References of "Léonard, Olivier"
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See detailA Quadratic Programming Framework for Constrained and Robust Jet Engine
Borguet, Sébastien ULg; Léonard, Olivier ULg

in EUCASS Advances in Aerospace Sciences : Propulsion Physics (2009)

Kalman filters are largely used in the jet engine community for condition monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the residuals between the model ... [more ▼]

Kalman filters are largely used in the jet engine community for condition monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the residuals between the model prediction and the measurements are zero-mean, Gaussian random variables. In the case of sensor faults, this assumption does not hold anymore and consequently the diagnosis is spoiled. This contribution presents a recursive estimation algorithm based on a Quadratic Programming formulation which provides robustness against sensor faults and allows constraints on the health parameters to be specified. The improvements in estimation accuracy brought by this new algorithm are illustrated by a series of typical test-cases that may be encountered on current turbofan engines. [less ▲]

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See detailToward Less Empiricism in Throughflow Calculations
Léonard, Olivier ULg

Scientific conference (2008, August 19)

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See detailAdaptive estimation algorithm for aircraft engine performance monitoring
Léonard, Olivier ULg; Borguet, Sébastien ULg; Dewallef, Pierre ULg

in Journal of Propulsion and Power (2008), 24(4), 763-769

In the frame of turbine engine performance monitoring, system identification procedures are often used to adapt a simulation model of the engine to some observed data through a set of so-called health ... [more ▼]

In the frame of turbine engine performance monitoring, system identification procedures are often used to adapt a simulation model of the engine to some observed data through a set of so-called health parameters. Doing so, the values of these health parameters are intended to represent the actual health condition of the engine. The Kalman filter has been widely used to achieve the identification procedure in real-time onboard applications. However, to achieve a proper filtering of the measurement noise, the health parameters are often assumed to vary in time relatively slowly, preventing any abrupt accidental events from being tracked effectively. This contribution presents a procedure called adaptive filtering. Based on a covariance-matching method, it is intended to automatically release the health parameters once an accidental event is detected. This enables the Kalman filter to deal with both continuous and abrupt fault conditions. [less ▲]

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See detailOn the Role of the Deterministic and Circumferential Stresses in Throughflow Calculations
Simon, Jean-Francois; Léonard, Olivier ULg

in Proceedings of the ASME Turbo Expo 2008 (2008, June)

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See detailInvestigating Circumferential Non-Uniformities in Throughflow Calculations using an Harmonic Reconstruction
Thomas, Jean-Philippe ULg; Léonard, Olivier ULg

in Proceedings of the ASME Turbo Expo 2008 (2008, June)

The flow field in a multistage turbomachine is very complex. It is 3D, unsteady and turbulent. Even if modern simulation tools can describe most of the flow features, the computation time needed and the ... [more ▼]

The flow field in a multistage turbomachine is very complex. It is 3D, unsteady and turbulent. Even if modern simulation tools can describe most of the flow features, the computation time needed and the extraction of useful information remain severe drawbacks to systematic use of URANS codes in a design procedure. In this context the throughflow simulation proved to be more convenient. Nevertheless the need for empiricism limits the potential of throughflow solvers. As an alternative, Admaczyck (1984) proposed three averaging operators (ensemble, time and passage) that lead to the average-passage model, linking the unsteady turbulent flow field to a steady flow field in a typical blade passage. This model involves additional terms that respectively bring back the mean effect of turbulence, deterministic unsteadiness and aperiodicity on the mean periodic flow. These terms need to be modelled; it is the closure problem. Harmonic closure, which consists in solving a linearized perturbation system in the frequency domain, revealed to be an efficient method to approximate deterministic stresses (He and Ning, 1998, Stridh, 2005, Vilmin, 2006). A fourth averaging can be performed, a circumferential averaging, giving rise to the throughflow model. Additional terms appear: the so-called circumferential stresses. It has been proven that these terms play an important role in the description of the flow (Jennions, 1986, Perrin, 1995), being at least as considerable as deterministic stresses. Introducing these terms in a throughflow simulation allows to reproduce the averaged 3D steady flow field (Simon, 2007). The aim of the present contribution is to prove that harmonic method can potentially be used to reconstruct circumferential stresses. The importance of circumferential stresses in a throughflow simulation is first highlighted on a single stage low speed compressor testcase, for viscous and non-viscous flow fields. The second step is the characterization of the frequency spectrum of the circumferential perturbation field. Next are compared the stresses associated to a Fourier reconstruction of the perturbation field with the real ones. Finally the approximated circumferential stresses are injected into a throughflow simulation tool to analyse and demonstrate their capability to reproduce a 3D averaged flow field. [less ▲]

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See detailA hybrid optimization technique coupling evolutionary and local search algorithms
Kelner, Vincent ULg; Capitanescu, Florin ULg; Léonard, Olivier ULg et al

in Journal of Computational & Applied Mathematics (2008), 215(2), 448-456

Evolutionary Algorithms are robust and powerful global optimization techniques for solving large scale problems that have many local optima. However, they require high CPU times, and they are very poor in ... [more ▼]

Evolutionary Algorithms are robust and powerful global optimization techniques for solving large scale problems that have many local optima. However, they require high CPU times, and they are very poor in terms of convergence performance. On the other hand, local search algorithms can converge in a few iterations but lack a global perspective. The combination of global and local search procedures should offer the advantages of both optimization methods while offsetting their disadvantages. This paper proposes a new hybrid optimization technique that merges a Genetic Algorithm with a local search strategy based on the Interior Point method. The efficiency of this hybrid approach is demonstrated by solving a constrained multi-objective mathematical test-case. [less ▲]

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See detailA way to deal with model-plant mismatch for a reliable diagnosis in transient operation
Borguet, Sébastien ULg; Dewallef, Pierre ULg; Léonard, Olivier ULg

in Journal of Engineering for Gas Turbines & Power (2008), 130(3),

Least-squares health parameter identification techniques, such as the Kalman filter, have been extensively used to solve diagnosis problems. Indeed, such methods give a good estimate provided that the ... [more ▼]

Least-squares health parameter identification techniques, such as the Kalman filter, have been extensively used to solve diagnosis problems. Indeed, such methods give a good estimate provided that the discrepancies between the model prediction and the measurements are Zero-mean, white, Gaussian random variables. In a turbine engine diagnosis, however this assumption does not always hold due to the presence of biases in the model. This is especially true for a transient operation. As a result, the estimated parameters tend to diverge from their actual values, which strongly degrades the diagnosis. The purpose of this contribution is to present a Kalman filter diagnosis tool where the model biases are treated as an additional random measurement error. The new methodology is tested on simulated transient data representative of a current turbofan engine configuration. While relatively simple to implement, the newly developed diagnosis tool exhibits a much better accuracy than the original Kalman filter in the presence of model biases. [less ▲]

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See detailThe Fisher Information Matrix as a Relevant Tool for Sensor Selection in Engine Health Monitoring
Borguet, Sébastien ULg; Léonard, Olivier ULg

in International Journal of Rotating Machinery (2008), 2008

Engine health monitoring has been an area of intensive research for many years. Numerous methods have been developed with the goal of determining a faithful picture of the engine condition. On the other ... [more ▼]

Engine health monitoring has been an area of intensive research for many years. Numerous methods have been developed with the goal of determining a faithful picture of the engine condition. On the other hand, the issue of sensor selection allowing an efficient diagnosis has received less attention from the community. The present contribution revisits the problem of sensor selection for engine performance monitoring within the scope of information theory. To this end, a metric that integrates the essential elements of the sensor selection problem is defined from the Fisher information matrix. An example application consisting in a commercial turbofan engine illustrates the enhancement that can be expected from a wise selection of the sensor set. [less ▲]

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See detailA quasi-one-dimensional CFD model for multistage turbomachines
Léonard, Olivier ULg; Adam, Olivier

in Journal Of Thermal Science (2008), 17(1), 7-20

The objective of this paper is to present a fast and reliable CFD model that is able to simulate stationary and transient operations of multistage compressors and turbines. This analysis tool is based on ... [more ▼]

The objective of this paper is to present a fast and reliable CFD model that is able to simulate stationary and transient operations of multistage compressors and turbines. This analysis tool is based on an adapted version of the Euler equations solved by a time-marching, finite-volume method. The Euler equations have been extended by including source terms expressing the blade-flow interactions. These source terms are determined using the velocity triangles and a row-by-row representation of the blading at mid-span. The losses and deviations undergone by the fluid across each blade row are supplied by correlations. The resulting flow solver is a performance prediction tool based only on the machine geometry, offering the possibility of exploring the entire characteristic map of a multistage compressor or turbine. Its efficiency in terms of CPU time makes it possible to couple it to an optimization algorithm or to a gas turbine performance tool. Different test-cases are presented for which the calculated characteristic maps are compared to experimental ones. [less ▲]

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See detailA Study on Observability and Sensor Selection for Efficient Jet Engine Health Monitoring
Borguet, Sébastien ULg; Léonard, Olivier ULg

in Proceedings of ISROMAC-12 (2008, February)

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See detailComparison of Adaptive Filtering Schemes for Gas Turbine Performance Diagnostics
Borguet, Sébastien ULg; Léonard, Olivier ULg

in Proceedings of the 4th International Conference on Advanced Computational Methods in Engineering (2008)

Kalman filters are widely used in the turbine engine community for health monitoring purpose. This algorithm has proven its capability to track gradual deterioration with a good accuracy. On the other ... [more ▼]

Kalman filters are widely used in the turbine engine community for health monitoring purpose. This algorithm has proven its capability to track gradual deterioration with a good accuracy. On the other hand, its response to rapid deterioration is either a long delay in recognising the fault, and/or a spread of the estimated fault on several components. The main reason of this deficiency lies in the transition model of the parameters that assumes a smooth evolution of the engine condition. The aim of this contribution is to compare two adaptive diagnosis tools that combine a Kalman filter and a secondary system that monitors the residuals. This auxiliary component implements on one hand a covariance matching scheme and on the other hand a generalised likelihood ratio test to improve the behaviour of the diagnosis tool with respect to abrupt faults. [less ▲]

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See detailA sensor-fault-tolerant diagnosis tool based on a quadratic programming approach
Borguet, Sébastien ULg; Léonard, Olivier ULg

in Journal of Engineering for Gas Turbines & Power (2008), 130(2),

Kalman filters are widely used in the turbine engine community for health monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the discrepancies between the model ... [more ▼]

Kalman filters are widely used in the turbine engine community for health monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the discrepancies between the model prediction and the measurements are Zero-mean, white random variables. However this assumption is not verified when instrumentation (sensor) faults occur As a result, the identified health parameters tend to diverge from their actual values, which strongly deteriorates the diagnosis. The purpose of this contribution is to blend robustness against sensor faults into a tool for performance monitoring of jet engines. To this end, a robust estimation approach is considered and a sensor-fault detection and isolation module is derived. It relies on a quadratic program to estimate the sensor faults and is integrated easily with the original diagnosis tool. The improvements brought by this robust estimation approach are highlighted through a series of typical test cases that may be encountered on current turbine engines. [less ▲]

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See detailModeling of 3-D losses and deviations in a throughflow analysis tool
Simon, Jean-Francois; Léonard, Olivier ULg

in Journal Of Thermal Science (2007), 16(3), 208-214

This contribution is dedicated to the modeling of the end-wall flows in a throughflow model for turbomachinery applications. The throughflow model is based on the Euler or Navier-Stokes equations solved ... [more ▼]

This contribution is dedicated to the modeling of the end-wall flows in a throughflow model for turbomachinery applications. The throughflow model is based on the Euler or Navier-Stokes equations solved by a Finite-Volume technique. Two approaches are presented for the end-wall modeling. The first one is based on an inviscid formulation with dedicated 3-D distributions of loss coefficient and deviation in the end-wall regions. The second approach is directly based on a viscous formulation with no-slip boundary condition along the annular end-walls and blade force modification in the region close to the end-walls. The throughflow results are compared to a series of 3-D Navier-Stokes calculations averaged in the circumferential direction. These 3-D calculations were performed on the three rotors of a low pressure axial compressor, for a series of tip clearance values. [less ▲]

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See detailA Quasi-One Dimensiona Model for Axial Turbines
Adam, Olivier; Léonard, Olivier ULg

in Proceedings of the 18th ISABE Conference (2007, September)

An axial turbine model is presented that is intended to predict its aerodynamic performance based only on the turbine geometry and thermodynamic environment. The model is an extension of an existing quasi ... [more ▼]

An axial turbine model is presented that is intended to predict its aerodynamic performance based only on the turbine geometry and thermodynamic environment. The model is an extension of an existing quasi-1D compressor representation. The simulation tool is able to compute the flow through a whole multistage turbine, with detail at the blade row level. It relies upon a quasi-one dimensional Euler system of equations, expressed here in curvilinear coordinates, and resulting from the application of mass, momentum and energy conservation principles in finite-volume formalism. The source terms expressing the interactions between the flow, the blades and the flowpath are determined using the velocity triangles for each blade row, at mid-span. The solver performs an elaborate implicit time-marching resolution of the equations. The enthalpy loss coefficients as well as the blade outlet flow angles are evaluated through open literature correlations. An efficient representation of the Craig-Cox loss coefficients and the Ainley-Mathieson outlet flow angle correlation brings the necessary empirical information for the velocity triangle computations. The computer code was validated against a high pressure turbine test case featuring multiple cooling flows. The results show the good capabilities of the turbine model using only standard correlations. The computed efficiency also shows the need to model the cooling losses. The low speed, low expansion rate results may finally indicate that the code accuracy would benefit from a correlation parametric identification such as the one led in the compressor case. [less ▲]

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See detailCoupling Principle Component Analysis and Kalman Filtering Algorithms for On-Line Aircraft Engine Diagnostics
Borguet, Sébastien ULg; Léonard, Olivier ULg

in Proceedings of the 18th ISABE Conference (2007, September)

Engine health monitoring has been an area of intensive research for more than three decades. Numerous methods have been developed with the goal of determining a faithful picture of the engine condition ... [more ▼]

Engine health monitoring has been an area of intensive research for more than three decades. Numerous methods have been developed with the goal of determining a faithful picture of the engine condition. It becomes largely admitted that a practical implementation of a monitoring tool will rely on an adequate fusion of some techniques. In this framework, the present contribution proposes an original approach for coupling two diagnosis tools in order to enhance the capability of an engine health monitoring system. One tool is based on a Principal Component Analysis scheme and the other one on a Kalman filter technique. The three methodologies are compared and the benefit of the fused tool is demonstrated on simulated fault cases which can be expected on a current turbofan layout. [less ▲]

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See detailModeling of 3-D losses and deviations in a throughflow analysis tool
Simon, Jean-Francois; Nicks, Alain; Paris, Nicolas et al

in Proceedings of the 8th International Symposium for Experimental and Computational Aerothermodynamics of Internal Flow (2007, July)

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See detailOn Inverse Problems in Turbine Engine Parameter Estimation
Henriksson, Mattias; Borguet, Sébastien ULg; Léonard, Olivier ULg et al

in Proceedings of the ASME Turbo Expo 2007 (2007, May)

This paper extends previous work on model order reduction based on singular value decomposition. It is shown how the decrease in estimator variance must be balanced against the bias on the estimate ... [more ▼]

This paper extends previous work on model order reduction based on singular value decomposition. It is shown how the decrease in estimator variance must be balanced against the bias on the estimate inevitably introduced by solving the inverse problem in a reduced order space. A proof for the decrease in estimator variance by means of multi-point analysis is provided. The proof relies on comparing the Cramer-Rao lower bound of the single point and the multi-point estimators. Model order selection is discussed in the presence of a varying degree of a priori parameter information, through the use of a regularization parameter. Simulation results on the SR-30 turbojet engine indicate that the theoretically attainable multi-point improvements are difficult to realize in practical jet engine applications. [less ▲]

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See detailA Sensor-Fault-Tolerant Diagnosis Tool Based on a Quadratic Programming Approach
Borguet, Sébastien ULg; Léonard, Olivier ULg

in Proceedings of the ASME Turbo Expo 2007 (2007, May)

Kalman filters are widely used in the turbine engine community for health monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the discrepancies between the model ... [more ▼]

Kalman filters are widely used in the turbine engine community for health monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the discrepancies between the model prediction and the measurements are zeromean, white random variables. However, this assumption is not verified when instrumentation (sensor) faults occur. As a result, the identified health parameters tend to diverge from their actual values which strongly deteriorates the diagnosis. The purpose of this contribution is to blend robustness against sensor faults into a tool for performance monitoring of jet engines. To this end, a robust estimation approach is considered and a Sensor Fault Detection and Isolation module is derived. It relies on a quadratic program to estimate the sensor faults and is integrated easily with the original diagnosis tool. The improvements brought by this robust estimation approach are highlighted through a series of typical test-cases that may be encountered on current turbine engines. [less ▲]

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See detailA Quadratic Programming Framework for Constrained and Robust Jet Engine Health Monitiring
Borguet, Sébastien ULg; Léonard, Olivier ULg

in Proceedings of the 2nd European Conference on Aerospace Sciences (2007)

Kalman filters are largely used in the jet engine community for condition monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the residuals between the model ... [more ▼]

Kalman filters are largely used in the jet engine community for condition monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the residuals between the model prediction and the measurements are zero-mean, Gaussian random variables. In the case of sensor faults, this assumption does not hold anymore and consequently the diagnosis is spoiled. This contribution presents a recursive estimation algorithm based on a Quadratic Programming formulation which provides robustness against sensor faults and allows constraints on the health parameters to be specified. The improvements in estimation accuracy brought by this new algorithm are illustrated by a series of typical test-cases that may be encountered on current turbofan engines. [less ▲]

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See detailA Way to Deal with Model-Plant Mismatch for a Reliable Diagnosis in Transient Operation
Borguet, Sébastien ULg; Dewallef, Pierre ULg; Léonard, Olivier ULg

in Proceedings of the ASME Turbo Expo 2006 (2006, May)

Least-squares health parameter identification techniques such as the Kalman filter have been massively used to solve the problem of turbine engine diagnosis. Indeed, such methods give a good estimate ... [more ▼]

Least-squares health parameter identification techniques such as the Kalman filter have been massively used to solve the problem of turbine engine diagnosis. Indeed, such methods give a good estimate provided that the discrepancies between the model prediction and the measurements are zero-mean, white random variables. In turbine engine diagnosis, however, this assumption does not always hold due to the presence of biases in the model. This is especially true for transient operation. As a result, the estimated parameters tend to diverge from their actual values which strongly deteriorates the diagnosis. The purpose of this contribution is to present a Kalman filter diagnosis tool where the model biases are treated as an additional random measurement error. The new methodology is tested on simulated transient data representative of a current turbofan layout. While relatively simple to implement, the newly developed diagnosis tool exhibits a much better accuracy than the original Kalman filter in the presence of model biases. [less ▲]

Detailed reference viewed: 26 (2 ULg)