A multi-fault diagnosis strategy of electro-hydraulic servo actuation system based on extended Kalman filter
Title | A multi-fault diagnosis strategy of electro-hydraulic servo actuation system based on extended Kalman filter |
Publication Type | Conference Paper |
Year of Publication | 2017 |
Authors | Wang, X., Lin, S., Wang, S., Shi, J., Zhang, C. |
Conference Name | 2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM) |
ISBN Number | 978-1-5386-3135-5 |
Keywords | actuation system, aerospace control, extended Kalman filter, fault diagnosis, Human Behavior, human factor, human factors, Kalman filters, Metrics, multi-fault diagnosis, multiple fault diagnosis, Pistons, pubcrawl, resilience, Resiliency, Servomotors, Valves |
Abstract | Electro-hydraulic servo actuation system is a mechanical, electrical and hydraulic mixing complex system. If it can't be repaired for a long time, it is necessary to consider the possibility of occurrence of multiple faults. Considering this possibility, this paper presents an extended Kalman filter (EKF) based method for multiple faults diagnosis. Through analysing the failure modes and mechanism of the electro-hydraulic servo actuation system and modelling selected typical failure modes, the relationship between the key parameters of the system and the faults is obtained. The extended Kalman filter which is a commonly used algorithm for estimating parameters is used to on-line fault diagnosis. Then use the extended Kalman filter to diagnose potential faults. The simulation results show that the multi-fault diagnosis method based on extended Kalman filter is effective for multi-fault diagnosis of electro-hydraulic servo actuation system. |
URL | https://ieeexplore.ieee.org/document/8274848 |
DOI | 10.1109/ICCIS.2017.8274848 |
Citation Key | wang_multi-fault_2017 |