Method for soft measurement of nuclear power station reactor core temperature fields on basis of neutral network surface fitting

A neural network and surface fitting technology, applied in the field of thermal measurement, can solve problems such as difficulty in obtaining the temperature distribution inside the furnace or reactor, difficulty in measuring temperature, and inability to guarantee the real-time performance of the algorithm, so as to avoid local minimum problems, The effect of strong memory ability and accelerated learning speed

Inactive Publication Date: 2017-05-24
SOUTHEAST UNIV
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Problems solved by technology

However, due to the high temperature and high pressure environment during the operation of reactors and the structural characteristics of these devices, it is difficult to measure the temperature inside them.
Although the current measurement technology is developing rapidly and can measure the temperature of certain points, it is difficult to obtain the internal temperature distribution of the entire furnace or reactor. Therefore, we need to reconstruct the temperature field
[0004] Although a lot of work has been done on reactor core temperature measurement methods and temperature field reconstruction at home and abroad, certain results have been achieved: domestic scholars have proposed a reconstruction algorithm based on the algebraic reconstruction method (ART), which uses a small number of data to simulate and reconstruct typical temperature The field model has achieved good results, but the solution of this method requires multiple iterations, and the real-time performance of the algorithm cannot be guaranteed

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  • Method for soft measurement of nuclear power station reactor core temperature fields on basis of neutral network surface fitting
  • Method for soft measurement of nuclear power station reactor core temperature fields on basis of neutral network surface fitting
  • Method for soft measurement of nuclear power station reactor core temperature fields on basis of neutral network surface fitting

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Embodiment Construction

[0036] The present invention will be further explained below in conjunction with the accompanying drawings and specific embodiments.

[0037] The main process of this patent implementation scheme is specifically as follows (see figure 1 ):

[0038] (1) The method of radial basis function neural network surface fitting that adopts is carried out the concrete realization that n measuring point temperature is calculated and processed as follows (see Image 6 ):

[0039] The output of the kth node in the hidden layer of the RBF neural network can be expressed as r k =R(‖X i -T k ‖); the output of the jth node in the output layer can be expressed as RBF radial basis function R(·) is a Gaussian function (wherein, c is the center of the Gaussian function, and σ is the variance of the Gaussian function), then the output of the RBF neural network, that is, the fitted outlet temperature is:

[0040]

[0041] where x p is the sensor temperature measuring point data as the p...

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Abstract

The invention discloses a method for soft measurement of nuclear power station reactor core temperature fields on the basis of neutral network surface fitting. The method comprises the following steps of: establishing a reactor core temperature calculation model through researching a reactor core channel model, a reactor core segment division and power distribution model, a reactor core coolant flow distribution model and a reactor core heat conduction and transmission model; carrying out preliminary reconstruction on a two-dimensional temperature field at the section of a pressurized water reactor core coolant outlet by utilizing a radial basis function (RBF) neutral network surface fitting method on the basis of discrete temperature data of the coolant outlet; calculating the flow of each coolant channel by utilizing a heat transfer formula; and finally substituting the calculated outlet temperature and channel flows into a reactor core temperature calculation model to realize the soft measurement of three-dimensional temperature distribution of a reactor core coolant and a reactor core fuel assembly. According to the method disclosed by the invention, safety guidance can be provided for reactor core design, a coolant temperature distribution law can be analyzed by utilizing a calculation model, and reference can be provided for reactor core structure design parameters.

Description

technical field [0001] The invention belongs to the technical field of thermal measurement, in particular to a soft measurement method for nuclear power plant core temperature field based on neural network surface fitting. Background technique [0002] In recent years, non-fossil energy has gradually replaced the role of fossil energy by virtue of its clean and renewable advantages, which is also the trend of future energy development. Relying on its environmental and economic advantages, nuclear energy has gradually become a clean energy recognized by the energy industry. my country's nuclear power development has a history of nearly 40 years. In the long run, nuclear power is an indispensable part of gradually reducing environmental pollution and improving my country's energy structure. [0003] The continuous development of nuclear energy also makes people have higher and higher requirements for effective control and safety control of nuclear power plants. As a basic an...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/10
CPCG06F30/20G06N3/10
Inventor 朱小良景亚杰陆彬羊冰清姜懿纯沈维
Owner SOUTHEAST UNIV
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