Fault diagnosis method of link control system for gravitational wave detection

doi:10.23919/JSEE.2024.000048

Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (4): 922-931.doi: 10.23919/JSEE.2024.000048

• SYSTEMS ENGINEERING • Previous Articles

Fault diagnosis method of link control system for gravitational wave detection

Ai GAO¹^,²^,³^,*(), Shengnan XU¹^,²^,³(), Zichen ZHAO¹^,²^,³(), Haibin SHANG¹^,²^,³(), Rui XU¹^,²^,³()

¹ School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China
² Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration, Ministry of Industry and Information Technology, Beijing 100081, China
³ Key Laboratory of Dynamics and Control of Flight Vehicle, Ministry of Education, Beijing 100081, China

Received:2022-01-05 Online:2024-08-18 Published:2024-08-06
Contact: Ai GAO E-mail:gaoai@bit.edu.cn;1059860965@qq.com;BitZhaozc@foxmail.com;shanghb@bit.edu.cn;xurui@bit.edu.cn
About author:
GAO Ai was born in 1984. She received her Ph.D. degree from Harbin Institute of Technology, Harbin, in 2012. She is currently an associate professor at the School of Aerospace Engineering, Beijing Institute of Technology. Her research interests include autonomous navigation, guidance and control of deep space probe, spacecraft dynamics and multi-constraint trajectory optimization and autonomous approach observation and tracking control of non-cooperative targets. E-mail: gaoai@bit.edu.cn

XU Shengnan was born in 1998. She received her B.E. degree from Beijing Institute of Technology in 2023. She is currently pursuing her M.E. degree at the School of Aerospace Engineering, Beijing Institute of Technology. Her research interests include gravity wave detection task and attitude planning for aerospace vehicle. E-mail: 1059860965@qq.com

ZHAO Zicheng was born in 1997. He received his B.E. degree from Beijing Institute of Technology in 2020. He is currently a Ph.D. candidate at the School of Aerospace Engineering, Beijing Institute of Technology. His research interests include convex optimization, trajectory and attitude planning for aerospace vehicle, autonomous planning, guidance and control, gravity wave detection task and unmanned aerial vehicle obstacle-free path planning. E-mail: BitZhaozc@foxmail.com

SHANG Haibin was born in 1980. He received his Ph.D. degree from Harbin Institute of Technology, Harbin, in 2008. He is currently a professor at the School of Aerospace Engineering, Beijing Institute of Technology. His research interests include design and analysis of deep space exploration mission, spacecraft orbit design, optimization and analysis, orbit dynamics and low energy transfer in multi-body system and orbit dynamics and control in gravitational field of small bodies. E-mail: shanghb@bit.edu.cn

XU Rui was born in 1975. He received his Ph.D. degree from Harbin Institute of Technology, Harbin, in 2004. He is currently a professor at the School of Aerospace Engineering, Beijing Institute of Technology. His research interests include autonomous mission planning of spacecraft, attitude planning of spacecraft and fault identification and reconstruction. E-mail: xurui@bit.edu.cn
Supported by:
This work was supported by the National Key Research and Development Program Topics (2020YFC2200902) and the National Natural Science Foundation of China (11872110).

Abstract

Abstract:

To maintain the stability of the inter-satellite link for gravitational wave detection, an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is proposed. Different from the traditional fault diagnosis optimization algorithms, the fault intelligent learning method proposed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong coupling nonlinearity. By constructing a two-layer learning network, the method enables efficient joint diagnosis of fault areas and fault parameters. The simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s, and the fault diagnosis efficiency is improved by 99.8% compared with the traditional algorithm.

Key words: large scale multi-satellite formation, gravitational wave detection, laser link monitoring, fault diagnosis, deep learning

Ai GAO, Shengnan XU, Zichen ZHAO, Haibin SHANG, Rui XU. Fault diagnosis method of link control system for gravitational wave detection[J]. Journal of Systems Engineering and Electronics, 2024, 35(4): 922-931.

Figures/Tables 14

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References 31

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Failure diagnosis method		Computing time	Error
Optimization algorithm	Sequential quadratic programming algorithm	132.0619	${10^{ - 3}}$
	Particle swarm optimization	22361.3669	${10^{ - 6}}$
	Genetic algorithm	2425.8973	${10^{ - 2}}$
Machine learning	Deep learning	0.242113	${10^{ - 4}}$
Machine learning	Support vector machine	0.262848	${10^{ - 2}}$

Fault area	Number
Spacecraft attitude control failure	x₁
Telescope control failure	x₂
Test mass attitude control failure	x₃
Test mass-spacecraft relative displacement control failure	x₄

Fault area	Label
x₁	y₁
x₂	y₂
x₃	y₃
x₄	y₄
x_1，x₂	y₅
x_1，x_2，x₃	y₆
x_1，x_2，x_3，x₄	y₇

Fault area	Number of hidden layers	Number of neurons in hidden layers	Accuracy
y₁	4	[20,15,15,15]	0.8670
		[20,15,15,20]	0.8825
		[20,15,20,20]	0.8725
	5	[20,15,15,15,20]	0.9840
		[20,15,15,20,20]	0.9970
		[20,15,20,20,20]	0.9265
	6	[20,15,15,15,15,20]	0.9400
		[20,15,15,15,20,20]	0.9380
		[20,15,15,20,20,20]	0.9345
y₂	4	[20,15,15,15]	0.8995
		[20,15,15,20]	0.8945
		[20,15,20,20]	0.9115
	5	[20,15,15,15,20]	0.9925
		[20,15,15,20,20]	0.9960
		[20,15,20,20,20]	0.9500
	6	[20,15,15,15,15,20]	0.9860
		[20,15,15,15,20,20]	0.9405
		[20,15,15,20,20,20]	0.9870
y₃	4	[20,15,15,15]	0.9160
		[20,15,15,20]	0.8650
		[20,15,20,20]	0.8655
y₃	5	[20,15,15,15,20]	0.9880
		[20,15,15,20,20]	0.9965
		[20,15,20,20,20]	0.9925
	6	[20,15,15,15,15,20]	0.9920
		[20,15,15,15,20,20]	0.9875
		[20,15,15,20,20,20]	0.9915
y₄	4	[20,15,15,15]	0.8645
		[20,15,15,20]	0.8755
		[20,15,20,20]	0.8895
	5	[20,15,15,15,20]	0.9925
		[20,15,15,20,20]	0.9990
		[20,15,20,20,20]	0.9620
	6	[20,15,15,15,15,20]	0.9845
		[20,15,15,15,20,20]	0.9860
		[20,15,15,20,20,20]	0.9915
y₅	4	[20,15,15,15]	0.8845
		[20,15,15,20]	0.8680
		[20,15,20,20]	0.8750
	5	[20,15,15,15,20]	0.9690
		[20,15,15,20,20]	0.9968
		[20,15,20,20,20]	0.9925
	6	[20,15,15,15,15,20]	0.9885
		[20,15,15,15,20,20]	0.9795
		[20,15,15,20,20,20]	0.9890
y₆	4	[20,15,15,15]	0.8775
		[20,15,15,20]	0.8940
		[20,15,20,20]	0.8875
	5	[20,15,15,15,20]	0.9960
		[20,15,15,20,20]	0.9995
		[20,15,20,20,20]	0.9930
	6	[20,15,15,15,15,20]	0.9550
		[20,15,15,15,20,20]	0.9815
		[20,15,15,20,20,20]	0.9675
y₇	4	[20,15,15,15]	0.8865
		[20,15,15,20]	0.8810
		[20,15,20,20]	0.8895
	5	[20,15,15,15,20]	0.9880
		[20,15,15,20,20]	0.9955
		[20,15,20,20,20]	0.9910
	6	[20,15,15,15,15,20]	0.9910
		[20,15,15,15,20,20]	0.9730
		[20,15,15,20,20,20]	0.9855

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Fault diagnosis method of link control system for gravitational wave detection

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