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Diagnosis method of steam generator water supply system based on reinforcement learning of multi-source information

A steam generator and reinforcement learning technology, applied in nuclear power generation, greenhouse gas reduction, climate sustainability, etc., can solve problems such as large loss scale, complex information interaction, and inability to provide health information for large-scale equipment from the system level. The effect of improving the degree of intelligence

Active Publication Date: 2022-03-29
WUHAN SECOND SHIP DESIGN & RES INST
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  • Claims
  • Application Information

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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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  • Diagnosis method of steam generator water supply system based on reinforcement learning of multi-source information
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  • Diagnosis method of steam generator water supply system based on reinforcement learning of multi-source information

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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] It is easy for those skilled in the art to 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...

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Abstract

The invention provides a method for fault diagnosis of a steam generator water supply system based on multi-source information reinforcement learning, which includes monitoring the status of the steam generator, feed water pump and feed water valve in the steam generator water supply system, and obtaining multiple status information; The type clusters the associated state information to form a characteristic information cluster; establishes a characteristic matrix based on the integration of the characteristic information cluster, and extracts the state characteristic vector from the characteristic matrix; inputs the state characteristic vector into the data analysis model system to diagnose the fault type, and diagnoses the corresponding component Evaluate and regulate the state parameters of the system. Aiming at the multi-source information fault diagnosis of the steam generator water supply system, the present invention adopts technologies such as signal processing, mutual information correlation, nonlinear dimensionality reduction, deep reinforcement learning, etc., and solves feature extraction, feature fusion, feature integration, and feature learning of multi-source information It provides a new technical solution for the self-learning and state identification and diagnosis of multi-source information of 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 Patents(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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