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Generator brush slip ring burn fault degree diagnosis method

A technology of brush slip ring and fault degree, which is applied in the field of generator brush slip ring burn fault degree diagnosis, can solve the problems of low precision and low operability, and achieve integrity assurance, strong operability, and avoidance of external interference effect

Inactive Publication Date: 2018-01-05
HOHAI UNIV
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  • Abstract
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Problems solved by technology

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art, to provide a method for diagnosing the degree of burn fault of the generator brush slip ring, and to solve the problem of low accuracy and low operability of the fault diagnosis method for the generator brush slip ring in the prior art. Technical issues with certain limitations

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  • Generator brush slip ring burn fault degree diagnosis method
  • Generator brush slip ring burn fault degree diagnosis method
  • Generator brush slip ring burn fault degree diagnosis method

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Embodiment Construction

[0024] In the present invention, four kinds of failure degrees of surface burns of the generator brush slip ring system are considered, including: normal slip ring surface, mild burn on the faulty phase of the slip ring surface, severe burns on the faulty phase of the slip ring surface, and severe burn on the slip ring surface The fault phase included one mild burn and one severe burn. Based on the simulation software, the different degrees of burn faults of the generator brush slip ring are simulated, and the excitation current flowing through the brush slip ring system is collected as the training sample data, and an adaptive neuro-fuzzy reasoning system is constructed; using a hybrid learning algorithm Train the constructed adaptive neuro-fuzzy reasoning system to determine the input membership function and output membership function parameters in the system; the adaptive neuro-fuzzy reasoning system with determined system parameters can be used to diagnose the burn fault of...

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Abstract

The invention discloses a generator brush slip ring burn fault degree diagnosis method. Different degrees of burn fault happening to the generator brush slip ring are simulated based on simulation software, excitation current correspondingly flowing through a brush slip ring system is acquired as training sample data, and an adaptive neural fuzzy inference system is constructed; a hybrid learningalgorithm is used to train the constructed adaptive neural fuzzy inference system, and parameters of an input membership function and an output membership function in the system are determined; and the adaptive neural fuzzy inference system with the system parameters determined can be used for diagnosing the burn fault of the generator brush slip ring and determining the degree of the burn fault.The diagnosis method provided by the invention is accurate and effective, the accuracy is high, and the operability is strong.

Description

technical field [0001] The invention relates to a method for diagnosing the burn fault degree of a brush slip ring of a generator, which belongs to the technical field of generators. Background technique [0002] Doubly-fed asynchronous induction generator (DFIG) is widely used in wind power generation systems due to its characteristics of sensitive speed adjustment, bi-directional power conversion, and flexible frequency conversion control. As the dynamic and static conversion device of the generator, it is not uncommon for the generator to fail to operate stably due to the failure of the running brush slip ring system. Shutdown after load. At the same time, the daily maintenance workload of the brush slip ring system is heavy, requiring frequent manual inspection and component replacement, especially for wind turbines in harsh environments such as high altitude, low air pressure, and high humidity. The difficulty of maintaining and repairing the large brush slip ring sys...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/34G06N5/04
Inventor 马宏忠李思源徐艳魏海增张艳刘宝稳黄春梅
Owner HOHAI UNIV
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