Reactor internal reliability analysis system and method based on data mining

A data mining and analysis system technology, applied in data mining, neural learning methods, electrical digital data processing, etc., can solve the problem of unpredictable failure and its risk probability, reactor internal components that do not meet the needs of engineering, and insufficient consideration To solve such problems, achieve high recognition accuracy and generalization ability, improve economy, and achieve low prediction error

Pending Publication Date: 2021-02-19
ZHEJIANG UNIV CITY COLLEGE
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Recently, the design of reactor internals mostly relies on the method of determinism, which often leads to overly conservative design in some aspects, and the existing theories in other aspects have not been fully considered, and it is impossible to predict its complex operating conditions. The possible failures and their risk probabilities, resulting in the internal components of the reactor still not meeting the needs of actual engineering

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Reactor internal reliability analysis system and method based on data mining
  • Reactor internal reliability analysis system and method based on data mining
  • Reactor internal reliability analysis system and method based on data mining

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] The present invention will be more fully described with reference to the accompanying drawings, in which some, but not all embodiments of the invention are shown. Indeed, the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather as embodiments of the invention as applicable to the disclosure of the invention. provided by lawful request. The content of the present invention will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0043] figure 1 The functions of each module and the logical relationship among the modules of the data mining-based reliability analysis system for reactor internals are listed.

[0044] The data preprocessing module performs abnormal value processing, null value processing, discretization processing and normalization processing on the data collected by the internal components of the reactor, making ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a reactor internal reliability analysis system and method based on data mining, and the method comprises the steps: building evaluation indexes in a modeling process through supervised learning, so as to measure the advantages and disadvantages of a model, and obtaining two types of modeling indexes for evaluating the reliability of a reactor internal; based on the determined indexes for evaluating the health state of the reactor internals, conducting dimension reduction processing on the collected data, and constructing service features for reliability evaluation; reconstructing a current sample into a sample set with time sequence based on the time sequence characteristic of the reactor internal operation state data, and establishing a model framework through a long-short-term memory recurrent neural network prediction method. The model training process is based on the prediction purpose, a cross entropy loss function and an Adam optimizer are selected, algorithm model parameters are searched, and the reliability of reactor internals is predicted. The method has high recognition precision and generalization ability, is good in performance, and is suitablefor health state recognition and reliability judgment of reactor internals.

Description

technical field [0001] The invention relates to state identification and fault diagnosis of reactor internal components, in particular to a data mining-based reliability analysis system and method for reactor internal components. Background technique [0002] The safety of the PWR nuclear power plant mainly depends on the safety of the primary circuit. According to nuclear safety regulations, all mechanical equipment and pipelines in the primary circuit belong to nuclear safety level 1 and earthquake resistance category 1. One of the main equipment of the primary circuit is the reactor pressure vessel. The components in the container are called internal components. The internal components of the reactor mainly include the lower support components of the core, the upper support components of the core, and the in-core measurement devices, etc. When the reactor is in operation, each component in the reactor is in a harsh environment such as high temperature, high pressure, c...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06F16/215G06F16/2458G06N3/04G06N3/08G06F119/02
CPCG06F30/27G06F16/215G06F16/2465G06N3/08G06F2119/02G06F2216/03G06N3/044G06N3/045
Inventor 万安平陈挺颜孙挺王文晖杨洁常庆
Owner ZHEJIANG UNIV CITY COLLEGE
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products