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Method and system for predicting wind machine state based on Bayesian reasoning mode

A wind turbine and state technology, which is applied in the field of predicting the state of wind turbines based on Bayesian reasoning, can solve problems such as the prediction of difficult wind turbine fault operating states.

Active Publication Date: 2014-08-27
瀛能科技(上海)有限公司 +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] In view of this, the technical problem to be solved by this application is to provide a method and system for predicting the fault state of wind turbines based on Bayesian Inference, so as to solve the problem problem of prediction

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  • Method and system for predicting wind machine state based on Bayesian reasoning mode
  • Method and system for predicting wind machine state based on Bayesian reasoning mode

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Embodiment 1

[0042] Such as figure 1 As shown, it is a method for predicting the fault state of a fan based on Bayesian reasoning described in Embodiment 1 of the present application. The method includes:

[0043] Step 101, obtain the operation data of all the wind turbines to be tested in the wind farm for a certain period of time before the specified time point, classify the operation data according to the preset operation status types of the wind turbines, and Obtain the corresponding operating state type of each wind turbine in each time period according to the same time period within the certain period of time.

[0044] In step 101, the specified time point may be specifically the time when a certain fault actually occurs in the wind turbine and causes shutdown as the time point, or it may be a certain moment in the normal operation of the wind turbine The time point is not limited here. The operation data is specifically the correlation data between the operation parameters of the ...

Embodiment 2

[0052] combine figure 2 As shown, it is a method for predicting the fault state of a fan based on Bayesian reasoning described in Embodiment 2 of the present application. The method includes:

[0053] Step 201, obtain the operation data of the wind turbine to be tested within a certain period of time, divide the operation data into various operation characteristic items according to the preset division conditions, and obtain the wind power in the same period of time within the certain period of time The operating feature items corresponding to each time period of the machine.

[0054] For step 201, obtain the operating data of the wind turbine to be tested within a certain period of time, specifically: the wind speed data of the wind turbine to be tested within a certain period of time and the power generation, blade speed, and pitch angle of the wind turbine to be measured and other operating parameters to perform a correlation test, and obtain the operating data generated ...

Embodiment 3

[0065] The specific application of the method for predicting the fan failure state based on the Bayesian reasoning method will be described in detail below in conjunction with the figure:

[0066] It should be noted that when obtaining the operation data, the more types of correlation tests there are, the more accurate the operation status of the wind turbine reflected will be. Therefore, in this embodiment, the wind turbine to be tested is The data of the three kinds of correlation tests are obtained as operation data: the correlation test between the wind speed data and the power generation, blade speed, and pitch angle of the wind turbine to be tested.

[0067] Step 1, taking the moment when a certain fault of the wind turbine causes shutdown as the designated time point, and obtaining the three kinds of operation data generated by the three kinds of correlation tests 25 days before the designated time point, according to the following table The preset division conditions s...

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Abstract

The invention discloses a method and system for predicting a wind machine state based on a Bayesian reasoning mode. The method comprises the steps that operation data of a wind machine in a certain time are obtained and are classified; the wind machine operation state type of each time period is subjected to probability statistics processing, probability values are generated, and overall operation state types in the time periods are determined; the overall operation state types are subjected to Bayesian network modeling, and the priori condition probability of the overall operation state types is generated; and the priori condition probabilities of the time periods and the probability values of the overall operation state types are subjected to probability processing in a Bayesian reasoning mode, a joint probability value is generated, the state distribution curve of the wind machine is established, and according to the state distribution curve, the wind machine is subjected to fault state prediction. The problem that the fault operation state of a wind power generator cannot be predicted easily is solved.

Description

technical field [0001] The present application relates to the field of state monitoring of wind turbines, and more specifically relates to a method and system for predicting the state of wind turbines based on Bayesian reasoning. Background technique [0002] Driven by natural wind, wind turbines operate and generate electricity. During the operation of wind turbines, they will be affected by external environmental factors and their own working conditions. For example, due to real-time changes in natural wind, sometimes the wind speed is lower than that of wind turbines. The cut-in wind speed makes it difficult for the wind turbine to start; sometimes the wind speed is greater than the limit wind speed that the wind turbine can withstand, causing damage to the wind turbine, causing the wind turbine to fail or even shut down; another example: the wind turbine runs for a long time, cause wind turbines to malfunction. [0003] For the operation failure of the wind turbine, usu...

Claims

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Application Information

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IPC IPC(8): F03D11/00
CPCY02E10/722
Inventor 叶翔
Owner 瀛能科技(上海)有限公司
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