithm is combined. Time series related information and dynamic and static information of controller regulation relative to the running state are extracted. The dynamicandstatic online monitoring index is established to conduct process monitoring to the mega-kilowatt ultra-supercritical unit. The method can fully reflect the regulation of a closed-loop system, and cangreatly improve subsequent process online monitoring performance. Understanding of complex processes characteristics can be facilitated. Reliability and credibility of mega-kilowatt ultra-supercritical unit online process monitoring are improved. A thermal power plant is assisted to make an accurate judgment on the operating state of the unit and find faults timely. Safe and reliable operation ofthe mega-kilowatt ultra-supercritical unit is guaranteed.

Description

technical field [0001] The invention belongs to the field of thermal power process process monitoring, and in particular relates to an online process monitoring of dynamic and static coordination of a million-kilowatt ultra-supercritical unit by considering the adjustment effect of a closed-loop system, comprehensively analyzing the time-series correlation relationship of process variables and the dynamic and static characteristics of the process. method. Background technique [0002] In the rapidly developing 21st century, with the improvement of industrial automation and the trend of economic globalization, the thermal power industry is developing in the direction of large-scale and complex. At the same time, in order to achieve the sustainable development of electric power, the thermal power industry is actively carrying out structural adjustments, replacing high-energy consumption small thermal power units with large-capacity, high-parameter, low-energy supercritical and...

AI Technical Summary

Problems solved by technology

However, existing data analysis methods, such as principal component analysis, partial least squares method, and Fisher's discriminant analysis, only consider the static information of the process and ignore the regulatory role of the closed-loop system in the process.

Therefore, applying it to a mega-kilowatt ultra-supercritical unit cannot obtain a good monitoring effect

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