Aiming at the problem of multiple faults in the electro-hydraulic servo actuator system (EHSA), this paper proposes a novel fault diagnosis method based on a nonsingular terminal sliding mode observer (NTSMO). Three typical faults, namely servo valve stuck, hydraulic cylinder leakage, and open circuit, are modeled and injected into the EHSA based on their fault mechanisms and corresponding mathematical descriptions. The main focus of the study lies in the design of a group of NTSMOs specifically developed for fault diagnosis, supported by a more accurate AMESim model to enhance simulation reliability. Fault decision-making is further achieved through a dedicated observer strategy (DOS) combined with an adaptive threshold mechanism. Theoretical analysis verifies the stability and accuracy of the proposed observer as well as the rationality of the adaptive threshold design. Co-simulation results using AMESim/MATLAB demonstrate that the proposed method exhibits strong applicability and high diagnostic accuracy for the three typical types of faults.
BanerjeePPandeyK (2016) Implementation of failure modes and effect analysis on the electro-hydraulic servo valve for steam turbine. In: 2016 IEEE 1st international conference on power electronics, intelligent control and energy systems (ICPEICES), New Delhi, India, 4–6 July, pp. 1–3. New York: IEEE.
2.
BertolinoACDe MartinAJacazioG, et al. (2021) A case study on the detection and prognosis of internal leakages in electro-hydraulic flight control actuators. Actuators10: 215.
3.
ChangXPengBLiuL, et al. (2016) Sensorless control of permanent magnet synchronous motor using a novel non singular terminal sliding mode observer. Journal of Xi’an Jiaotong University50(1): 85–91.
4.
CzyżniewskiMŁangowskiR (2022) A robust sliding mode observer for non-linear uncertain biochemical systems. ISA Transactions123: 25–45.
5.
GaoZCecatiCDingSX (2015) A survey of fault diagnosis and fault-tolerant techniques—part I: Fault diagnosis with model-based and signal-based approaches. IEEE Transactions on Industrial Electronics62(6): 3757–3767.
6.
JiaCKangKGaoW, et al. (2020) Fault prediction of electro-hydraulic servo valve based on CNN + LSTM neural network. Chinese Hydraulics & Pneumatics2020(12): 173–181.
7.
JiaQFuYChenG, et al. (2011) Fault diagnosis of space robotic arm joint based on state observer. Journal of Aeronautics42(1): 165–175.
8.
LiuHLiuDLuC, et al. (2014) Fault diagnosis of hydraulic servo system using the unscented Kalman filter. Asian Journal of Control16(6): 1713–1725.
9.
LiuJWangZYongY, et al. (2013) Fault diagnosis of integrated electro-hydraulic actuator based on improved HHT. Journal of Beihang University39(1): 62–66.
10.
LiuJYangLXuM, et al. (2020) Model-based detection of soft faults using the smoothed residual for a control system. Measurement Science and Technology32(1): 015107.
11.
LuH (2014) Application of proportional electro-hydraulic actuator in static blade control system of axial fan. Chemical Engineering and Equipment2014(3): 136–138.
12.
MaLXiaoLJiangB (2022) Wind turbine state feedback sliding mode fault-tolerant control based on wind speed estimation. Control Theory & Applications39(3): 480–490.
13.
MaLXiaoLMengZ, et al. (2020) Robust adaptive fault reconfiguration for micro-gas turbine based on optimized T–S fuzzy model and nonsingular TSMO. International Journal of Fuzzy Systems22: 2204–2222.
14.
MaLYanHCaiC, et al. (2021) Mechanism of temperature-induced zero drift on electro-hydraulic servo valve. AIP Advances11(6): 065210.
15.
NguyenMHDaoHVAhnKK (2023) Extended sliding mode observer-based high-accuracy motion control for uncertain electro-hydraulic systems. International Journal of Robust and Nonlinear Control33(2): 1351–1370.
16.
SaeedUJanSULeeYD, et al. (2021) Fault diagnosis based on extremely randomized trees in wireless sensor networks. Reliability Engineering & System Safety205: 107284.
17.
SchwungABeckMAdamyJ (2015) Fault diagnosis of dynamical systems using recurrent fuzzy systems with application to an electrohydraulic servo axis. Fuzzy Sets and Systems277: 138–153.
18.
SharifiSRezaeiSMTivayA, et al. (2016) Multi-class fault detection in electro-hydraulic servo systems using support vector machines. In: 2016 4th international conference on robotics and mechatronics (ICROM), Tehran, Iran, 26–28 October, pp. 252–257. New York: IEEE.
19.
ShuaiLQingGDanJ (2022) Electrohydraulic servo tracking control technique with finite-time uncertainty estimation. Chinese Hydraulics & Pneumatics46(2): 8–14.
20.
WangL (2021) Research on fault diagnosis test of hydraulic actuator of gas turbine control system. Master’s Thesis, North China Electric Power University, Beijing, China.
21.
WuJMingTShenJ (2011) A review on fault diagnosis technology of electro-hydraulic servo system. Hydraulics and Pneumatics2011(6): 18–14.
22.
WuYYaoL (2021) Fault diagnosis and fault tolerant control for manipulator with actuator multiplicative fault. International Journal of Control, Automation and Systems19: 980–987.
23.
XiaoLDuYHuJ, et al. (2018) Sliding mode fault tolerant control with adaptive diagnosis for aircraft engines. International Journal of Turbo & Jet-Engines35(1): 49–57.
24.
YangPLiuZLiD, et al. (2021) Sliding mode predictive active fault-tolerant control method for discrete multi-faults system. International Journal of Control, Automation and Systems19(3): 1228–1240.
25.
YuanYZhangMChenY, et al. (2018) Multi-sliding surface control for the speed regulation system of ship diesel engines. Transactions of the Institute of Measurement and Control40(1): 22–34.
26.
ZhangKJiangBChenF, et al. (2021) Directed-graph-learning-based diagnosis of multiple faults for high speed train with switched dynamics. IEEE Transactions on Cybernetics53(3): 1712–1724.
27.
ZhaoJShenGZhuW, et al. (2018) Force tracking control of an electro-hydraulic control loading system on a flight simulator using inverse model control and a damping compensator. Transactions of the Institute of Measurement and Control40(1): 135–147.
