The Experts below are selected from a list of 80700 Experts worldwide ranked by ideXlab platform
Pascal Bellemain - One of the best experts on this subject based on the ideXlab platform.
-
Robust Estimation of temperature field during microwave tempering under unknown dielectric properties
2011Co-Authors: Lionel Boillereaux, Mazen Alamir, Sebastien Curet, Olivier Rouaud, Pascal BellemainAbstract:The present study is dedicated to the estimation of internal temperatures within a foodstuff during microwave tempering, in presence of unknown dielectric properties. The solution consists in a Software Sensor based on a model issued from the closed form solutions of Maxwell's equations coupled with the conduction heat equation solved by finite differences. The algorithm implemented permits to converge towards acceptable dielectric properties functions whereas the temperature field is estimated simultaneously. This approach is carried out in simulation by considering the tempering of a block of raw beef located in a rectangular wave guide allowing to consider a fundamental mode with perfectly known electromagnetic conditions.
-
estimation of temperature field during microwave tempering with unknown dielectric properties using clpp a generic user friendly Software Sensor
Innovative Food Science and Emerging Technologies, 2011Co-Authors: Lionel Boillereaux, Mazen Alamir, Sebastien Curet, Olivier Rouaud, Pascal BellemainAbstract:Abstract The present study is dedicated to the estimation of internal temperatures within a foodstuff during microwave tempering, in the presence of unknown dielectric properties. The solution consists of a Software Sensor based on a model originating from the closed-form solutions of Maxwell's equations coupled with the conduction heat equation solved by finite differences. The algorithm implemented enables convergence towards acceptable dielectric property functions while the temperature field is estimated simultaneously. This approach is carried out in simulation by considering the tempering of a block of raw beef located in a rectangular wave guide in order to consider a fundamental mode with perfectly known electromagnetic conditions. Industrial Relevance In the industrial processes, the lack of Sensors constitutes a brake to the design of relevant control strategies. One well-known solution is to implement Software Sensors (also called observers) to estimate online the lacking data. However, such a solution requires a good knowledge of the dynamical model structure and the model parameters. The development of Software Sensors remains nevertheless a difficult task for non specialist in process control. CLPP presented in this submission is particularly well suited to industrial cases, because it permits to estimate with a good accuracy the lacking state variables in the presence of large uncertainties on the parameters' vector. The interest is illustrated on a microwave food tempering process, where dielectric parameters are unknown, and where the available measurements are only surface temperatures.
Lionel Boillereaux - One of the best experts on this subject based on the ideXlab platform.
-
Parameter identification and state estimation of a microalgae dynamical model in sulphur deprived conditions: Global sensitivity analysis, optimization criterion, extended Kalman filter
Canadian Journal of Chemical Engineering, 2014Co-Authors: Moemen Daboussy, Mariana Titica, Lionel BoillereauxAbstract:In this article, a dynamic model describing the growth of the green microalgae Chlamydomonas reinhardtii , under light attenuation and sulphur‐deprived conditions leading to hydrogen production in a photobioreactor is presented. The strong interactions between biological and physical phenomena require complex mathematical expressions with an important number of parameters. This article presents a global identification procedure in three steps using data from batch experiments. First, it includes the application of a sensitivity function analysis, which allows one to determine the parameters having the greatest influence on model outputs. Secondly, the most influential parameters were identified by using the classical least‐squares cost function. This stage is applied to the experimental data collected from a lab‐scale batch photobioreactor. Finally, the implementation of an Extended Kalman Filter estimating the biomass concentration, extracellular and intracellular sulphur concentrations is presented. Thereby, the observer uses on‐line measurements provided by a mass spectrometer measuring the outlet gas composition (O2, CO2). Software Sensor performances and limits are illustrated in simulation and with experimental data.
-
Robust Estimation of temperature field during microwave tempering under unknown dielectric properties
2011Co-Authors: Lionel Boillereaux, Mazen Alamir, Sebastien Curet, Olivier Rouaud, Pascal BellemainAbstract:The present study is dedicated to the estimation of internal temperatures within a foodstuff during microwave tempering, in presence of unknown dielectric properties. The solution consists in a Software Sensor based on a model issued from the closed form solutions of Maxwell's equations coupled with the conduction heat equation solved by finite differences. The algorithm implemented permits to converge towards acceptable dielectric properties functions whereas the temperature field is estimated simultaneously. This approach is carried out in simulation by considering the tempering of a block of raw beef located in a rectangular wave guide allowing to consider a fundamental mode with perfectly known electromagnetic conditions.
-
estimation of temperature field during microwave tempering with unknown dielectric properties using clpp a generic user friendly Software Sensor
Innovative Food Science and Emerging Technologies, 2011Co-Authors: Lionel Boillereaux, Mazen Alamir, Sebastien Curet, Olivier Rouaud, Pascal BellemainAbstract:Abstract The present study is dedicated to the estimation of internal temperatures within a foodstuff during microwave tempering, in the presence of unknown dielectric properties. The solution consists of a Software Sensor based on a model originating from the closed-form solutions of Maxwell's equations coupled with the conduction heat equation solved by finite differences. The algorithm implemented enables convergence towards acceptable dielectric property functions while the temperature field is estimated simultaneously. This approach is carried out in simulation by considering the tempering of a block of raw beef located in a rectangular wave guide in order to consider a fundamental mode with perfectly known electromagnetic conditions. Industrial Relevance In the industrial processes, the lack of Sensors constitutes a brake to the design of relevant control strategies. One well-known solution is to implement Software Sensors (also called observers) to estimate online the lacking data. However, such a solution requires a good knowledge of the dynamical model structure and the model parameters. The development of Software Sensors remains nevertheless a difficult task for non specialist in process control. CLPP presented in this submission is particularly well suited to industrial cases, because it permits to estimate with a good accuracy the lacking state variables in the presence of large uncertainties on the parameters' vector. The interest is illustrated on a microwave food tempering process, where dielectric parameters are unknown, and where the available measurements are only surface temperatures.
Raúl González-garcía - One of the best experts on this subject based on the ideXlab platform.
-
Online monitoring of Mezcal fermentation based on redox potential measurements
Bioprocess and Biosystems Engineering, 2009Co-Authors: Pilar Escalante-minakata, A. De León-rodríguez, V. Ibarra-junquera, H. C. Rosu, Raúl González-garcíaAbstract:We describe an algorithm for the continuous monitoring of the biomass and ethanol concentrations as well as the growth rate in the Mezcal fermentation process. The algorithm performs its task having available only the online measurements of the redox potential. The procedure combines an artificial neural network (ANN) that relates the redox potential to the ethanol and biomass concentrations with a nonlinear observer-based algorithm that uses the ANN biomass estimations to infer the growth rate of this fermentation process. The results show that the redox potential is a valuable indicator of the metabolic activity of the microorganisms during Mezcal fermentation. In addition, the estimated growth rate can be considered as a direct evidence of the presence of mixed culture growth in the process. Usually, mixtures of microorganisms could be intuitively clear in this kind of processes; however, the total biomass data do not provide definite evidence by themselves. In this paper, the detailed design of the Software Sensor as well as its experimental application is presented at the laboratory level.
-
An algorithm for real-time estimation of Mezcal fermentation parameters based on redox potential measurements
arXiv: Quantitative Methods, 2006Co-Authors: Pilar Escalante-minakata, Vrani Ibarra-junquera, Haret Codratian Rosu, A. De León-rodríguez, Raúl González-garcíaAbstract:We present an algorithm for the continuous monitoring of the biomass and ethanol concentrations and moreover the kinetic rate in the Mezcal fermentation process. This algorithm performs its task having only available the on-line measurements of the redox potential. The procedure includes an artificial neural network (ANN) that relates the redox potential to the ethanol and biomass concentrations. Then a nonlinear-observer-based algorithm uses the biomass estimations to infer the kinetic rate of this fermentation process. The method shows that the redox potential is a valuable indicator of microorganism metabolic activity during the Mezcal fermentation. In addition, the estimated kinetic rate can be considered as a direct evidence of the presence of mixed culture growth in the process. In this work, the detailed design of the Software-Sensor is presented, as well as its experimental application at the laboratory level
Sebastien Curet - One of the best experts on this subject based on the ideXlab platform.
-
Robust Estimation of temperature field during microwave tempering under unknown dielectric properties
2011Co-Authors: Lionel Boillereaux, Mazen Alamir, Sebastien Curet, Olivier Rouaud, Pascal BellemainAbstract:The present study is dedicated to the estimation of internal temperatures within a foodstuff during microwave tempering, in presence of unknown dielectric properties. The solution consists in a Software Sensor based on a model issued from the closed form solutions of Maxwell's equations coupled with the conduction heat equation solved by finite differences. The algorithm implemented permits to converge towards acceptable dielectric properties functions whereas the temperature field is estimated simultaneously. This approach is carried out in simulation by considering the tempering of a block of raw beef located in a rectangular wave guide allowing to consider a fundamental mode with perfectly known electromagnetic conditions.
-
estimation of temperature field during microwave tempering with unknown dielectric properties using clpp a generic user friendly Software Sensor
Innovative Food Science and Emerging Technologies, 2011Co-Authors: Lionel Boillereaux, Mazen Alamir, Sebastien Curet, Olivier Rouaud, Pascal BellemainAbstract:Abstract The present study is dedicated to the estimation of internal temperatures within a foodstuff during microwave tempering, in the presence of unknown dielectric properties. The solution consists of a Software Sensor based on a model originating from the closed-form solutions of Maxwell's equations coupled with the conduction heat equation solved by finite differences. The algorithm implemented enables convergence towards acceptable dielectric property functions while the temperature field is estimated simultaneously. This approach is carried out in simulation by considering the tempering of a block of raw beef located in a rectangular wave guide in order to consider a fundamental mode with perfectly known electromagnetic conditions. Industrial Relevance In the industrial processes, the lack of Sensors constitutes a brake to the design of relevant control strategies. One well-known solution is to implement Software Sensors (also called observers) to estimate online the lacking data. However, such a solution requires a good knowledge of the dynamical model structure and the model parameters. The development of Software Sensors remains nevertheless a difficult task for non specialist in process control. CLPP presented in this submission is particularly well suited to industrial cases, because it permits to estimate with a good accuracy the lacking state variables in the presence of large uncertainties on the parameters' vector. The interest is illustrated on a microwave food tempering process, where dielectric parameters are unknown, and where the available measurements are only surface temperatures.
Mazen Alamir - One of the best experts on this subject based on the ideXlab platform.
-
Robust Estimation of temperature field during microwave tempering under unknown dielectric properties
2011Co-Authors: Lionel Boillereaux, Mazen Alamir, Sebastien Curet, Olivier Rouaud, Pascal BellemainAbstract:The present study is dedicated to the estimation of internal temperatures within a foodstuff during microwave tempering, in presence of unknown dielectric properties. The solution consists in a Software Sensor based on a model issued from the closed form solutions of Maxwell's equations coupled with the conduction heat equation solved by finite differences. The algorithm implemented permits to converge towards acceptable dielectric properties functions whereas the temperature field is estimated simultaneously. This approach is carried out in simulation by considering the tempering of a block of raw beef located in a rectangular wave guide allowing to consider a fundamental mode with perfectly known electromagnetic conditions.
-
estimation of temperature field during microwave tempering with unknown dielectric properties using clpp a generic user friendly Software Sensor
Innovative Food Science and Emerging Technologies, 2011Co-Authors: Lionel Boillereaux, Mazen Alamir, Sebastien Curet, Olivier Rouaud, Pascal BellemainAbstract:Abstract The present study is dedicated to the estimation of internal temperatures within a foodstuff during microwave tempering, in the presence of unknown dielectric properties. The solution consists of a Software Sensor based on a model originating from the closed-form solutions of Maxwell's equations coupled with the conduction heat equation solved by finite differences. The algorithm implemented enables convergence towards acceptable dielectric property functions while the temperature field is estimated simultaneously. This approach is carried out in simulation by considering the tempering of a block of raw beef located in a rectangular wave guide in order to consider a fundamental mode with perfectly known electromagnetic conditions. Industrial Relevance In the industrial processes, the lack of Sensors constitutes a brake to the design of relevant control strategies. One well-known solution is to implement Software Sensors (also called observers) to estimate online the lacking data. However, such a solution requires a good knowledge of the dynamical model structure and the model parameters. The development of Software Sensors remains nevertheless a difficult task for non specialist in process control. CLPP presented in this submission is particularly well suited to industrial cases, because it permits to estimate with a good accuracy the lacking state variables in the presence of large uncertainties on the parameters' vector. The interest is illustrated on a microwave food tempering process, where dielectric parameters are unknown, and where the available measurements are only surface temperatures.