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Fault detection method of satellite attitude control system for supervised locally linear embedding

A technology of local linear embedding and satellite attitude control, which can be used in testing/monitoring control systems, general control systems, control/regulation systems, etc., and can solve the problems of satellite attitude control system failures, difficulty in updating the database high-dimensional feature accuracy in real time, etc. , to achieve the effect of improving the detection ability

Active Publication Date: 2020-01-17
CHANGGUANG SATELLITE TECH CO LTD
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Problems solved by technology

[0006] In order to solve the problems that the local linear embedding (LLE) algorithm of the existing batch processing mode is difficult to update the database in real time and ensure the accuracy of high-dimensional feature extraction, the present invention provides a satellite attitude control system fault detection method that supervises local linear embedding

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  • Fault detection method of satellite attitude control system for supervised locally linear embedding
  • Fault detection method of satellite attitude control system for supervised locally linear embedding
  • Fault detection method of satellite attitude control system for supervised locally linear embedding

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specific Embodiment approach 1

[0043] Specific implementation mode 1. Combination Figure 1 to Figure 8 Illustrate this embodiment, supervise the fault detection method of the satellite attitude control system of partial linear embedding, this method is realized by the following steps:

[0044] Step 1. Obtain high-dimensional original satellite telemetry data, and perform feature analysis and preprocessing on the obtained original satellite telemetry data;

[0045] The telemetry parameters of the satellite are the state values ​​of each subsystem of the satellite transmitted by the telemetry arc, and the telemetry parameters of each subsystem can reflect the current operating status of each subsystem. Due to the high dimensionality of telemetry data, fuzzy research and analysis of telemetry data is not targeted. According to the research objectives of different subsystems, different telemetry data dimensionality reduction and classification methods need to be used to analyze and process the data. There wi...

specific Embodiment approach 2

[0113] Specific embodiment two, combine Figure 4 to Figure 8 Describe this embodiment, this embodiment is the embodiment of the fault detection method of the satellite attitude control system that supervises local linear embedding described in specific embodiment one:

[0114] The SLLE algorithm is applied to this embodiment through online data, and the satellite telemetry database is continuously updated and supplemented. Because d is an inherent property of satellite telemetry data, d does not change when the parameter type does not change. Neighborhood point dimension k needs to be adjusted. Here k=12, which is much smaller than the number of neighborhood points of the LLE algorithm, which greatly reduces the computational complexity. Figure 4 a is the telemetry data of the 12-dimensional satellite attitude control system after preprocessing, Figure 4 b is the data after dimensionality reduction by the algorithm. It can be seen that the dimensionality reduction data r...

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Abstract

A fault detection method of a satellite attitude control system for supervised locally linear embedding relates to telemetry data mining methods for supervised locally linear embedding, solves the problem that the local linear embedding (LLE) algorithm of the existing batch processing mode is difficult to update the database in real time and ensure the accuracy of high-dimensional feature extraction, and comprises the following steps of obtaining high-dimensional original telemetry satellite data, and performing characteristics analysis and preprocessing on the obtained original telemetry satellite data; reducing the dimension of the pre-processed original satellite telemetry data by using the SLLE algorithm to obtain low-dimensional embedded feature information of satellite control systemtelemetry data, and using SPE statistics to complete fault detection. The invention uses the SLLE algorithm to extract high-dimensional data features, combines statistical SPE and T2 to design a fault detection scheme, and finally verifies the effectiveness of the fault detection scheme of the satellite attitude control system through the simulation of satellite telemetry data. The method effectively improves the detection ability of satellite abnormal states and has certain practical application value in engineering.

Description

technical field [0001] The invention relates to a remote measurement data mining method for supervising local linear embedding, and has the ability to detect abnormal states of spacecraft. Specifically, it relates to a fault detection method of satellite attitude control system with supervised local linear embedding, which is directly applied to the field of fault detection of spacecraft attitude control system. Background technique [0002] Currently, in the prior art, "Dynamic Recurrent Neural Network Fault Diagnosis and Isolation Architecture for Satellite Actuator / Thruster Faults", 2005 International Symposium on Neural Networks, 2005, 574-583. In this paper, the DRNN algorithm is used to complete the fault diagnosis of the spacecraft actuator, and different DRNN networks are used to isolate the fault detection of the actuator. Although this method can classify the fault modes in real time, the generalization ability of this method is not ideal, and it is only compatibl...

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Application Information

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IPC IPC(8): G05B23/02G06K9/62
CPCG05B23/024G06F18/21375
Inventor 曲直徐开何昕李峰刘萌萌解延浩韩霜雪任颢
Owner CHANGGUANG SATELLITE TECH CO LTD
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