A comparative study between a set of chosen machine learning tools for direct remaining useful life prediction is presented in this work. The main objective of this study is to select the appropriate prediction tool for health estimation of aircraft engines for future uses. The training algorithms are evaluated using “time-varying” data retrieved from Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) developed by NASA. The training and testing processes of each algorithm are carried out under the same circumstances using the similar initial condition and evaluation sets. The results prove that among the studied training tools, Support vector machine (SVM) achieved the best results.

A comparative study between a set of chosen machine learning tools for direct remaining useful life prediction is presented in this work. The main objective of this study is to select the appropriate prediction tool for health estimation of aircraft engines for future uses. The training algorithms are evaluated using “time-varying” data retrieved from Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) developed by NASA. The training and testing processes of each algorithm are carried out under the same circumstances using the similar initial condition and evaluation sets. The results prove that among the studied training tools, Support vector machine (SVM) achieved the best results.

A comparative study between a set of chosen machine learning tools for direct remaining useful life prediction is presented in this work. The main objective of this study is to select the appropriate prediction tool for health estimation of aircraft engines for future uses. The training algorithms are evaluated using “time-varying” data retrieved from Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) developed by NASA. The training and testing processes of each algorithm are carried out under the same circumstances using the similar initial condition and evaluation sets. The results prove that among the studied training tools, Support vector machine (SVM) achieved the best results.

A comparative study between a set of chosen machine learning tools for direct remaining useful life prediction is presented in this work. The main objective of this study is to select the appropriate prediction tool for health estimation of aircraft engines for future uses. The training algorithms are evaluated using “time-varying” data retrieved from Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) developed by NASA. The training and testing processes of each algorithm are carried out under the same circumstances using the similar initial condition and evaluation sets. The results prove that among the studied training tools, Support vector machine (SVM) achieved the best results.

: In this paper, we have studied a different fault tolerant control (FTC) strategies for a three-phase induction motor (3p-IM). Further we introduce Backstepping controller (BC) and Input-output linearization controller (IOLC). To provide a direct comparison between these FTCs approaches, the performances are evaluated using the control of 3p-IM under failures, variable speed, and variable parameters. A comparison between the two control strategies is proposed to prove the most robust one. The simulation results show the robustness and good performance of the fault tolerant control with Input-output linearization controller compared to one with Backstepping controller. The FTC with IOLC is more stable and robust against failures, load torque perturbation and speed reversion

: In this paper, we have studied a different fault tolerant control (FTC) strategies for a three-phase induction motor (3p-IM). Further we introduce Backstepping controller (BC) and Input-output linearization controller (IOLC). To provide a direct comparison between these FTCs approaches, the performances are evaluated using the control of 3p-IM under failures, variable speed, and variable parameters. A comparison between the two control strategies is proposed to prove the most robust one. The simulation results show the robustness and good performance of the fault tolerant control with Input-output linearization controller compared to one with Backstepping controller. The FTC with IOLC is more stable and robust against failures, load torque perturbation and speed reversion

: In this paper, we have studied a different fault tolerant control (FTC) strategies for a three-phase induction motor (3p-IM). Further we introduce Backstepping controller (BC) and Input-output linearization controller (IOLC). To provide a direct comparison between these FTCs approaches, the performances are evaluated using the control of 3p-IM under failures, variable speed, and variable parameters. A comparison between the two control strategies is proposed to prove the most robust one. The simulation results show the robustness and good performance of the fault tolerant control with Input-output linearization controller compared to one with Backstepping controller. The FTC with IOLC is more stable and robust against failures, load torque perturbation and speed reversion

The current paper illustrates the numerical study of the global combustion parameters. It mainly focused on the computational analysis that investigated the non-premixed combustion in the cylindrical burner. Therefore, we selected many fuels to supply the burner like Algerian biogas, CH₄, C3H₈, H2, natural gas, and diesel to compare their aerothermochemical characteristics variables. At first, we applied the numerical methods that confirm the solution convergence like combustion models and grid selection. After that, we resolved the aerothermochemical set equations of combustion using the coupled k-ɛɛ turbulent dynamic model with the probability density function approach. These models are also used to surmount the closer in the set of combustion equations too. Moreover, we integrated the pollutant computation model based on the chemical reactions of NO production. Thus, we evaluated each considered fuel’s NO emission during all combustion fuels cases. Accordingly, the results show that Algerian biogas and hydrogen have special characteristics compared to other cases of fuels. The most prominent characteristics are: the high level of the mixture and burn relative to other fuels, their low pollutants emissions (CO and NO), and the proportional relationship between the OH and NO production. Consequently, biogas and H2 conserve the impact on energy and the environment.

The current paper illustrates the numerical study of the global combustion parameters. It mainly focused on the computational analysis that investigated the non-premixed combustion in the cylindrical burner. Therefore, we selected many fuels to supply the burner like Algerian biogas, CH₄, C3H₈, H2, natural gas, and diesel to compare their aerothermochemical characteristics variables. At first, we applied the numerical methods that confirm the solution convergence like combustion models and grid selection. After that, we resolved the aerothermochemical set equations of combustion using the coupled k-ɛɛ turbulent dynamic model with the probability density function approach. These models are also used to surmount the closer in the set of combustion equations too. Moreover, we integrated the pollutant computation model based on the chemical reactions of NO production. Thus, we evaluated each considered fuel’s NO emission during all combustion fuels cases. Accordingly, the results show that Algerian biogas and hydrogen have special characteristics compared to other cases of fuels. The most prominent characteristics are: the high level of the mixture and burn relative to other fuels, their low pollutants emissions (CO and NO), and the proportional relationship between the OH and NO production. Consequently, biogas and H2 conserve the impact on energy and the environment.

The current paper illustrates the numerical study of the global combustion parameters. It mainly focused on the computational analysis that investigated the non-premixed combustion in the cylindrical burner. Therefore, we selected many fuels to supply the burner like Algerian biogas, CH₄, C3H₈, H2, natural gas, and diesel to compare their aerothermochemical characteristics variables. At first, we applied the numerical methods that confirm the solution convergence like combustion models and grid selection. After that, we resolved the aerothermochemical set equations of combustion using the coupled k-ɛɛ turbulent dynamic model with the probability density function approach. These models are also used to surmount the closer in the set of combustion equations too. Moreover, we integrated the pollutant computation model based on the chemical reactions of NO production. Thus, we evaluated each considered fuel’s NO emission during all combustion fuels cases. Accordingly, the results show that Algerian biogas and hydrogen have special characteristics compared to other cases of fuels. The most prominent characteristics are: the high level of the mixture and burn relative to other fuels, their low pollutants emissions (CO and NO), and the proportional relationship between the OH and NO production. Consequently, biogas and H2 conserve the impact on energy and the environment.

The current paper illustrates the numerical study of the global combustion parameters. It mainly focused on the computational analysis that investigated the non-premixed combustion in the cylindrical burner. Therefore, we selected many fuels to supply the burner like Algerian biogas, CH₄, C3H₈, H2, natural gas, and diesel to compare their aerothermochemical characteristics variables. At first, we applied the numerical methods that confirm the solution convergence like combustion models and grid selection. After that, we resolved the aerothermochemical set equations of combustion using the coupled k-ɛɛ turbulent dynamic model with the probability density function approach. These models are also used to surmount the closer in the set of combustion equations too. Moreover, we integrated the pollutant computation model based on the chemical reactions of NO production. Thus, we evaluated each considered fuel’s NO emission during all combustion fuels cases. Accordingly, the results show that Algerian biogas and hydrogen have special characteristics compared to other cases of fuels. The most prominent characteristics are: the high level of the mixture and burn relative to other fuels, their low pollutants emissions (CO and NO), and the proportional relationship between the OH and NO production. Consequently, biogas and H2 conserve the impact on energy and the environment.

The current paper illustrates the numerical study of the global combustion parameters. It mainly focused on the computational analysis that investigated the non-premixed combustion in the cylindrical burner. Therefore, we selected many fuels to supply the burner like Algerian biogas, CH₄, C3H₈, H2, natural gas, and diesel to compare their aerothermochemical characteristics variables. At first, we applied the numerical methods that confirm the solution convergence like combustion models and grid selection. After that, we resolved the aerothermochemical set equations of combustion using the coupled k-ɛɛ turbulent dynamic model with the probability density function approach. These models are also used to surmount the closer in the set of combustion equations too. Moreover, we integrated the pollutant computation model based on the chemical reactions of NO production. Thus, we evaluated each considered fuel’s NO emission during all combustion fuels cases. Accordingly, the results show that Algerian biogas and hydrogen have special characteristics compared to other cases of fuels. The most prominent characteristics are: the high level of the mixture and burn relative to other fuels, their low pollutants emissions (CO and NO), and the proportional relationship between the OH and NO production. Consequently, biogas and H2 conserve the impact on energy and the environment.

The current paper illustrates the numerical study of the global combustion parameters. It mainly focused on the computational analysis that investigated the non-premixed combustion in the cylindrical burner. Therefore, we selected many fuels to supply the burner like Algerian biogas, CH₄, C3H₈, H2, natural gas, and diesel to compare their aerothermochemical characteristics variables. At first, we applied the numerical methods that confirm the solution convergence like combustion models and grid selection. After that, we resolved the aerothermochemical set equations of combustion using the coupled k-ɛɛ turbulent dynamic model with the probability density function approach. These models are also used to surmount the closer in the set of combustion equations too. Moreover, we integrated the pollutant computation model based on the chemical reactions of NO production. Thus, we evaluated each considered fuel’s NO emission during all combustion fuels cases. Accordingly, the results show that Algerian biogas and hydrogen have special characteristics compared to other cases of fuels. The most prominent characteristics are: the high level of the mixture and burn relative to other fuels, their low pollutants emissions (CO and NO), and the proportional relationship between the OH and NO production. Consequently, biogas and H2 conserve the impact on energy and the environment.

In this paper, we consider a time-fractional reaction-diffusion system with the same nonlinearities of the Newton-Leipnik chaotic system. Through analytical tools and numerical results, we derive sufficient conditions for the asymptotic stability of the proposed model and show the existence of chaos. We also propose a nonlinear synchronization controller for a pair of systems and establish the local and global asymptotic convergence of the trajectories by means of fractional stability theory and the Lyapunov method.

In this paper, we consider a time-fractional reaction-diffusion system with the same nonlinearities of the Newton-Leipnik chaotic system. Through analytical tools and numerical results, we derive sufficient conditions for the asymptotic stability of the proposed model and show the existence of chaos. We also propose a nonlinear synchronization controller for a pair of systems and establish the local and global asymptotic convergence of the trajectories by means of fractional stability theory and the Lyapunov method.

In this paper, we consider a time-fractional reaction-diffusion system with the same nonlinearities of the Newton-Leipnik chaotic system. Through analytical tools and numerical results, we derive sufficient conditions for the asymptotic stability of the proposed model and show the existence of chaos. We also propose a nonlinear synchronization controller for a pair of systems and establish the local and global asymptotic convergence of the trajectories by means of fractional stability theory and the Lyapunov method.

In this paper, we consider a time-fractional reaction-diffusion system with the same nonlinearities of the Newton-Leipnik chaotic system. Through analytical tools and numerical results, we derive sufficient conditions for the asymptotic stability of the proposed model and show the existence of chaos. We also propose a nonlinear synchronization controller for a pair of systems and establish the local and global asymptotic convergence of the trajectories by means of fractional stability theory and the Lyapunov method.

In the industry, automated inspection is important for ensuring the high quality and allows acceleration of procedures for quality control of parts or mechanical assemblies. Although significant progress has been made in precision machining of complex surfaces, precision inspection of such surfaces remains a difficult problem. Thus the problem of the conformity of the parts of complex geometry is felt more and more. Motivated by the need to increase quality and reduce costs, and supported by the progress made in the field of it as well as the automation of production which in recent years has seen a considerable evolution in all these stages: from design to control through manufacturing. Due to, we used a 3D computer aided inspection technique on a physical gear using a coordinate measuring machine equipped with a “PC-DMIS” measurement and inspection software. Our work consists in developing a procedure for inspection for reproduction of gear profile by reconstruction of a circle involute gear from a cloud point’s measurement. In order to obtain a reliable result. In this works, we design the CAD-model of the part as accurately as possible (using a mathematical model) and matched with the 3D points cloud that represents the measurement that obtained from scanner. we compare the measurement cloud points from coordinate measurement machine with the mathematical model of construction by ICP (Iterative Closest Point) methods in order to obtain a conformed result and to show the impact of the dimensional inspection and geometric.

In the industry, automated inspection is important for ensuring the high quality and allows acceleration of procedures for quality control of parts or mechanical assemblies. Although significant progress has been made in precision machining of complex surfaces, precision inspection of such surfaces remains a difficult problem. Thus the problem of the conformity of the parts of complex geometry is felt more and more. Motivated by the need to increase quality and reduce costs, and supported by the progress made in the field of it as well as the automation of production which in recent years has seen a considerable evolution in all these stages: from design to control through manufacturing. Due to, we used a 3D computer aided inspection technique on a physical gear using a coordinate measuring machine equipped with a “PC-DMIS” measurement and inspection software. Our work consists in developing a procedure for inspection for reproduction of gear profile by reconstruction of a circle involute gear from a cloud point’s measurement. In order to obtain a reliable result. In this works, we design the CAD-model of the part as accurately as possible (using a mathematical model) and matched with the 3D points cloud that represents the measurement that obtained from scanner. we compare the measurement cloud points from coordinate measurement machine with the mathematical model of construction by ICP (Iterative Closest Point) methods in order to obtain a conformed result and to show the impact of the dimensional inspection and geometric.

In the industry, automated inspection is important for ensuring the high quality and allows acceleration of procedures for quality control of parts or mechanical assemblies. Although significant progress has been made in precision machining of complex surfaces, precision inspection of such surfaces remains a difficult problem. Thus the problem of the conformity of the parts of complex geometry is felt more and more. Motivated by the need to increase quality and reduce costs, and supported by the progress made in the field of it as well as the automation of production which in recent years has seen a considerable evolution in all these stages: from design to control through manufacturing. Due to, we used a 3D computer aided inspection technique on a physical gear using a coordinate measuring machine equipped with a “PC-DMIS” measurement and inspection software. Our work consists in developing a procedure for inspection for reproduction of gear profile by reconstruction of a circle involute gear from a cloud point’s measurement. In order to obtain a reliable result. In this works, we design the CAD-model of the part as accurately as possible (using a mathematical model) and matched with the 3D points cloud that represents the measurement that obtained from scanner. we compare the measurement cloud points from coordinate measurement machine with the mathematical model of construction by ICP (Iterative Closest Point) methods in order to obtain a conformed result and to show the impact of the dimensional inspection and geometric.