Open Access
Volume 41, Number 2, April 2023
Page(s) 264 - 273
Published online 07 June 2023
  1. KRVGER W, BESSELINK I, COWLING Det al. Aircraft landing gear dynamics: simulation and control[J]. Vehicle System Dynamics, 1997, 28(2/3): 119–158 [CrossRef] [Google Scholar]
  2. FENG Yunwen, ZHU Zhengzheng, YAO Xionghuaet al. Research on safety analysis method of civil aircraft landing gear[J]. Journal of Northwestern Polytechnical University, 2016, 34(6): 969–975 [Article] [Article] (in Chinese) [Google Scholar]
  3. XUE Jing, LI Yuren, TIAN Guanglaiet al. Finite element analysis of temperature field of aircraft brake disc[J]. Computer Simulation, 2009, 26(4): 27–30 [Article] (in Chinese) [Google Scholar]
  4. YANG Quanwei, HE Fadong, WANG Wenjunet al. Linear transformation and robustness in load measurement of aircraft landing gear[J]. Chinese Journal of Applied Mechanics, 2013, 30(4): 608–612 [Article] (in Chinese) [Google Scholar]
  5. SARTOR P, BECKER W, WORDEN Ket al. Bayesian sensitivity analysis of flight parameters in a hard-landing analysis process[J]. Journal of aircraft, 2016, 53(5): 1317–1331 [Article] [CrossRef] [Google Scholar]
  6. QI Mingliang, SHAO Xueyan, CHI Hong. Flight operation risk diagnosis method of QAR overrun event[J]. Journal of Beijing University of Aeronautics and Astronsutics, 2011, 37(10): 1207–1210 (in Chinese) [Google Scholar]
  7. CHEN J, CHEN S, LIU Zet al. Health monitoring of landing gear retraction/extension system based on optimized fuzzy C-means algorithm[J]. IEEE Access, 2020, 8219611–219621 [Article] [CrossRef] [Google Scholar]
  8. SARTOR P, SCHMIDT R K. Aircraft landing gear structural health monitoring using a loads monitoring approach[J]. Revue Internationale de la Croix-Rouge et Bulletin international des Sociétés de la Croix-Rouge, 2008, 33(387): 1–10 [Google Scholar]
  9. SUN Y G, SUN L. The design of avionics system interfaces emulation and verification platform based on QAR data[J]. Applied Mechanics and Materials, 2014, 668/669879–883 [Article] [Google Scholar]
  10. WANG Lei, SUN Ruishan, WU Changxuet al. Quantitative evaluation model of heavy landing risk based on flight QAR data[J]. China Safety Science Journal, 2014, 24(2): 88–92 [Article] (in Chinese) [Google Scholar]
  11. ZHONG J, WANG D, LI C. A nonparametric health index and its statistical threshold for machine condition monitoring[J]. Measurement, 2020, 167108290 [Google Scholar]
  12. HE Q, YAN R, KONG Fet al. Machine condition monitoring using principal component representations[J]. Mechanical Systems and Signal Processing, 2009, 23(2): 446–466 [Article] [CrossRef] [Google Scholar]
  13. CHENG Hongbo, LUN Li, KANG Chenet al. A transformer state evaluation method based on multivariate statistical analysis[J]. Power Grid Technology, 2018, 42(2): 2719–2724 (in Chinese) [Google Scholar]
  14. PEDREGAL D J, CARMEN C M. State space models for condition monitoring: a case study[J]. Reliability Engineering & System Safety, 2006, 91(2): 171–180 [CrossRef] [Google Scholar]
  15. SONG Weijie, GUAN Shan, PANG Hongyang. Tool wear state monitoring based on Hilbert-Yellow transform and equidistant feature mapping[J]. Modular Machine Tool and Automatic Processing Technology, 2018, 6114–118 [Article] (in Chinese) [Google Scholar]
  16. ATTOUI I, BOUTASSETA N, FERGANI Net al. Novel machinery monitoring strategy based on time-frequency domain similarity measurement with limited labeled data[J]. IEEE Trans on Instrumentation and Measurement, 2020, 703500708 [Google Scholar]
  17. CAO W, CHEN W, DONG Get al. Wear condition monitoring and working pattern recognition of piston rings and cylinder liners using on-line visual ferrograph[J]. Tribology Transactions, 2014, 57(4): 690–699 [CrossRef] [Google Scholar]
  18. MENG Guang, YOU Mingyi. Research progress of equipment life prediction and preventive maintenance planning based on condition monitoring[J]. Journal of Vibration and Shock, 2011, 30(8): 1–11 (in Chinese) [Google Scholar]
  19. DALKIRAN F Y, TORAMAN M. Predicting thrust of aircraft using artificial neural networks[J]. Aircraft Engineering and Aerospace Technology, 2021, 93(1): 35–41 [CrossRef] [Google Scholar]
  20. WANG S, ZHANG N, WU Let al. Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method[J]. Renewable Energy, 2016, 94629–636 [CrossRef] [Google Scholar]
  21. AI Jianliang, YANG Xizhong. An aero-engine fault diagnosis method based on adaptive neural network[J]. Science China Technology Sciences, 2018, 48(3): 326–335 [Article] (in Chinese) [Google Scholar]
  22. ZHOU J, QIU Y, ZHU Set al. Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate[J]. Engineering Applications of Artificial Intelligence, 2021, 97(1): 104015 [Google Scholar]
  23. CUI Jianguo, LI Shengnan, YU Mingyueet al. Performance trend prediction analysis of aircraft brake system based on combination prediction model[J]. Science Technology and Engineering, 2018, 18(31): 179–183 (in Chinese) [Google Scholar]
  24. LI Yaohua, WANG Xingzhou. Fault diagnosis of aircraft hydraulic system[J]. Computer Engineering and Applications, 2019, 55(5): 232–236 (in Chinese) [Google Scholar]
  25. GU Runping, LAI Jinghan, WEI Zhiqiang. Flight residual oil prediction method based on improved BP neural network[J]. Journal of Flight Mechanics, 2020, 38(4): 76–80 [Article] (in Chinese) [Google Scholar]
  26. XU Yi, WANG Huawei, XIONG Minglan. Civil aviation risk assessment system and prediction model based on PCA-GA-BP[J]. Ship Electronic Engineering, 2021, 41(2): 77–81 [Article] (in Chinese) [Google Scholar]
  27. MIRJALILI S, LEWIS A. The whale optimization algorithm[J]. Advances in Engineering Software, 2016, 95(1): 51–67 [CrossRef] [Google Scholar]

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