A fault warning method for a wind turbine generator

Abstract

The invention discloses a fault early warning method for a wind turbine generator. The method includes the following steps: collecting historical operating data of the entire fault evolution interval of the wind turbine generator, selecting parameters reflecting the generator operating state as modeling variables, and Normalize generator operating state parameters, establish DBN network, optimize the number of neurons in the hidden layer, and use the optimal number of neurons to establish a generator failure early warning model; reconstruct generator operating state parameters, and calculate and reconstruct The reconstruction error between the variable and the actual variable determines the reconstruction error threshold. When the reconstruction error does not exceed the threshold, it is judged that the generator is running normally; when the reconstruction error exceeds the threshold, it is judged that the generator is abnormal and sends Fault warning information. The invention provides judgment basis for the early fault detection of the generator of the wind turbine, so as to realize the early warning of the fault of the generator of the wind turbine.

Description

technical field [0001] The invention relates to a fault early warning technology for a wind turbine, in particular to a fault early warning method for a wind turbine generator. Background technique [0002] During the long-term operation of wind turbines, with the continuous increase of operating time and the natural environment with changing forces, harsh conditions and complex working conditions, the main components such as generators, gearboxes, main bearings, yaw systems, etc. The failure rate of components has increased significantly. As the core component of wind turbines, the failure of wind turbines is one of the main reasons for the shutdown of wind turbines, which seriously affects the safe and stable operation of the entire unit. Therefore, the use of accurate detection technology for early fault warning of generators can effectively reduce the failure rate of wind turbines and reduce the loss of wind farms. [0003] Wind turbines are a highly interrelated syste...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a fault early warning method for wind turbine generators, to solve the problem that most of the existing fault diagnosis methods are aimed at a single parameter, and cannot be practically applied due to the low accuracy of the mathematical model used and the short early warning time

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