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A method and system for predicting fan faults

A technology for failure prediction and wind turbines, applied in prediction, computer components, biological neural network models, etc., can solve problems such as low prediction accuracy, large individual differences between fans, and high prediction costs, so as to improve accuracy and efficiency , The effect of reducing the cost of hardware and software

Active Publication Date: 2020-06-09
ZHEJIANG SHANGFENG SPECIAL BLOWER IND CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

That is to say, the individual differences among wind turbines are large. If a large number of wind turbines are predicted by the same fault prediction method, there will be problems such as large prediction costs and low prediction accuracy.

Method used

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  • A method and system for predicting fan faults
  • A method and system for predicting fan faults
  • A method and system for predicting fan faults

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0051] Such as figure 1 As shown, this embodiment proposes a fan failure prediction method, including:

[0052] S1. Collect the basic information of the wind turbine to be predicted, including the service life and the length of use;

[0053] For the fan to be predicted, the present invention first collects the basic information of the fan to be predicted. Basic information includes, but is not limited to, the age of use and the length of time it has been used. The service life is related to the specific model of the fan and can be obtained by obtaining the official data corresponding to the model. The used time is obtained through statistical collection of fan operation data.

[0054] S2. Screen the wind turbines to be predicted based on the basic information, and screen out the wind turbine composition prediction wind turbine set that needs to be fault predicted;

[0055] Fans are widely used in ventilation, dust removal and cooling of factories, mines, tunnels, cooling ...

Embodiment 2

[0084] Such as figure 2 As shown, this embodiment proposes a fan failure prediction system, including:

[0085] The basic information collection module is used to collect the basic information of the wind turbine to be predicted, including the service life and the used time;

[0086] For the fan to be predicted, the present invention first collects the basic information of the fan to be predicted. Basic information includes, but is not limited to, the age of use and the length of time it has been used. The service life is related to the specific model of the fan and can be obtained by obtaining the official data corresponding to the model. The used time is obtained through statistical collection of fan operation data.

[0087] The screening module is used to screen the wind turbines to be predicted based on the basic information, and screen out the wind turbines that need to be fault predicted to form a forecasted wind turbine set;

[0088] Fans are widely used in ventila...

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Abstract

The invention discloses a wind turbine failure prediction method and system, wherein the method includes: collecting basic information of wind turbines to be predicted; screening out a set of predicted wind turbines based on the basic information; Fault prediction based on the prediction cycle corresponding to the fault prediction level; based on the environmental conditions, the fans in the predicted fan concentration are divided into predicted fan subsets; the standard time domain signal under the fan fault state is constructed; the time domain signal prediction model under the corresponding environmental conditions is constructed ; Based on the time-domain signal prediction model, predict the time-domain signal for the fan; divide the predicted time-domain signal of the fan into multiple time-domain sub-signals, calculate the correlation coefficient between the time-domain sub-signal and the standard time-domain signal, and predict whether the fan will fail and failure time. The invention realizes fault prediction for a large number of wind turbines, independently predicts based on different environmental conditions, has low processing cost, high efficiency and high prediction accuracy.

Description

technical field [0001] The invention relates to the field of fault prediction, in particular to a fan fault prediction method and system. Background technique [0002] As the running time increases, the dust in the fan will adhere to the impeller unevenly, gradually destroying the dynamic balance of the fan, and gradually increasing the vibration of the bearing. Once the vibration reaches the maximum value allowed by the fan, the fan must be shut down for repair. The annual loss of power generation due to wind turbine failure and the maintenance costs caused by the failure have brought huge economic losses to wind farms. [0003] Fans usually operate under natural conditions such as the field, and the cost of maintenance is relatively high. Therefore, predicting the failure of wind turbines in advance can effectively know the possible failures of wind turbines in advance, so that measures can be taken to avoid the occurrence of failures [0004] The invention patent applic...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/04G06K9/62G06K9/00G06Q10/04
CPCG06Q10/04G06N3/045G06F2218/00G06F18/24
Inventor 陈月娟郑涛冯雪飞汪狄帅
Owner ZHEJIANG SHANGFENG SPECIAL BLOWER IND CO LTD
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