Fan blade icing fault detection method and system based on AWKELM

A technology for wind turbine blades and fault detection, applied in wind turbines, engines, wind power generation, etc., can solve problems such as high computational overhead and low fault detection accuracy, achieve low computational overhead, adapt to data imbalance characteristics, and improve fault detection. The effect of precision

Active Publication Date: 2021-08-31
YUNNAN UNIV
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Problems solved by technology

[0006] The purpose of the present invention is to provide a fan blade icing fault detection method and system based on AWKELM to solve the problems of low fault detection accuracy and large calculation overhead in the existing fan blade icing fault detection method

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  • Fan blade icing fault detection method and system based on AWKELM
  • Fan blade icing fault detection method and system based on AWKELM
  • Fan blade icing fault detection method and system based on AWKELM

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[0079] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0080] The purpose of the present invention is to provide an AWKELM-based fan blade icing fault detection method and system, which can improve fault detection accuracy and reduce calculation overhead.

[0081] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0082] fi...

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Abstract

The invention relates to a fan blade icing fault detection method and system based on AWKELM. The method comprises: respectively acquiring SCADA data when the wind generating set operates in a normal state and a blade icing fault state, preprocessing the data, and storing the processed data into an offline training database; obtaining a sample number, and calculating an initial fixed weighting matrix of all samples based on the sample number; respectively establishing a normal state SVDD hyper-sphere model and a fault state SVDD hyper-sphere model which describe sample distribution information, and calculating a self-adaptive weighting matrix which considers all sample distribution information; establishing a fan blade icing fault detection model based on AWKELM in combination with the initial fixed weighting matrix and the adaptive weighting matrix; and inputting the SCADA data of the wind generating set to be detected into the fan blade icing fault detection model based on the AWKELM to detect fan blades, determining a detection result, and performing operation and maintenance decision making according to the detection result. The fault detection precision can be improved, and the calculation overhead can be reduced.

Description

technical field [0001] The invention relates to the field of state monitoring and health maintenance of new energy power generation equipment, in particular to a method and system for detecting icing faults of fan blades based on an Adaptive weighted kernel extreme learning machine (AWKELM). Background technique [0002] In recent years, wind power, as a clean, pollution-free and resource-rich renewable new energy power generation technology, has developed rapidly around the world. As the key equipment in the wind power generation system, the wind turbine blades are prone to icing failures when they are in the harsh environment of low temperature and high humidity for a long time. If the icing fault cannot be detected in time and the deicing system can be started as soon as possible, the operating efficiency of the wind turbine will be affected, and economic losses will be caused. At the same time, icing will increase the load bearing of the blades, which will lead to serio...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): F03D80/40F03D17/00F03D80/00
CPCF03D80/40F03D17/00F03D80/00Y02E10/72
Inventor 李鹏仝瑞宁郎恂高莲曾俊娆付乐天王永雪王昊宇
Owner YUNNAN UNIV
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