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Water guide shoe temperature trend early warning method, device and system based on machine learning

A machine learning and early warning device technology, applied in neural learning methods, information technology support systems, instruments, etc., can solve problems such as the inability to quickly locate and deal with faults in actual engineering needs, improve operational reliability, and avoid serious problems. glitch effect

Active Publication Date: 2021-01-05
NR ELECTRIC CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional early warning of water guide tile temperature of hydropower units often adopts the method of fixed limit value, which can no longer meet the actual engineering needs of current hydropower plants for rapid fault location and timely processing

Method used

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  • Water guide shoe temperature trend early warning method, device and system based on machine learning
  • Water guide shoe temperature trend early warning method, device and system based on machine learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0039] An embodiment of the present invention provides a machine learning-based water conduction tile temperature trend warning method, such as figure 1 As shown, it specifically includes the following steps:

[0040] Obtaining a water conduction tile temperature prediction model, the water conduction tile temperature prediction model is obtained based on machine learning training, including the water conduction tile temperature sum and input factors, and the relationship between the two;

[0041] Publishing the water conduction tile temperature prediction model as a temperature prediction service;

[0042] The temperature prediction service calculates the predicted temperature in response to the temperature prediction request sent by the early warning application module and the real-time sampling value of the input factor, and sends the predicted temperature to the early warning application module, so that the early warning application module According to the alarm rules, th...

Embodiment 2

[0062] Based on the same inventive concept as that of Embodiment 1, an embodiment of the present invention provides a water conduction tile temperature trend warning device based on machine learning, including:

[0063] The acquisition module is used to obtain the water conduction tile temperature prediction model, the water conduction tile temperature prediction model is obtained based on machine learning training, including the water conduction tile temperature sum and input factors, and the relationship between the two;

[0064] A publishing module, configured to publish the water conduction tile temperature prediction model as a temperature prediction service;

[0065] The early warning module is used for the temperature prediction service to calculate the predicted temperature in response to the temperature prediction request sent by the early warning application module and the real-time sampling value of the input factor, and send the predicted temperature to the early wa...

Embodiment 3

[0074] An embodiment of the present invention provides a water conduction tile temperature trend early warning system based on machine learning, including a storage medium and a processor;

[0075] The storage medium is used to store instructions;

[0076] The processor is configured to operate according to the instructions to execute the steps of the method according to any one of Embodiment 1.

[0077] Those skilled in the art should understand that the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable progr...

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Abstract

The invention discloses a water guide shoe temperature trend early warning method, device and system based on machine learning. The method comprises steps of obtaining a water guide shoe temperature prediction model which is obtained based on machine learning training and comprises the water guide shoe temperature sum, an input factor and the relation between the water guide shoe temperature sum and the input factor; publishing the water guide shoe temperature prediction model as a temperature prediction service; wherein the temperature prediction service responds to a temperature prediction request sent by the early warning application module and a real-time sampling value of an input factor, calculates a prediction temperature, and sends the prediction temperature to the early warning application module, so the early warning application module compares the prediction temperature with an actual sampling temperature according to a predefined warning rule, and sends the actual samplingtemperature to the early warning application module; and determining whether to issue an alarm. The method can scientifically and effectively predict the temperature of the water guide shoe of the hydroelectric generating set, gives out related early warning in advance, avoids severe faults of the hydroelectric generating set, and greatly improves operation reliability of the hydroelectric generating set.

Description

technical field [0001] The invention belongs to the field of hydropower, and in particular relates to a machine learning-based method, device and system for early warning of the temperature trend of a water guide tile of a hydroelectric unit. Background technique [0002] With the continuous development of my country's industry, hydropower resources as a clean energy have received more and more attention. At present, hydropower has successfully become an important part of my country's power generation. The hydroelectric unit equipment, which plays a key role in the process of hydroelectric power generation, is also constantly developing in the direction of large capacity and high load. During the operation of hydropower units, some faults often lead to abnormal shutdown of the units, which has a certain impact on the stability and reliability of the regional power grid. [0003] According to relevant investigation and statistics, a large part of the reasons for the abnorma...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06F30/27G06N3/04G06N3/08G06Q50/06G08B31/00
CPCG06Q10/04G06F30/27G06N3/084G06Q50/06G08B31/00G06N3/045Y04S10/50
Inventor 刘云久徐丹孙超王言国顾全陈州常夏勤
Owner NR ELECTRIC CO LTD
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