Fault Diagnosis Based on Chaos System under Strong Noise

被引：0
|
作者：
Huang P. [1 ]
Qu J. [1 ]
Chai Y. [1 ]
Chen X. [1 ]
Liu Q. [1 ]
机构：
[1] School of Automation, Chongqing University, Chongqing
来源：
Yuhang Xuebao/Journal of Astronautics | 2023年 / 44卷 / 08期
关键词：
Chaos system; Fault diagnosis; Fractional-order system; Hypersonic vehicle; Sensor fault;
D O I：
10.3873/j.issn.1000-1328.2023.08.009
中图分类号：
学科分类号：
摘要：
A study on fault diagnosis methods for angle of attack sensors is made to address the strong nonlinearity and noise issues of hypersonic aircraft. Based on the noise immunity properties of the chaos system, a fault signal feature extraction method is proposed by designing the parameters and order of the fractional-order chaos system. This method can effectively reduce the adverse effects of strong noise on fault feature extraction and fault diagnosis. A hypersonic aircraft angle of attack sensor fault diagnosis classifier is constructed using a combination of system models and machine learning for hypersonic aircraft sensor fault diagnosis. The simulation results validate the effectiveness of the proposed fractional-order chaos system in extracting fault signal features, which can significantly improve the accuracy of fault diagnosis. © 2023 China Spaceflight Society. All rights reserved.
引用
收藏
页码：1203 / 1212
页数：9
相关论文
共 19 条
  • [1] AI S J, SONG J, CAI G B., A real-time fault diagnosis method for hypersonic air vehicle with sensor fault based on the auto temporal convolutional network, Aerospace Science and Technology, 119, (2021)
  • [2] CHEN Yao, TAN Liguo, WEI Yiyin, Et al., Adaptive saturated fault-tolerant tracking control of flexible hypersonic vehicle considering state constraints, Journal of Astronautics, 42, 7, pp. 850-861, (2021)
  • [3] SHEN Yi, LI Liliang, WANG Zhenhua, A review of fault diagnosis and fault-tolerant control techniques for spacecraft, Journal of Astronautics, 41, 6, pp. 647-656, (2020)
  • [4] HUANG Jie, YAO Weixing, Drag reduction of hypersonic-vehicles by shock control [J], Journal of Astronautics, 41, 10, pp. 1280-1287, (2020)
  • [5] SAFAEIPOUR H, FOROUZANFAR M, RAMEZANI A., Incipient fault detection in nonlinear non-Gaussian noisy environment, Measurement, 174, (2021)
  • [6] HE Q Z, ZHANG W G, LU P, Et al., Performance comparison of representative model-based fault reconstruction algorithms for aircraft sensor fault detection and diagnosis, Aerospace Science and Technology, 98, (2020)
  • [7] FENG X X, WANG Y Q., Fault estimation based on sliding mode observer for Takagi-Sugeno fuzzy systems with digital communication constraints, Journal of the Franklin Institute, 357, 1, pp. 569-588, (2020)
  • [8] MEI Y F, LIAO Y, GONG K J, Fuzzy adaptive sliding mode fault estimation and fixed-time fault-tolerant control for coupled spacecraft based on SE (3), Aerospace Science and Technology, 126, (2022)
  • [9] LI Juan, ZHAO Yougang, YU Yang, Et al., Optimal fault diagnosis for networked control systems with large time-delays and noises, Acta Automatica Sinica, 38, 5, pp. 858-864, (2012)
  • [10] LUO Xiaoyuan, PAN Xueyang, WANG Xinyu, Et al., Detection of false data injection attack in smart grid via adaptive Kalman filtering [J], Acta Automatica Sinica, 48, 12, pp. 2960-2971, (2022)
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