Continuous rotation detonation combustion chamber supercharge ratio predicting method based on RBF neural network

A technology of neural network and prediction method, which is applied in the field of continuous rotating detonation combustion chamber pressurization ratio prediction, can solve the problem of not being able to effectively predict the continuous rotation detonation combustion chamber pressure ratio, so as to reduce research cost and time, and strengthen The effect of self-organization and adaptive capacity

Active Publication Date: 2017-09-08
HARBIN ENG UNIV
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Problems solved by technology

However, there is currently no technique that can effectively predict the boost ratio of continuously rotating detonation combustors

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  • Continuous rotation detonation combustion chamber supercharge ratio predicting method based on RBF neural network
  • Continuous rotation detonation combustion chamber supercharge ratio predicting method based on RBF neural network
  • Continuous rotation detonation combustion chamber supercharge ratio predicting method based on RBF neural network

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[0025] Exemplary embodiments of the present invention will be described below with reference to the accompanying drawings. In the interest of clarity and conciseness, not all features of an actual implementation are described in this specification. It should be understood, however, that in developing any such practical embodiment, many implementation-specific decisions must be made in order to achieve the developer's specific goals, such as meeting those constraints related to the system and business, and those Restrictions may vary from implementation to implementation. Moreover, it should also be understood that development work, while potentially complex and time-consuming, would at least be a routine undertaking for those skilled in the art having the benefit of this disclosure.

[0026] Here, it should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, only the device structure and / or processing steps closely related to the ...

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Abstract

The invention provides a continuous rotation detonation combustion chamber supercharge ratio predicting method based on a RBF neural network. The predicting method comprises the following steps: data sample acquisition, selection of input and output parameters, determination of the structure of the RBF neural network, training and testing of the RBF neural network and the like. The axial size, the peripheral size, the matching of inlet fuel/oxidizing agent flow, and total temperature and total pressure of an oxidizing agent of a combustion chamber are selected as input parameters of the RBF neural network, and the supercharge ratio of the combustion chamber is selected as an output parameter of the RBF neural network. By the predicting method, the specific mathematical relation between the input parameters and the output parameter does not need to be determined, the supercharge ratio of the continuous rotation detonation combustion chamber can be realized effectively, and the predicting method has a certain guidance significance on performance prediction of the continuous rotation detonation combustion chamber, the structural optimized design and modeling and simulation of a complete machine.

Description

technical field [0001] The invention relates to the fields of combustion, gas turbines and artificial intelligence, in particular to a method for predicting the pressurization ratio of a continuously rotating detonation combustion chamber based on an RBF neural network. Background technique [0002] With the intensification of the global energy crisis and the improvement of human awareness of environmental protection, how to achieve a substantial improvement in the performance of gas turbines is an important problem that needs to be solved urgently in the fields of aviation, ships and industrial power generation. Compared with the isobaric combustion used in modern gas turbines, continuous rotating detonation combustion has many advantages such as one-time ignition, small entropy increase, self-pressurization, and low emissions, and has become one of the most effective ways to improve the performance of gas turbines. [0003] The boost ratio is one of the important parameter...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/04
Inventor 赵宁波郑洪涛李智明祁磊
Owner HARBIN ENG UNIV
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