Method for evaluating remaining life of EPR (ethylene-propylene rubber) nuclear power cable and method for predicting remaining life of EPR nuclear power cable

A nuclear energy and life-span technology, applied in neural learning methods, measuring devices, instruments, etc., can solve problems such as cable failure, insulation failure, and cable insulation breakdown, and achieve accurate prediction results.

Inactive Publication Date: 2018-05-18
CHANGCHUN INST OF APPLIED CHEMISTRY - CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the current evaluation methods are all specific diagnostic methods for certain aging characteristics of cable insulation materials. The measured characteristic values ​​or characteristic curves in the analysis and detection methods are limited by a certain threshold value. If the threshold value is exceeded, the cable is deemed to be fail
However, in the actual measurement process, it often appears that the cable that reaches the threshold still has good insulation performance, or the insulation material of the cable that does not reach the threshold has the characteristics of local breakdown or insulation failure.
Therefore, there are certain defects in these diagnostic methods, and it is impossible to accurately and reliably evaluate the aging degree of insulating materials.

Method used

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  • Method for evaluating remaining life of EPR (ethylene-propylene rubber) nuclear power cable and method for predicting remaining life of EPR nuclear power cable
  • Method for evaluating remaining life of EPR (ethylene-propylene rubber) nuclear power cable and method for predicting remaining life of EPR nuclear power cable

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Effect test

Embodiment 1

[0043] A method for evaluating the remaining life of EPR nuclear energy cable insulation materials:

[0044] Measure the sound velocity, sound velocity attenuation, thermal imaging image analysis of EPR nuclear energy cable insulator materials in the energized state, and the relationship between current density (σε) and displacement current density (jωε′), and determine the relationship between sound velocity, sound velocity attenuation, and thermal imaging image analysis , and between the current density (σε) and the displacement current density (jωε′) in what kind of characteristics and values ​​when the EPR insulation material aging failure.

[0045] An artificial neural network model is established, using the above-mentioned EPR cable performance such as sound velocity, sound velocity attenuation, and Tanδ measurement data as input, and the cable service life as output. Through the constructed network model, after a large number of computer independent training, it can be u...

Embodiment 2

[0054] A method for predicting the remaining service life of cables through non-destructive testing of EPR nuclear energy cable insulation materials through a high-temperature oven:

[0055] An artificial neural network model is established, using EPR cable performance such as sound velocity, sound velocity attenuation, and Tanδ measurement data as input, and cable service life as output. The network model constructed through a large number of computer independent training can be used for different sound velocity and sound velocity attenuation. , Tanδ measurement data and other EPR cable performance to predict the cable service life when the performance reaches a certain value, the specific steps include:

[0056] Establish a database of sound velocity (X1), sound velocity attenuation (X2), and Tanδ (X3);

[0057] Create an artificial neural network model through Matlab and other software, use the speed of sound (X1), sound velocity attenuation (X2), and Tanδ (X3) as the netwo...

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Abstract

The invention relates to a method for predicting remaining life of an EPR (ethylene-propylene rubber) nuclear power cable by applying dielectric frequency spectra and ultrasonic measurement nondestructive testing methods and establishing an ANN (artificial neural network) model. The method comprises the following steps: firstly, detecting key chemical, physical and electrical parameters closely related to aging by an accelerated thermal aging test in a laboratory; further analyzing the relationship of dielectric spectrum and ultrasonic measurement curves with physical properties, chemical properties and other electrical parameters; finding a dielectric spectrum and ultrasonic measurement range of an insulation material sensitive to aging, and designing an in-situ monitoring system; then, deducing single-factor and multi-factor aging state equations with a mathematical analysis method, and establishing a relationship model among aging factors, time, detection indexes and remaining service life by an artificial neural network; finally, realizing evaluation of the remaining service life of the cables by ultrasonic and dielectric spectrum nondestructive online detection in combinationwith the ANN model.

Description

technical field [0001] The invention relates to the field of cable aging evaluation and monitoring, to the field of artificial neural network prediction application, and in particular to a method for predicting the remaining service life of cables based on non-destructive testing and artificial neural network models. Background technique [0002] Nuclear safety is an important prerequisite for the development of nuclear energy. In the 21st century, more and more nuclear power plants in the world have been operating for more than 30 years, and the aging and life management of nuclear power plants have attracted widespread attention. Research in this area is still in its infancy in our country. According to the understanding of the IAEA and the United States and other countries and organizations that carried out aging research earlier, the aging management of nuclear power plants should start at the design stage of the power plant. The safe service life of cables is not clea...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N17/00G06N3/04G06N3/08
CPCG01N17/00G06N3/04G06N3/08
Inventor 崔磊何浪冉祥海
Owner CHANGCHUN INST OF APPLIED CHEMISTRY - CHINESE ACAD OF SCI
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