Wind driven generator bearing fault diagnosis method and system based on VaDE

A technology for wind turbines and fault diagnosis models, applied in the field of bearing faults, can solve problems such as low accuracy of diagnosis methods, and achieve the effect of improving accuracy

Pending Publication Date: 2022-03-01
HUANENG HUAJIALING WIND POWER CO LTD +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present application provides a VaDE-based wind turbine bearing fault diagnosis method and system to at least solve the technical problem of low accuracy of the diagnostic method for wind turbine bearing faults in the related art

Method used

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  • Wind driven generator bearing fault diagnosis method and system based on VaDE
  • Wind driven generator bearing fault diagnosis method and system based on VaDE
  • Wind driven generator bearing fault diagnosis method and system based on VaDE

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Effect test

Embodiment 1

[0023] figure 1 A flow chart of a VaDE-based wind turbine bearing fault diagnosis method provided by an embodiment of the present disclosure, as shown in figure 1 As shown, the method includes:

[0024] Step 1: Obtain the status data of the wind turbine bearings at each moment within the forecast period.

[0025] It should be noted that the status data of the wind turbine bearings include:

[0026] The temperature difference between the driving end and the non-driving end of the wind turbine, the output power of the wind turbine, the speed of the wind turbine, the second-level eigenvalue of the wind turbine bearing vibration velocity, and the second-level eigenvalue of the bearing vibration acceleration;

[0027] Wherein, the second-level characteristic value of the bearing vibration speed includes: the effective value, maximum value, minimum value, and mean value of the bearing vibration speed;

[0028] The second-level eigenvalues ​​of bearing vibration acceleration inclu...

Embodiment 2

[0067] image 3 A structural diagram of a VaDE-based wind turbine bearing fault diagnosis system provided by an embodiment of the present disclosure, as shown in image 3 As shown, the system includes:

[0068] The first acquisition module is used to acquire the state data of the wind turbine bearing at each moment within the forecast period;

[0069] The second acquisition module is used to input the status data of the wind turbine bearings at each moment within the prediction period into the pre-established wind turbine bearing fault diagnosis model, and obtain the Gaussian distribution corresponding to the wind turbine bearings within the prediction period the weight of;

[0070] The diagnosis module is configured to diagnose whether there is a fault in the wind turbine bearing within the prediction period based on the weight of the Gaussian distribution corresponding to the wind turbine bearing within the prediction period.

[0071] In an embodiment of the present discl...

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Abstract

The invention relates to a VaDE-based wind driven generator bearing fault diagnosis method and system. The method comprises the steps of obtaining state data of a wind driven generator bearing at each moment in a prediction time period; inputting the state data of the wind driven generator bearing at each moment in the prediction time period into a pre-established wind driven generator bearing fault diagnosis model, and obtaining the weight of Gaussian distribution corresponding to the wind driven generator bearing in the prediction time period; and based on the weight of the Gaussian distribution corresponding to the wind driven generator bearing in the prediction time period, diagnosing whether the wind driven generator bearing has a fault in the prediction time period. According to the technical scheme, whether the bearing breaks down or not is diagnosed through the wind driven generator bearing fault diagnosis model, and the accuracy of wind driven generator bearing fault diagnosis can be improved.

Description

technical field [0001] The invention relates to the field of bearing faults, in particular to a VaDE-based method and system for wind turbine bearing fault diagnosis. Background technique [0002] At present, wind turbine bearing faults are a common phenomenon in the wind power industry. The existing bearing fault monitoring system can only monitor the vibration, temperature and other parameters of the bearing. The analysis and judgment of the monitoring data still requires human judgment by experienced technicians. Therefore, the existing bearing fault diagnosis system is of little significance for generator bearing fault prediction and real-time diagnosis, and still provides raw data for generator bearing parameter monitoring and non-fault reason analysis. [0003] This shows that above-mentioned existing wind-driven generator bearing fault diagnosis obviously still has inconvenience and defect, needs to be further improved urgently. How to create a convenient and accurat...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06F17/18G06N3/04G06N3/08G01M13/045
CPCG06F17/18G06N3/08G01M13/045G06N3/045G06F18/2414
Inventor 万芳王振荣曹硕唐云曾谁飞王青天卢泽华赵鹏程杜静宇王华王恩民童彤李小翔任鑫
Owner HUANENG HUAJIALING WIND POWER CO LTD
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