ACTA AERONAUTICAET ASTRONAUTICA SINICA >
A Fault Diagnosis Approach for Spacecraft Based on Hierarchical Transition System Model
Received date: 2012-03-06
Revised date: 2012-05-25
Online published: 2012-06-07
Supported by
National Basic Research Program of China (2012CB720003)
In order to improve the low resolution of the diagnostic results caused by the poor completeness and low diagnostic efficiency of a traditional single-granularity transition system model when modeling a spacecraft autonomous fault diagnosis system, a multi-granularity transition system model is proposed. A hierarchical strategy is used to build such a model using multi-granularity diagnostic knowledge according to the granularity and the structure. An up-to-down recursive inference algorithm is proposed to detect the failure component, confirm the fault-mode and locate the fault candidate set by reducing the search space layer by layer. Meanwhile, a separation strategy for conflict recognition is used to reduce the amount of calculation. The telemetry and command subsystem of a certain spacecraft is modeled with this approach and the result of the simulation shows that the completeness of the model, the diagnostic resolution and the diagnostic efficiency are significantly improved.
JIN Yang , WANG Rixin , XU Minqiang . A Fault Diagnosis Approach for Spacecraft Based on Hierarchical Transition System Model[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013 , 34(2) : 401 -408 . DOI: 10.7527/S1000-6893.2013.0046
[1] Schetter T, Campbell M, Surka D. Multiple agent-based autonomy for satellite constellations. Artificial Intelligence, 2003, 145(1): 147-180.
[2] Jiang L X, Li H W, Yang G Q, et al. A survey of spacecraft autonomous fault diagnosis research. Journal of Astronautics, 2009, 30(4): 1320-1326. (in Chinese) 姜连祥, 李华旺, 杨根庆, 等. 航天器自主故障诊断技术研究进展. 宇航学报, 2009, 30(4): 1320-1326.
[3] Venkatasubramanian V, Rengaswamy R, Kavuri S N. A review of process fault detection and diagnosis. Part II: qualitative models and search strategies. Computers and Chemical Engineering, 2003, 27(3): 313-326.
[4] Wang D, Feng W Q, Li J W. A hybrid and hierarchy modeling approach to model-based diagnosis. Electrical Engineering and Control, 2011, 98: 173-180.
[5] Thumati B T, Feinstein M A, Fonda J W, et al. An online model-based fault diagnosis scheme for HVAC systems. 2011 IEEE International Conference on Control Applications (CCA), 2011.
[6] Song Q J, Xu M Q, Wang R X. Spacecraft fault diagnosis based on hierarchical digraphs. Acta Aeronautica et Astronautica Sinica, 2006, 27(3): 448-452. (in Chinese) 宋其江, 徐敏强, 王日新. 基于分层有向图的航天器故障诊断. 航空学报, 2006, 27(3): 448-452.
[7] Williams B C, Nayak P P. A reactive planner for a model-based executive. Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997.
[8] Kurien J, Nayak P P. Back to the future for consistency-based trajectory tracking. The 17th National Conference on Artificial Intelligence, 2000.
[9] Manna Z, Pnueli A. The temporal logic of reactive and concurrent systems. New York: Springer, 1992.
[10] Hayden S C, Sweet A J, Christa S E, et al. Advanced diagnostic system on Earth Observing One. Proceedings of AIAA Space 2004 Conference and Exhibit, 2004.
[11] Hayden S C, Sweet A J, Christa S E. Livingstone model-based diagnosis of Earth Observing One. Proceedings of AIAA Intelligent Systems Conference, 2004.
[12] Schwabacher M, Samuels J, Brownston L. The NASA integrated vehicle health management technology experiment for X-37. SPIE AeroSense, 2002.
[13] Huang J J, Zhang H M. Multi-granularity modeling in virtual prototype description of complex product. Journal of System Simulation, 2009, 21(17): 5445-5449. (in Chinese) 黄俊杰, 张和明. 复杂产品虚拟样机描述中的多粒度建模方法. 系统仿真学报, 2009, 21(17): 5445-5449.
[14] Liu C F, Feng L. Construction and application of hierarchical knowledge granularity. Advanced Materials Research, 2010, 143-144: 717-721.
[15] Reiter R. A theory of diagnosis from first principles. Artificial Intelligence, 1987, 32(1): 57-95.
[16] Fang M. A practical method to identify the minimal conflict sets. Journal of Hefei University of Technology: Natural Science Edition, 1999, 22(1): 39-43. (in Chinese) 方敏. 一种识别最小冲突集的实用方法. 合肥工业大学学报: 自然科学版, 1999, 22(1): 39-43.
[17] Jiang Y F, Lin L. Computing the minimal hitting sets with binary HS-tree. Journal of Software, 2002, 13(12): 2267-2274. (in Chinese) 姜云飞, 林笠. 用对分HS-树计算最小碰集. 软件学报, 2002, 13(12): 2267-2274.
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