Abstract
Fault diagnostic and prognostic methods are the extensive topics of condition-based maintenance system. These publications include a wide range of statistical approaches for model-based approaches. Uncertainty in prediction cannot be avoided; therefore, algorithms are working to help manage these uncertainties. Remaining useful lives (RUL) are regularly updated through adaptive degradation models identified by using the concept of sampling importance resampling (SIR) filter. The SIR filter algorithm has become a popular choice for model-based progressive system. As a matter of study, we consider a hydraulic system and develop a detailed physics-based model and use extensive simulations to describe our prehistoric science approach and to evaluate its effectiveness and strength.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wu W, Hu J, Jing C, Jiang Z, Yuan S (2014) Investigation of energy efficient hydraulic hybrid propulsion system for automobiles. Energy 73:497–505
Lin T, Huang W, Ren H, Fu S, Liu Q (2016) New compound energy regeneration system and control strategy for hybrid hydraulic excavators. Autom Constr 68:11–20
Shi H, Yang H, Gong G, Liu H, Hou D (2014) Energy saving of cutterhead hydraulic drive system of shield tunneling machine. Autom Constr 37:11–21
Kumar S, Das S, Ghoshal SK, Das J (2018) Review of different energy saving strategies applicable to hydraulic hybrid systems used in heavy vehicles. IOP Conf Ser Mater Sci Eng 377(1):012072. (IOP Publishing)
Roychoudhury I, Hafiychuk V, Goebel K (2013) Model-based diagnosis and prognosis of a water recycling system. In: Aerospace conference, IEEE, pp 1–9
Mahulkar V, McGinnis H, Derriso M, Adams DE (2010) Fault identification in an electro-hydraulic actuator and experimental validation of prognosis based life extending control. Air force research lab wright-patterson AFB OH air vehicles directorate
Prakash O, Samantaray AK, Bhattacharyya R, Ghoshal SK (2018) Adaptive prognosis for a multi-component dynamical system of unknown degradation modes. IFAC-PapersOnLine 51(24):184–191
Pandian A, Ali A (2009) A review of recent trends in machine diagnosis and prognosis algorithms. In: 2009 world congress on nature and biologically inspired computing. NaBIC 2009, IEEE, pp 1731–1736
Daigle MJ, Goebel K (2011) A model-based prognostics approach applied to pneumatic valves. Int J Progn Health Manag 2(2):84–99
Acknowledgements
I am grateful to DST project number YSS/2015/000397 “Design and development of series-parallel hydraulic hybrid energy efficient excavator having displacement con-trolled actuators” for providing the setup for doing future research in this field.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Kumar, S., Dutta, S.K., Ghoshal, S.K., Das, J. (2020). Model-Based Adaptive Prognosis of a Hydraulic System. In: Kumar, H., Jain, P. (eds) Recent Advances in Mechanical Engineering. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-1071-7_32
Download citation
DOI: https://doi.org/10.1007/978-981-15-1071-7_32
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-1070-0
Online ISBN: 978-981-15-1071-7
eBook Packages: EngineeringEngineering (R0)