Surface heat flow identification three-dimensional effect correction method based on neural network

A neural network and three-dimensional effect technology, applied in biological neural network models, neural architectures, special data processing applications, etc., can solve problems such as limited heat flow function forms

Inactive Publication Date: 2019-08-02
ZHEJIANG UNIV
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Cui Miao uses the dimensionless objective equation to identify the parameters

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  • Surface heat flow identification three-dimensional effect correction method based on neural network
  • Surface heat flow identification three-dimensional effect correction method based on neural network
  • Surface heat flow identification three-dimensional effect correction method based on neural network

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[0068] The specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, and the purpose and effect of the present invention will become more obvious.

[0069] A neural network-based three-dimensional effect correction method for surface heat flow identification of the present invention, its core content is to install a number of temperature sensors on the inner wall surface of the area around the stagnation point heat flow, and use the one-dimensional sequential function method to convert the measurement data of each temperature sensor It is transformed into the corresponding heat flow identification sequence, and after the data is normalized, it is used as the input of the BP network, and the denormalized result of the network output is the identification result of the stagnation point heat flow. The neural network correction process of the present invention is detailed in figure 1 .

[0070] This example demo...

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Abstract

The invention discloses a surface heat flow identification three-dimensional effect correction method based on a neural network. The correction method comprises the following steps: mounting a plurality of temperature sensors on the inner wall surface of an area around a stationary point heat flow; utilizing temperature data of each internal temperature measuring point; obtaining a heat flow on acorresponding heating surface point through a one-dimensional heat flow identification method; and then introducing an artificial neural network algorithm, carrying out normalization processing on theidentified heat flow corresponding to each measuring point in the previous step to serve as an input sequence of the neural network, and carrying out training in the neural network to obtain an output anti-normalization result to serve as a heat flow identification value of a region of interest. According to the correction method provided by the invention, the time complexity of three-dimensionalidentification is avoided, meanwhile, the good noise resistance of the sequential function method and the strong nonlinearity of the neural network are combined, a traditional model can be greatly simplified, the identification precision of the stationary point heat flow is improved, and the real-time performance of on-line identification is ensured.

Description

technical field [0001] The invention relates to a calculation method for surface heat flow identification and a neural network correction method, in particular to a three-dimensional effect correction method for surface heat flow identification based on a neural network. Background technique [0002] Hypersonic flight faces serious aerodynamic heating problems. Due to the strong friction and compression of the air, a large amount of kinetic energy is converted into heat energy, causing the air temperature around the aircraft to rise sharply. The high temperature affects the structural strength and rigidity of the aircraft, and even causes ablation damage to the outer surface. The design of thermal protection system is an important support for the rapid development of hypersonic flight technology, and its research design requires a large amount of test data from flight tests. The measurement of key parameters such as temperature and heat flow during aircraft service is a nec...

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Application Information

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IPC IPC(8): G06F17/50G06N3/04
CPCG06F30/20G06F2119/08G06F30/15G06N3/045
Inventor 陈伟芳赵文文潘学浩沈煊
Owner ZHEJIANG UNIV
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