Hydroelectric generating set vibration trend prediction method and system

Abstract

The embodiment of the invention provides a hydroelectric generating set vibration trend prediction method and system. The method comprises the steps: collecting an original signal feature set of a hydroelectric generating set; analyzing the correlation between each intrinsic mode component and the environment variable based on a maximum information coefficient (MIC), and extracting the environment variable of which the correlation is greater than a preset correlation threshold as the environment feature of each intrinsic mode component; forming a feature input sequence by each intrinsic mode component and the corresponding environment feature, taking the feature input sequence as the input of a neural network according to a time sequence, and performing neural network training to obtain a vibration trend prediction model; and enabling each intrinsic mode component of the current hydroelectric generating set to be predicted and the corresponding environmental characteristics to form a characteristic input vector, inputting the characteristic input vector into the vibration trend prediction model for prediction, and fusing all prediction results to obtain a future trend prediction value of the hydroelectric generating set, so that the precision and stability of the vibration trend prediction result are greatly improved.

Description

Technical field[0001]Embodiments of the present invention relate to the technical field of hydropower units, in particular, to a hydropower unit vibration trend prediction method and system.Background technique[0002]At present, my country's large watersheds have been built into a world-famous row, and the power supply capacity and annual power generation of hydropower stations are ranked first in the world. Hydroelectric power plant, a pump turbine, power generator, main transformer, etc., is the core of the energy supply function and economic benefits of hydropower station, which is equipped with multiple tasks such as power grid peaks, flexographic phase, rotating spare. Frequent factors such as frequent, hydraulic shock, mechanical failure, and electromagnetic imbalances may induce hydraulic power generation, structural fatigue, electrical failure, operational mode destruction, etc., are extremely serious. Therefore, the strategic needs of the development of smart hydropower stat...

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present invention provides a method and system for predicting the vibration trend of hydropower units, which is used to solve the problem that in the prior art, useful information cannot be completely extracted, the standard of feature selection is not generalizable, and the prediction under massive data takes a long time. The problem of training time

Images