Wind turbine generator state-of-health online monitoring and fault diagnosis method based on SOM-MQEs and SFCM

Abstract

The invention discloses a wind turbine generator state-of-health online monitoring and fault diagnosis method based on SOM-MQEs and an SFCM. The method comprises the steps of firstly, processing obtained real-time data according to a local outlier factor algorithm, a partial least squares method and a Laplacian Eigenmap dimension reduction technology, and extracting important characteristic parameters influencing the state of health of wind turbine generators; secondly, inputting the characteristic parameters to an SOM-MQE state-of-health evaluation model, calculating health decay indexes of the wind turbine generators, and evaluating the state of health of the wind turbine generators; finally, utilizing a fuzzy c-means soft clustering algorithm for clustering analysis on operating data ofwind turbine generators with abnormal states to determine the fault types of the wind turbine generators. By means of the method, the state of health of the wind turbine generators can be monitored accurately in real time, faulty parts are accurately positioned, the accuracy of detecting the state abnormality of the wind turbine generators reaches 99.9% or so, and a guiding idea is provided for corresponding maintenance by maintenance personnel aiming at the real-time operating condition of a draught fan.

Description

technical field [0001] The invention relates to the field of wind power generation technology and computer monitoring technology, in particular to an online monitoring and fault diagnosis method for the health status of wind turbines based on SOM-MQE and SFCM. Background technique [0002] With the gradual depletion of fossil and various mineral resources and the increasing demand for energy, people have attached great importance to the use of renewable energy. Among them, wind energy has the largest installed capacity and has become the renewable energy with the highest proportion. [0003] However, while the installed capacity of wind turbines continues to grow, the reliability of individual wind turbines is not optimistic. On the one hand, frequent failures of wind turbines reduce the utilization rate of wind energy, and the low reliability leads to high operation and maintenance costs of wind farms, which greatly increases the cost of operation and maintenance; on the ot...

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Problems solved by technology

[0003] However, while the installed capacity of wind turbines continues to grow, the reliability of individual wind turbines is not optimistic.

On the one hand, frequent failures of wind turbines reduce the utilization rate of wind energy, and the low reliability leads to high operation and maintenance costs of wind farms, which greatly increases the cost of operation and maintenance; on the other hand, wind turbines are usually located in remote areas such as mountainous areas. In some places, offshore wind farms are also located in offshore and near-sea areas. The working environment is harsh, and the nacelle is generally installed at a height of tens of meters or even hundreds of meters above the ground. difficulty

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