A satellite fault in-orbit real-time fault diagnosis method and system based on deep learning

A deep learning, satellite fault technology, applied in instruments, character and pattern recognition, data processing applications, etc., can solve problems such as high cost, difficulty in data acquisition, restricting the accuracy and generalization of existing methods, etc.
CN109934130AInactive Publication Date: 2019-06-25CHINA ACADEMY OF SPACE TECHNOLOGY

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA ACADEMY OF SPACE TECHNOLOGY
Publication Date
2019-06-25
Estimated Expiration
Not applicable · inactive patent

Smart Images

  • Figure 1
    Figure 1
Patent Text Reader

Abstract

The invention discloses a satellite fault in-orbit real-time fault diagnosis system and method based on deep learning. The method comprises the following specific steps: (1) acquiring historical observation data of a satellite single machine and a subsystem; Wherein the historical observation data is remote measurement data; (2) constructing a training set by adopting historical observation data of the single satellite and the sub-system, and training the deep learning model to obtain a satellite fault deep learning model of the single satellite and the sub-system; (3) predicting on-orbit observation data collected in real time by adopting a satellite fault deep learning model to obtain a prediction result of a next frame; (4) obtaining actual measurement data of the next frame, and comparing the actual measurement data with a prediction result to obtain a prediction error; (5) judging whether the prediction error continuously exceeds a preset range for N times or not, and if yes, performing fault diagnosis according to a comparison result; Otherwise, repeating the steps (3)-(5). According to the invention, the satellite in-orbit fault autonomous diagnosis capability is improved.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to a method and system for on-orbit real-time fault diagnosis of satellite faults based on deep learning, and is suitable for real-time fault diagnosis of high-orbit satellite on-orbit faults. Background technique

[0002] With the development of aerospace technology and the increasing demand for satellites in various countries, the number of artificial satellites launched around the world has also increased dramatically, and the reliability of satellites has seriously affected the quality of satellite services. In order to ensure the safety and reliability of the satellite, it is extremely necessary for the satellite to have an autonomous fault diagnosis function. Problems faced by current satellite in-orbit fault diagnosis:

[0003] 1. The number of satellites has increased sharply, and the traditional on-orbit operation and maintenance model is limited. For a long time, when the satellite is in orbit, the response to abnormal...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More