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Method for identifying flow state of large-scale supersonic air inlet channel

A supersonic air inlet and flow state technology, applied in character and pattern recognition, instruments, electrical digital data processing, etc.

Pending Publication Date: 2020-10-27
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide an efficient hybrid algorithm to solve the identification problem of the flow state of the intake port directly based on a large amount of dynamic test data

Method used

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  • Method for identifying flow state of large-scale supersonic air inlet channel
  • Method for identifying flow state of large-scale supersonic air inlet channel
  • Method for identifying flow state of large-scale supersonic air inlet channel

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Embodiment Construction

[0047] In order to better reflect the superiority of the present invention,

[0048] In the case of supersonic inlet flow status recognition, first collect sample data of a certain type of external pressure supersonic inlet, and perform related preprocessing. The specific process is as follows: divide all samples into training set and test set, and then use the ReliefF algorithm to select the most effective sensor position for identifying the current flow state of the intake duct, and each sample is composed of the selected sensor signals .

[0049] Then, for each test sample x to be determined, quickly find its k accurate neighbor samples. The specific process is as follows: First, a reference sample R is randomly determined, and an ordered queue and an index table are established according to the distance between each training sample and R. The record in the index table is the order in the The position of each training sample in the ordered queue and its distance to R. After ...

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Abstract

The invention provides a method for identifying the flow state of a large-scale supersonic air inlet channel, and the method is a mixed algorithm combining F-KNN and I-DAGSVM, and is used for solvinga problem of flow state identification of the large-scale supersonic air inlet channel. The hybrid algorithm comprises the following steps: firstly, k accurate neighbor samples of each test sample byusing F-KNN are quickly found; then, based on the neighbor samples, an I-DAGSVM is used to train a local classifier to carry out discrimination; therefore, the efficient search speed of the F-KNN andthe excellent classification performance of the I-DAGSVM are combined; meanwhile, the defects that the F-KNN algorithm is mistakenly classified when the numbers of neighbor samples belonging to different categories are equal and the training process of the I-DAGSVM algorithm is very time-consuming when the I-DAGSVM algorithm is used for processing big data are also overcome, so that an excellent classification result can be obtained within reasonable running time.

Description

Technical field [0001] The invention relates to the technical field of flow state identification of a supersonic inlet, in particular to a method for identifying the flow state of a large-scale supersonic inlet. Background technique [0002] As one of the key components of the aspirated supersonic propulsion system, the supersonic inlet has a direct impact on the performance of the entire system. For example, intake port surge is an extremely unstable flow state, usually accompanied by severe and periodic shock wave oscillations, so that the thrust characteristics of the entire system will be seriously deteriorated, and the risk of flameout is always faced. Not only that, the periodic thermal load generated by the shock wave oscillation will also make the maneuverability of the entire system drastically worse, and may even directly lead to the destruction of the overall structure, posing a threat to the safety of aircraft and personnel. From the perspective of protection control...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06K9/62G06F30/28G06F119/14G06F113/08
CPCG06F30/27G06F2119/14G06F2113/08G06F30/28G06F18/24147G06F18/2411
Inventor 吴奂赵永平李兵谭慧俊
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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