Solar array expansion reliability assessment method based on expert knowledge and neural network
A neural network and expert knowledge technology, applied in the interdisciplinary field of aerospace engineering and information science, can solve problems such as undeployable tests, national property losses, and solar wings that cannot be deployed normally, and achieve reliability evaluation problems and objective evaluation results Effect
Active Publication Date: 2014-04-09
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology
If the solar wings cannot be deployed normally, it will cause disastrous consequences and cause heavy losses to national property
However, due to the expensive structure of the solar wing mechanism, it is impossible to conduct a large number of deployment tests
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[0019] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0020] figure 1 It is a modeling flowchart of the present invention.
[0021] The present invention uses expert knowledge to establish a comprehensive evaluation index system for the reliability of solar wing deployment, and uses Analytic Hierarchy Process (Analytic Hierarchy ProeesS, AHP) to synthesize expert knowledge to obtain the weight coefficients of each evaluation index. The distribution of weight coefficients shows that the solar wing deployment test data directly reflects the reliability of the solar wing deployment, and its influence on the comprehensive evaluation results of the solar wing deployment reliability is much greater than other test data, and the solar wing deployment test data is also more important than other data. Rich. Based on this, a BP neural network model is established for the solar wing deployment test, and the compreh...
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The invention discloses a solar array expansion reliability assessment method based on expert knowledge and a neural network, which comprises the steps of: creating a comprehensive solar array expansion reliability assessment index system according to expert knowledge; obtaining a weight vector of the assessment index system via a layered analysis method by the knowledge of a plurality of experts; adding the expert knowledge in the network training process of solar array expansion reliability network modeling, assessing the original test data by the plurality of experts to combine the test data with the expert knowledge and to unify the dimensions of the assessment standards. According to the invention, the expert knowledge is combined with the neural network method to fully utilize the historical test data to overcome the problems of high assessment result uncertainty and low reliability resulting from few test times and pure relay on expert knowledge.
Description
technical field [0001] The invention relates to a method for evaluating the reliability of solar wing deployment, which belongs to the cross field of aerospace engineering and information science. Background technique [0002] With the rapid development of aerospace technology, the structure of spacecraft is becoming more and more complex, and its functions are increasing. Various mechanisms are required to complete various tasks. The solar wing deployment mechanism is the main component of the satellite. Whether the solar wing can be successfully deployed is related to the success or failure of the satellite. In the history of spaceflight in the world, there have been many cases where the failure of the solar wing to deploy in the space orbit resulted in the failure of the launch or operation of the satellite. Whether the solar wings can be deployed is a prerequisite for the normal operation of the satellite. If the solar wings cannot be deployed normally, it will cause ...
Claims
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IPC IPC(8): G06N3/08
CPCY04S10/54Y04S10/50
Inventor 皮德常高天行
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS