Electro-Hydraulic Systems (EHS) are commonly used in many industrial applications. Prediction and timely fault detection of EHS can significantly reduce their maintenance cost, and eliminate the need for redundant actuators. Current practice to detect faults in the actuators can miss failures with combination of multiple sources. Missed faults can result in sudden, unforeseen failures. We propose a fault detection technique based on Multiple Regressor Adaptive Observers (MRAO). The results were evaluated using a two-stage servo-valve model. The proposed MRAO can be used for on-line fault detection. Therefore, we propose a health monitoring approach based on the trend of the identified parameters of the system. Using the history of identified parameters, normal tear and wear of the actuator can be distinguished from the component failures to more accurately estimate the remaining useful life of the actuator.
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ASME 2017 Dynamic Systems and Control Conference
October 11–13, 2017
Tysons, Virginia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5828-8
PROCEEDINGS PAPER
Prognostics and Health Monitoring of Electro-Hydraulic Systems
Damoon Soudbakhsh,
Damoon Soudbakhsh
Massachusetts Institute of Technology, Cambridge, MA
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Anuradha M. Annaswamy
Anuradha M. Annaswamy
Massachusetts Institute of Technology, Cambridge, MA
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Damoon Soudbakhsh
Massachusetts Institute of Technology, Cambridge, MA
Anuradha M. Annaswamy
Massachusetts Institute of Technology, Cambridge, MA
Paper No:
DSCC2017-5392, V002T19A005; 6 pages
Published Online:
November 14, 2017
Citation
Soudbakhsh, D, & Annaswamy, AM. "Prognostics and Health Monitoring of Electro-Hydraulic Systems." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications. Tysons, Virginia, USA. October 11–13, 2017. V002T19A005. ASME. https://doi.org/10.1115/DSCC2017-5392
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