Anomaly Monitoring Method for Key Components of Satellite

Joint Authors

Peng, Jian
Fan, Linjun
Xiao, Weidong
Tang, Jun

Source

The Scientific World Journal

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-14, 14 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-01-22

Country of Publication

Egypt

No. of Pages

14

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

This paper presented a fault diagnosis method for key components of satellite, called Anomaly Monitoring Method (AMM), which is made up of state estimation based on Multivariate State Estimation Techniques (MSET) and anomaly detection based on Sequential Probability Ratio Test (SPRT).

On the basis of analysis failure of lithium-ion batteries (LIBs), we divided the failure of LIBs into internal failure, external failure, and thermal runaway and selected electrolyte resistance (Re) and the charge transfer resistance (Rct) as the key parameters of state estimation.

Then, through the actual in-orbit telemetry data of the key parameters of LIBs, we obtained the actual residual value (RX) and healthy residual value (RL) of LIBs based on the state estimation of MSET, and then, through the residual values (RX and RL) of LIBs, we detected the anomaly states based on the anomaly detection of SPRT.

Lastly, we conducted an example of AMM for LIBs, and, according to the results of AMM, we validated the feasibility and effectiveness of AMM by comparing it with the results of threshold detective method (TDM).

American Psychological Association (APA)

Peng, Jian& Fan, Linjun& Xiao, Weidong& Tang, Jun. 2014. Anomaly Monitoring Method for Key Components of Satellite. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1048314

Modern Language Association (MLA)

Peng, Jian…[et al.]. Anomaly Monitoring Method for Key Components of Satellite. The Scientific World Journal No. 2014 (2014), pp.1-14.
https://search.emarefa.net/detail/BIM-1048314

American Medical Association (AMA)

Peng, Jian& Fan, Linjun& Xiao, Weidong& Tang, Jun. Anomaly Monitoring Method for Key Components of Satellite. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1048314

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1048314