Solenoid Valve Diagnosis for Railway Braking Systems with Embedded Sensor Signals and Physical Interpretation
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
This paper proposes a fault diagnosis method for solenoid valves in urban railway braking systems. For dominant failure modes of solenoid valves, sensor signals including electrical current, and input and output pressure were acquired and analyzed. The physical behaviors of the solenoid valves are modeled analytically. Numerous forces including magnetic, elastic, and gravity forces are incorporated in the model. With the analytical model and sensor signals, health indices are defined. The health indices are used to quantify the condition of the solenoid valves with different failure modes. Finally, a fault diagnosis method is proposed with the health indices and failure criteria. We anticipate that this study can help decrease maintenance costs and improve reliability of urban railway braking systems.
How to Cite
##plugins.themes.bootstrap3.article.details##
PHM
Yang, B. S., & Widodo, A. (2009). Introduction of Intelligent Machine Fault Diagnosis and Prognosis, Nova Science Publishers, New York, NY.
Ma, Q. (1997). Condition-Based Maintenance Applied to Rail Freight Car Components: the Case of Rail Car Trucks, Massachusetts Institute of Technology, Boston, MA.
Kryter, R. C. (1990). Nonintrusive Methods for Monitoring the Operational Readiness of Solenoid-Operated Valves, Nuclear Engineering and Design, vol. 118 (3), pp. 409-417.doi:10.1016/0029-5493(90)90042-V
Straky, H., & Weispfenning, T. (1999). Model Based Fault Detection of Hydraulic Brake System, Proceedings of IEEE European Control Conference. August 31-September 3, Karlsruhe, Germany.
Börner, M., Straky, H., Weispfenning, T., & Isermann, R. (2002). Model Based Fault Detection of Vehicle Suspension and Hydraulic Brake Systems, Mechatronics, vol. 12 (8), pp. 999-1010. doi:10.1016/S0957-4158(02)00008-9
Tsai, H. H., & Tseng, C. Y. (2010). Detecting Solenoid Valve Deterioration in In-Use Electronic Diesel Fuel Injection Control Systems, Sensors, vol. 10 (8), pp. 7157-7169. doi:10.3390/s100807157
Mutschler, K., Dwivedia, S., Kartmanna, S., Bammesbergera, S., Koltaya, P., Zengerle, R., & Tanguy, L. (2014). Multi physics network simulation of a solenoid dispensing valve, Mechatronics, vol. 24, pp. 209-221. doi:10.1016/j.mechatronics.2014.02.005
Rahman, M. F., Cheung, N. C., & Lim, K. W. (1995). A Sensorless Position Estimator for a Nonlinear Solenoid Actuator, Proceedings of the 1995 IEEE IECON 21st International Conference. November 6-10, Orlando, FL. doi:10.1109/IECON.1995.483969
Kreyszig, E. (2006) Advanced Engineering Mathematics, 9th Edition, John Wiley & Sons, Hoboken, NJ, pp. 264-265.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.