Electrical equipment operation condition classification method

Abstract

The invention relates to an electrical equipment operation condition classification method, which comprises the steps of building training data of a mean clustering model; pre-processing the training data, deleting invalid data and carrying out normalization processing; adopting a K-means++ algorithm for determining an initial clustering center; determining upper and lower limitations of clustering classification categories; circularly realizing a clustering process of multiple categories; carrying out evaluation analysis on a clustering result, and determining an optimal clustering category number K value; selecting an optimal K value model as an optimal condition classification result, so that the efficiency and the accuracy are improved.

Description

technical field [0001] The invention relates to the field of division of operating conditions of thermal power plants, in particular to a method for dividing operating conditions of electric power equipment. Background technique [0002] In my country's coal-fired thermal power plants, the boiler steam-water system is widely used, and the high-temperature superheater, as an important part of the steam-water system, plays an important role in the normal operation of the entire boiler. However, in actual thermal power plants, problems such as coking and overheating of the heating surface, unreasonable installation, long-term fixed-point blowing, and long-term unqualified steam quality of high-temperature superheaters often occur during operation, which seriously threaten the safety and security of power plants. Economic Operation. At present, the normal operation of the high-temperature superheater of the steam-water system in most thermal power plants in China depends on the...

AI Technical Summary

Problems solved by technology

In the actual application of power plants, the operating conditions of the system that humans can understand are limited, and a large part of the operating conditions of the system are far beyond human understanding, and professional knowledge cannot be given.

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