Steam generator water supply system diagnosis method based on multi-source information reinforcement learning

A steam generator, reinforcement learning technology, applied in nuclear power generation, greenhouse gas reduction, power plant safety devices, etc., can solve problems such as increase, system operating conditions, and single data features cannot accurately reflect equipment operating status.

Active Publication Date: 2021-04-20
WUHAN SECOND SHIP DESIGN & RES INST
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, with the extensive application of new technologies, the complexity of the steam generator water supply system has increased significantly, and the uncertain factors involved have also increased. The risks faced by the steam generator water supply system during operation and maintenance and the scale of losses caused by risks also getting bigger
The steam generator water supply system generally contains various equipment such as machinery, hydraulic pressure, electrical appliances, and pipelines. The data obtained from each equipment has differences in information categories, change characteristics, and sampling characteristics, so that a single data feature cannot accurately reflect the operation of the equipment. status; the multi-source heterogeneous data of the steam generator water supply system has the characteristics of incomplete local information, high information redundancy, and low information concentration. There are nonlinear correlations in data features, and equipment features that have not been separated from multi-source information and fused with related information cannot effectively describe the overall state of the system
However, the traditional fault diagnosis method can only reflect the local operating status of the equipment from the partial data level, but cannot provide the health information of large-scale equipment from the system level

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  • Steam generator water supply system diagnosis method based on multi-source information reinforcement learning
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  • Steam generator water supply system diagnosis method based on multi-source information reinforcement learning

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Embodiment Construction

[0041] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0042] Those skilled in the art can easily understand that the above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention, All should be included within the protection scope of the present invention.

[0...

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Abstract

The invention provides a steam generator water supply system fault diagnosis method based on multi-source information reinforcement learning. The method comprises the steps of carrying out the state monitoring of a steam generator, a water supply pump and a water supply valve in a steam generator water supply system, and obtaining a plurality of pieces of state information; clustering the associated state information based on the information source type to form a feature information cluster; establishing a feature matrix based on feature information cluster integration, and extracting a state feature vector from the feature matrix; and inputting the state feature vector into a data analysis model system to diagnose the fault type, and evaluating, regulating and controlling the state parameter of the corresponding component. Aiming at multi-source information fault diagnosis of a steam generator water supply system, technologies of signal processing, mutual information association, nonlinear dimension reduction, deep reinforcement learning and the like are adopted, so that the problems of feature extraction, feature fusion, feature integration, feature learning and the like of multi-source information are solved; and a new technical scheme is provided for autonomous learning and state recognition and diagnosis of multi-source information of the steam generator water supply system.

Description

technical field [0001] The invention relates to the fields of data feature processing and machine learning, in particular to a method and system for diagnosing a water supply system of a steam generator based on multi-source information reinforcement learning. Background technique [0002] The steam generator is the hub of the first and second circuits of the power plant. Its main function is to transfer the heat generated by the reactor of the first circuit to the feed water of the second circuit, so that the feed water of the second circuit becomes steam at a certain temperature and pressure, thereby performing heat exchange and energy transfer. The role of the steam generator water supply system is a system composed of steam turbine, condenser, feed water pump, regulating valve and other components. Steam generator feed water control is an extremely important control function in PWR nuclear power plants. It is used to adjust the water level of the secondary side of the st...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B23/02G21D3/06
CPCY02E30/00
Inventor 冯毅李献领郑伟周宏宽邹海柯志武陶模陈朝旭刘伟林原胜张克龙赵振兴代路
Owner WUHAN SECOND SHIP DESIGN & RES INST
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