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A pca-knn based converter fault identification method for wind power generation system

A technology for wind power generation system and fault identification, applied in the direction of measuring electrical variables, instruments, measuring electricity, etc., can solve problems such as converter fault identification, improve accuracy and efficiency, reduce redundancy, and reduce classification time Effect

Active Publication Date: 2022-02-11
南京瓦亮科技有限责任公司
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Problems solved by technology

The invention provides a PCA-kNN based wind power generation system converter fault identification method to solve the problem of converter fault identification in the wind power generation system

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  • A pca-knn based converter fault identification method for wind power generation system
  • A pca-knn based converter fault identification method for wind power generation system
  • A pca-knn based converter fault identification method for wind power generation system

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Embodiment Construction

[0057] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0058] The present invention provides a fault identification method for converters of wind power generation systems based on PCA-kNN, which extracts the characteristics of the time domain, frequency domain and time-frequency domain of the DC side DC voltage of the converters of wind power generation systems, and utilizes the dimensionality reduction capability of PCA to analyze these The features are dimensionally reduced, and finally the kNN algorithm is used to classify the samples to be tested. The overall algorithm principle flow process of the present invention is as figure 1 As shown, the specific steps are as follows:

[0059] Step 1: Detect the DC side output voltage signal of the back-to-back three-phase PWM rectifier in the wind power generation system under various open circuit faults;

[0060] The various open-circuit faults of the...

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Abstract

The present invention relates to a method for fault identification of converters in wind power generation systems based on PCA-kNN. First, the DC side output voltage signals of back-to-back three-phase PWM rectifiers in wind power generation systems are collected, and then the time domain, frequency domain and time domain of the voltage signals are extracted. Frequency domain characteristics, and then use the PCA algorithm to reduce the dimensionality of the characteristics of the voltage signal, and finally combine the kNN algorithm to realize the fault identification of the wind power system converter.

Description

technical field [0001] The invention relates to the field of fault identification of converters, and particularly designs a fault identification method for converters of wind power generation systems based on PCA-kNN. Background technique [0002] As a renewable energy source, wind power is an important force in the world's energy supply. With the continuous development of economy and science and technology, wind power generation has been greatly developed in our country. However, the randomness of the wind makes the working state of the wind turbine unstable, which leads to frequent failures of the components of the wind power generation system. Double pulse width modulation ( The pulse width modulation (PWM) converter is used as the interface between the power generation system and the power grid. It needs to control the voltage stability and cooperate to achieve the maximum utilization of wind energy. It is also one of the most prone to failure components. When the conver...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/00G06N20/00
CPCG01R31/00G06N20/00
Inventor 卢军锋姜劲邹政耀
Owner 南京瓦亮科技有限责任公司