Wind turbine generator main gear fault diagnosis method of multi-feature multilevel comprehensive judgment

A wind turbine and fault diagnosis technology, which is applied in the testing of machine gears/transmission mechanisms, etc., can solve problems such as heavy economic losses and long maintenance work time, and achieve strong fault tolerance, scalability, and simple diagnostic methods.

Active Publication Date: 2013-04-10
XI AN JIAOTONG UNIV
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Problems solved by technology

Due to the fixed and delayed maintenance methods and insufficient preparation in

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  • Wind turbine generator main gear fault diagnosis method of multi-feature multilevel comprehensive judgment
  • Wind turbine generator main gear fault diagnosis method of multi-feature multilevel comprehensive judgment
  • Wind turbine generator main gear fault diagnosis method of multi-feature multilevel comprehensive judgment

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Embodiment Construction

[0035] The method provided by the present invention collects the historical operation data of the wind turbine gearbox, performs digital signal processing on the data to extract characteristic information, and makes a fault diagnosis sample library. Then carry out two-level evaluation design, use the AHP to calculate the weight vector, and adjust it according to the sample diagnosis results to obtain the weight vector that meets the accuracy requirements. These information constitute the wind turbine gearbox fault diagnosis model. In the application, the latest operating vibration data of the wind turbine gearbox is read online in real time, and these data are input into the fault diagnosis model of the wind turbine. The failure probability of each component of the gearbox can be used to determine the operating status and fault conditions of each component of the gearbox, and realize online real-time monitoring and fault diagnosis analysis of the gearbox status. The present in...

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Abstract

The invention discloses a wind turbine generator main gear fault diagnosis method of multi-feature multilevel comprehensive judgment. As to a wind turbine generator to be tested, a sensor and characteristic value two-stage evaluation model can be obtained by one time collection of historical data. When the wind turbine generator runs, real-time running data of a gear box can be collected. As to a fault of a component, a corresponding digital signal processing algorithm can be called to process the collected data. Typical characteristic value is obtained from the collected data and used as input parameters of the sensor and characteristic value two-stage evaluation model. Vector quantity of the final judgment result of the model is the fault rate of the component. The probability of failure of components of the whole generator can be obtained by loop execution of the procedure. The wind turbine generator main gear fault diagnosis method of the multi-feature multilevel comprehensive judgment is capable of monitoring real-time online status and diagnosing faults of different kinds of wind turbine generator gear boxes, simple, fast and stable in diagnosing method and strong in fault tolerance.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis methods, and relates to a multi-feature and multi-stage comprehensive evaluation method for fault diagnosis of a main transmission device of a wind turbine. Background technique [0002] The cost of wind turbines is generally high, so once a unit fails, its maintenance costs and economic losses during shutdown maintenance are often high. In order to avoid huge economic losses caused by major faults, real-time monitoring and timely maintenance of the unit must be carried out. At present, wind turbines generally adopt the method of planned maintenance and after-event maintenance. Planned maintenance is routine maintenance after the unit has been running for 2500h and 5000h, and after-the-fact maintenance is the operation of repairing or replacing parts after the unit has an obvious failure or even shut down. Due to the fixed and delayed maintenance methods, and insufficient preparation in ...

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Application Information

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IPC IPC(8): G01M13/02
Inventor 杨清宇庄健孙凤伟苏周
Owner XI AN JIAOTONG UNIV
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