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Satellite momentum wheel fault diagnosis modeling method and system based on HC-TP-K2 algorithm

A HC-TP-K2, satellite momentum wheel technology, applied in computing, computer parts, character and pattern recognition, etc., can solve the problems of complex calculation and inflexible model, and achieve the effect of improving accuracy

Inactive Publication Date: 2019-08-09
CHINA UNIV OF GEOSCIENCES (WUHAN)
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  • Application Information

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Problems solved by technology

[0009] The purpose of the invention is to propose a satellite momentum wheel fault diagnosis modeling method based on the HC-TP-K2 algorithm to overcome the shortcomings of existing momentum wheel fault diagnosis modeling methods such as complex calculations and inflexible models. more accurate fault diagnosis results

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  • Satellite momentum wheel fault diagnosis modeling method and system based on HC-TP-K2 algorithm
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[0047] In order to have a clearer understanding of the technical features, objectives and effects of the present invention, the specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0048] figure 1 It is a flowchart of an embodiment of the satellite momentum wheel fault diagnosis modeling method based on the HC-TP-K2 algorithm of the present invention. In this embodiment, the satellite momentum wheel fault diagnosis modeling method based on the HC-TP-K2 algorithm of the present invention includes the following steps:

[0049] (1) Establish a Bayesian network model of momentum wheel failure based on the HC-TP-K2 algorithm combined with momentum wheel failure data;

[0050] (2) Based on the Bayesian network model established in step (1), use Bayesian network parameter learning to obtain the parameters of each network node in the model;

[0051] (3) Based on the model with node parameters obtained in step (2) and the ...

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Abstract

The invention discloses a satellite momentum wheel fault diagnosis modeling method and system based on an HC-TP-K2 algorithm. The objective of the invention is to solve a node sequence problem in a K2algorithm. The invention provides a K2 algorithm based on a hill climbing algorithm and topological sorting. According to the algorithm, firstly, a hill climbing algorithm is used for learning data to obtain an initial network structure, then a topological sorting algorithm is used for obtaining topological sorting of nodes, and finally the node sequence is applied to a K2 algorithm, so that theaccuracy of the K2 algorithm in satellite momentum wheel fault diagnosis modeling is improved.

Description

Technical field [0001] The present invention relates to a Bayesian network research method in the establishment of a satellite momentum wheel fault diagnosis model, in particular to the fields of spacecraft health management and computer technology. More specifically, the present invention relates to a method based on the HC-TP-K2 algorithm Satellite momentum wheel fault diagnosis modeling method and system. Background technique [0002] The momentum wheel is a key component of the satellite attitude control system. Traditional satellite momentum wheel fault diagnosis techniques such as observer method and expert system method cannot better solve the uncertainty in the satellite momentum wheel fault. As a kind of probability network, Bayesian network has obvious advantages in the reasoning of uncertainty problems. The model established by Bayesian network structure learning will affect the accuracy of the final reasoning result. The Bayesian network structure learning is an NP-h...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06K9/62
CPCG06F30/20G06F18/24155
Inventor 彭雷戴光明王茂才宋芳然
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)