On-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques

Angeli, Chrissanthi; Chatzinikolaou, Avraam

doi:10.20965/jaciii.2008.p0111

Cited by 4 publications

(4 citation statements)

References 15 publications

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“…The D-matrix is used to quickly identify the fault within the ambiguity group and the model based inference can be subsequently applied to disambiguate the fault (Ponizovskaya-Devine et al, 2015a;Ponizovskaya et al, 2015;Kodali et al, 2015). It is known that in general the model-based frameworks can substantially enhance interaction of behavioral knowledge and diagnostic inference (Angeli & Chatzinikolaou, 2004). Our preliminary results confirm this expectation.…”

Section: Application To the Fault Diagnosticssupporting

confidence: 84%

Inferential framework for autonomous cryogenic loading operations

et al. 2017

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We address the problem of autonomous cryogenic management of loading operations on the ground and in space. As a step towards the solution of this problem we develop a probabilistic framework for inferring correlations parameters of two-fluid cryogenic flow. The simulation of two-phase cryogenic flow is performed using nearly-implicit scheme. A concise set of cryogenic correlations is introduced. The proposed approach is applied to an analysis of the cryogenic flow in experimental Propellant Loading System built at NASA Kennedy Space Center. An efficient simultaneous optimization of a large number of model parameters is demonstrated and a good agreement with the experimental data is obtained.

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Section: Application To the Fault Diagnosticssupporting

confidence: 84%

Inferential framework for autonomous cryogenic loading operations

et al. 2017

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“…It is well-known that the model-based frameworks can substantially enhance interaction of behavioral knowledge and diagnostic inference (Angeli & Chatzinikolaou, 2004). A more detailed discussion of the development of the on-line expert system for the IHM of cryogenic transfer will be given elsewhere.…”

Section: Dependency Matrix Of the Cryogenic Chilldownmentioning

confidence: 99%

Fault diagnostics and evaluation in cryogenic loading system using optimization algorithm

et al. 2015

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Physics-based approach to the cryogenic flow health management is presented. It is based on fast and time-accurate physics models of the cryogenic flow in the transfer line. We discuss main features of one of these models – the homogeneous moving front model and presents results of its validation. The main steps of the approach including fault detection, identification, and evaluation are discussed. A few examples of faults are presented. It is shown that dynamic features of the faults naturally form a number of ambiguity groups. A D-matrix approach to optimized identification of these faults is briefly outlined. An example of discerning and evaluating faults within one ambiguity group using optimization algorithm is considered in more details. An application of this approach to the Integrated Health Management of cryogenic loading is discussed.

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“…Comprehensive reviews on FD can be found in the literature: [Isermann 1997, Isermann 2005, Angeli 2004, Venkatasubramanian 2003a, Venkatasubramanian 2003b, Venkatasubramanian 2003c]. Among the diagnosis methods, one can distinguish two categories.…”

Section: Fault Tolerant Systemsmentioning

confidence: 99%

Bond Graph Model Based on Structural Diagnosability and Recoverability Analysis: Application to Intelligent Autonomous Vehicles

Loureiro

Merzouki

Bouamama

2012

IEEE Trans. Veh. Technol.

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It is time to write the acknowledgments. I will do my best. First of all, I would like to show my gratitude towards my supervisors, Mr. Belkacem Ould-Bouamama and Mr. Rochdi Merzouki for providing me with the opportunity to work on this interesting topic. Without whose support, availability, encouragement and fruitful discussions, I would not have achieved the results I obtained in my Ph.D. thesis. It was through his persistence, understanding and kindness that I always worked with enthusiasm. My gratitude also goes towards Mr. Taha Boukhobza and Mr. Eric Bideaux for their availability and interest on reviewing my work. I express to them my deepest appreciation. I also thank Ms. Geneviève Dauphin-Tanguy, Mr. François Charpillet and Mr. Mohamed Djemai for agreeing to be part of the jury of this thesis. Thank you to doctoral and post-doctoral researcher at the Laboratoire d'Automatique, Génie Informatique et Signal (LAGIS). With them, I was able to share the joys and difficulties faced during a Ph.D. thesis. More specifically, I would like to extend very special thanks my office colleagues Samir Benmoussa and Youcef Touati for the helpful discussions and their useful suggestions during these three years.Thank you to all persons who were not mentioned above, but were involved with our work, directly and indirectly.Finally, thanks to my family for the support they provided me through my entire life. I must acknowledge Alice, without whose encouragement and assistance, I would not have worked serenely.

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On-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques

Cited by 4 publications

References 15 publications

Inferential framework for autonomous cryogenic loading operations

Inferential framework for autonomous cryogenic loading operations

Fault diagnostics and evaluation in cryogenic loading system using optimization algorithm

Bond Graph Model Based on Structural Diagnosability and Recoverability Analysis: Application to Intelligent Autonomous Vehicles

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