Fan gearbox performance detection and health evaluation method based on temperature parameters

Abstract

The invention discloses a fan gearbox performance detection and health evaluation method based on temperature parameters. According to the method, fan state detection data are analyzed, the operationcharacteristics of a wind turbine generator unit are combined, state detection and fault prediction are carried out on the temperature of a gearbox and the temperature of a gearbox bearing by adoptinga model established by combining KECA and GRNN, an evaluation decision is performed on the running state of the fan gearbox through ideas of threshold discrimination and statistical process control according to predicted residual error, and a gearbox health state result is obtained by adopting comprehensive fuzzy discrimination. When the method is applied to an actual wind turbine generator unitcase with small sample data, the health state of the wind turbine generator unit can be accurately predicted and evaluated. The method is applied to an actual wind turbine generator unit with small sample data, and the health state of the wind turbine generator unit can be accurately predicted and evaluated.

Description

technical field [0001] The invention is a performance detection and health assessment method applied to wind turbine gearboxes, especially considering the characteristics of a large number of diverse and nonlinear SCADA parameters of wind turbines, and improving the reliability of the gearbox health assessment method; it belongs to data-driven state detection, Fault early warning and health assessment technology field. Background technique [0002] With the continuous increase of human energy requirements and the rapid development of the power industry, the wind power industry has become the main development trend of clean energy due to its relatively low cost, abundant wind resources, and green energy. The maintenance cost after the completion of the wind farm directly determines the benefit of the wind farm. The wind power project is a project with a long investment time, about 7 years, and the profit period is also very long, even more than 10 years. Long-term operation ...

AI Technical Summary

Problems solved by technology

[0003] Considering the large variety and nonlinear characteristics of wind turbine SCADA parameters, there is a lack of general guidelines for the selection and processing of the input parameters of the prediction model

Moreover, the choice of predicted state parameters is single, and the health analysis of the gearbox based on a single state lacks reliability. Therefore, a state assessment method for wind turbine gearboxes based on state detection and prediction models is proposed.

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