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Wind driven generator set failure feature extracting method based on sparse decomposition

A wind turbine, sparse decomposition technology, applied in the direction of machine gear/transmission mechanism testing, etc., can solve the problems of cross-effect of fault features, large background noise, and difficult to extract fault features, etc., achieve simple calculation, improve economic and social benefits , Facilitate the effect of engineering practical application

Active Publication Date: 2015-05-27
XI AN JIAOTONG UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to solve the above-mentioned problems in the prior art, and provide a method for extracting fault features of wind power generators based on sparse decomposition. It is difficult to extract fault features due to reasons such as multi-feature coupling and large background noise

Method used

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  • Wind driven generator set failure feature extracting method based on sparse decomposition
  • Wind driven generator set failure feature extracting method based on sparse decomposition
  • Wind driven generator set failure feature extracting method based on sparse decomposition

Examples

Experimental program
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Embodiment

[0051] The vibration acceleration signal in the vertical direction of the output shaft of the parallel shaft gearbox is collected from a wind turbine drive chain fault diagnosis test bench. The gear at the high-speed end of the parallel shaft gearbox has 23 teeth, and the large gear on the intermediate shaft meshing with it is a faulty gear with prefabricated pitting on the teeth. The gear has 83 teeth and the meshing transmission ratio is 1:3.61.

[0052] After obtaining the vibration signal a(t), proceed as follows:

[0053] 1. For the tested vibration signal, according to the different morphological components of the signal, the harmonic component, impact component and margin are extracted through iterative sparse decomposition and reconstruction of the signal; this case adopts the Morphological Component Analysis (MCA) method ) combined with Stagewise Orthogonal Matching Pursuit (StOMP), and the use of discrete cosine transform (DCT) dictionary to extract harmonics, discre...

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Abstract

The invention discloses a wind driven generator set failure feature extracting method based on sparse decomposition. The method is used for diagnosing wind driven generator set failures and is suitable for being used for non-direct-drive-type wind driven generator sets. The method is aimed to solve the problem that failure features of a wind driven generator set vibration signal are difficult to extract due to failure feature coupling, large background noise and the like, and on the basis of a form composition analysis principle, the signal is decomposed into three compositions including harmonic waves, impact and noise by means of different sparse expression dictionaries, so that the failure features which are difficult to find outstand; experiments are carried out on a wind driven generator failure simulation experiment table, and validness is proved. The method has the advantages that the failure features which are covered by noise or other feature signals and difficult to find are extracted, accordingly a failure portion is determined, instructive suggestions are made for maintenance of a wind driven generator set and arrangement adjustment of maintenance plans, non-scheduled down time is effectively reduced and economical efficiency and social efficiency of a wind power plant are improved.

Description

technical field [0001] The invention belongs to the field of fault diagnosis of a transmission chain of a wind power generating set, and in particular relates to a method for extracting fault features of a wind power generating set based on sparse decomposition. Background technique [0002] my country's wind power generation is developing rapidly. In 2012, my country's new installed capacity reached 13,200MW, and the cumulative installed capacity reached 75,564MW, continuing to lead the world. Due to the special structure and operation mode, wind turbines are not only subject to random aerodynamic loads, inertial forces, loads caused by different operating states and other external environments superimposed on the operating state, but also internally integrate mechanical, electronic, electrical, and hydraulic systems. Integrated complex electromechanical system. The operating environment is harsh, the cabin is high off the ground, the degree of automation is high, the stru...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M13/02
Inventor 陈雪峰方作为杜朝辉张晗
Owner XI AN JIAOTONG UNIV
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