Wind turbine generator main shaft bearing fault prediction method

A main shaft bearing and fault prediction technology, applied in the direction of mechanical bearing testing, computer parts, instruments, etc., can solve problems such as easy to cause false alarms, insufficient pertinence, and inability to locate faults to specific components, achieving short time-consuming, classification The effect of high accuracy and improved accuracy

Inactive Publication Date: 2020-01-10
GUANGDONG MINGYANG WIND POWER IND GRP CO LTD
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Problems solved by technology

[0005] At present, there have been many studies on early warning of wind turbines, many of which combine wind speed based power anomaly methods to early warning; on the one hand, this type of method is not pert

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  • Wind turbine generator main shaft bearing fault prediction method
  • Wind turbine generator main shaft bearing fault prediction method
  • Wind turbine generator main shaft bearing fault prediction method

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[0045] The present invention will be further described below in conjunction with specific embodiments.

[0046] The method for predicting the fault of the main shaft bearing of the wind turbine provided in this embodiment is based on the historical fault maintenance data of the main shaft bearing of the fan, combined with statistics and machine learning methods, using multiple monitoring indicators of the fan as input variables, and the state of the main shaft bearing as the predicted output Variables, and statistically analyze the predicted values ​​of output variables, and set thresholds for fault prediction; it includes the following steps:

[0047] 1) Data exploration: select the data of the week before the spindle bearing wear failure of the wind turbine, do quality analysis and characteristic analysis of all monitoring indicators, view the data quality and data distribution, etc., refer to the attachment Figure 1a , 1b , 1c and 1d show the data distribution of some monitoring ...

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Abstract

The invention discloses a wind turbine generator main shaft bearing fault prediction method. According to the method, based on historical fault maintenance data of a main shaft bearing of a draught fan, statistics and a machine learning method are combined, multiple monitoring indexes of the draught fan serve as input variables, the state of the main shaft bearing serves as a prediction output variable, statistical analysis is conducted on a prediction value of the output variable, and a threshold value is set for fault prediction. The method has high accuracy and stability, and can predict the fault of the main shaft bearing one week in advance and discover early abnormality as soon as possible.

Description

Technical field [0001] The invention relates to the technical field of wind power generation, in particular to a method for predicting the failure of a main shaft bearing of a wind turbine. Background technique [0002] With the continuous development of wind power technology, large-megawatt and low-speed wind turbines have emerged in recent years, and substantial progress has been made in the development and commissioning of offshore large-megawatt compact units. [0003] The main shaft bearing is a key component of the drive system of a wind turbine. Due to the influence of random natural wind, it bears a huge random impact force, resulting in many types of failures. Once the main shaft bearing fails, if it is not maintained in time, it will force the unit to shut down to replace expensive components, or damage the entire unit and cause huge losses. [0004] At this stage, the wind farm is mainly performing routine maintenance, and the status assessment and fault diagnosis of the ...

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Application Information

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IPC IPC(8): G06K9/62G01M13/04
CPCG01M13/04G06F18/2148G06F18/24
Inventor 凌永志孙启涛银磊
Owner GUANGDONG MINGYANG WIND POWER IND GRP CO LTD
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