Non-Linear Engine Component Fault Diagnosis From a Limited Number of Measurements Using a Combinatorial Approach

2002 ◽  
Author(s):  
N. Aretakis ◽  
K. Mathioudakis ◽  
A. Stamatis
Keyword(s):  
Selection Procedure ◽  
Combinatorial Approach ◽  
Jet Engines ◽  
Turbofan Engine ◽  
Engine Simulation ◽  
Health Indices ◽  
Non Linear ◽  
Faulty Component ◽  
Component Faults

A method for diagnosing component faults of jet engines is presented. It uses non-linear gas path analysis techniques to determine the values of health parameters, with the help of a suitably formulated engine simulation model. The incentive of the method is to achieve the determination of the values of component health indices when a limited number of measured quantities is available, which do not allow the determination of all the fault indices simultaneously. A combinatorial approach is introduced, in order to circumvent the problem of the insufficient information for determining a full set of indices. After obtaining a set of possible solutions, a selection procedure is applied to isolate the ones that can give the actual fault identity. Quantification of the fault comes at a final step, when the faulty component has been identified. Different scenarios of faults on a twin spool partially mixed turbofan engine are considered in order to demonstrate the effectiveness of the method. The limitations of the method are also discussed.

Nonlinear Engine Component Fault Diagnosis From a Limited Number of Measurements Using a Combinatorial Approach

2003 ◽  
Vol 125 (3) ◽  
pp. 642-650 ◽  
Author(s):  
N. Aretakis ◽  
K. Mathioudakis ◽  
A. Stamatis
Keyword(s):  
Selection Procedure ◽  
Combinatorial Approach ◽  
Jet Engines ◽  
Turbofan Engine ◽  
Analysis Techniques ◽  
Engine Simulation ◽  
Health Indices ◽  
Faulty Component ◽  
Component Faults

A method for diagnosing component faults of jet engines is presented. It uses nonlinear gas path analysis techniques to determine the values of health parameters, with the help of a suitably formulated engine simulation model. The incentive of the method is to achieve the determination of the values of component health indices when a limited number of measured quantities is available, which do not allow the determination of all the fault indices simultaneously. A combinatorial approach is introduced, in order to circumvent the problem of the insufficient information for determining a full set of indices. After obtaining a set of possible solutions, a selection procedure is applied to isolate the ones that can give the actual fault identity. Quantification of the fault comes at a final step, when the faulty component has been identified. Different scenarios of faults on a twin spool partially mixed turbofan engine are considered in order to demonstrate the effectiveness of the method. The limitations of the method are also discussed.

scholarly journals Benchmarking Gas Path Diagnostic Methods: A Public Approach

2008 ◽  
Author(s):  
Donald L. Simon ◽  
Jeff Bird ◽  
Craig Davison ◽  
Al Volponi ◽  
R. Eugene Iverson
Keyword(s):  
Power Systems ◽  
Health Management ◽  
Diagnostic Methods ◽  
Fault Detection And Isolation ◽  
Benchmark Problem ◽  
Noise Levels ◽  
Turbofan Engine ◽  
Engine Simulation ◽  
Component Faults ◽  
New Algorithms

Recent technology reviews have identified the need for objective assessments of engine health management (EHM) technology. The need is two-fold: technology developers require relevant data and problems to design and validate new algorithms and techniques while engine system integrators and operators need practical tools to direct development and then evaluate the effectiveness of proposed solutions. This paper presents a publicly available gas path diagnostic benchmark problem that has been developed by the Propulsion and Power Systems Panel of The Technical Cooperation Program (TTCP) to help address these needs. The problem is coded in Matlab™ and coupled with a non-linear turbofan engine simulation to produce “snap-shot” measurements, with relevant noise levels, as if collected from a fleet of engines over their lifetime of use. Each engine within the fleet will experience unique operating and deterioration profiles, and may encounter randomly occurring relevant gas path faults including sensor, actuator and component faults. The challenge to the EHM community is to develop gas path diagnostic algorithms to reliably perform fault detection and isolation. An example solution to the benchmark problem is provided along with associated evaluation metrics. A plan is presented to disseminate this benchmark problem to the engine health management technical community and invite technology solutions.

Determination of Concrete Cube Strength from Used Samples / Určení Krychelné Pevnosti Betonu U Použitých Zkušebních Trámců

2012 ◽  
Vol 12 (2) ◽  
pp. 186-194 ◽  
Author(s):  
Oldřich Sucharda ◽  
David Mikolášek ◽  
Jiří Brožovský
Keyword(s):  
Compressive Strength ◽  
Concrete Beams ◽  
Linear Analysis ◽  
Bending Tests ◽  
Cube Strength ◽  
Non Linear ◽  
Compressive Strength Of Concrete ◽  
Concrete Cube

Abstract This paper deals with the determination of compressive strength of concrete. Cubes, cylinders and re-used test beams were tested. The concrete beams were first subjected to three-point or fourpoint bending tests and then used for determination of the compressive strength of concrete. Some concrete beams were reinforced, while others had no reinforcement. Accuracy of the experiments and calculations was verified in a non-linear analysis.

scholarly journals Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form

2021 ◽  
Vol 19 (1) ◽  
pp. 205-213
Author(s):  
Hany W. Darwish ◽  
Abdulrahman A. Al Majed ◽  
Ibrahim A. Al-Suwaidan ◽  
Ibrahim A. Darwish ◽  
Ahmed H. Bakheit ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simultaneous Determination ◽  
Predictive Power ◽  
Principal Component Regression ◽  
Selection Procedure ◽  
Principal Component ◽  
Chemometric Methods ◽  
Full Spectrum ◽  
Azilsartan Medoxomil

Abstract Five various chemometric methods were established for the simultaneous determination of azilsartan medoxomil (AZM) and chlorthalidone in the presence of azilsartan which is the core impurity of AZM. The full spectrum-based chemometric techniques, namely partial least squares (PLS), principal component regression, and artificial neural networks (ANN), were among the applied methods. Besides, the ANN and PLS were the other two methods that were extended by genetic algorithm procedure (GA-PLS and GA-ANN) as a wavelength selection procedure. The models were developed by applying a multilevel multifactor experimental design. The predictive power of the suggested models was evaluated through a validation set containing nine mixtures with different ratios of the three analytes. For the analysis of Edarbyclor® tablets, all the proposed procedures were applied and the best results were achieved in the case of ANN, GA-ANN, and GA-PLS methods. The findings of the three methods were revealed as the quantitative tool for the analysis of the three components without any intrusion from the co-formulated excipient and without prior separation procedures. Moreover, the GA impact on strengthening the predictive power of ANN- and PLS-based models was also highlighted.

scholarly journals Efficiency of Machine Learning Algorithms for the Determination of Macrovesicular Steatosis in Frozen Sections Stained with Sudan to Evaluate the Quality of the Graft in Liver Transplantation

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1993
Author(s):  
Fernando Pérez-Sanz ◽  
Miriam Riquelme-Pérez ◽  
Enrique Martínez-Barba ◽  
Jesús de la Peña-Moral ◽  
Alejandro Salazar Nicolás ◽  
...  
Keyword(s):  
Machine Learning ◽  
Liver Transplantation ◽  
Learning Algorithms ◽  
Selection Procedure ◽  
Machine Learning Algorithms ◽  
Liver Biopsies ◽  
Convenient Technique ◽  
End Stage ◽  
Macrovesicular Steatosis

Liver transplantation is the only curative treatment option in patients diagnosed with end-stage liver disease. The low availability of organs demands an accurate selection procedure based on histological analysis, in order to evaluate the allograft. This assessment, traditionally carried out by a pathologist, is not exempt from subjectivity. In this sense, new tools based on machine learning and artificial vision are continuously being developed for the analysis of medical images of different typologies. Accordingly, in this work, we develop a computer vision-based application for the fast and automatic objective quantification of macrovesicular steatosis in histopathological liver section slides stained with Sudan stain. For this purpose, digital microscopy images were used to obtain thousands of feature vectors based on the RGB and CIE L*a*b* pixel values. These vectors, under a supervised process, were labelled as fat vacuole or non-fat vacuole, and a set of classifiers based on different algorithms were trained, accordingly. The results obtained showed an overall high accuracy for all classifiers (>0.99) with a sensitivity between 0.844 and 1, together with a specificity >0.99. In relation to their speed when classifying images, KNN and Naïve Bayes were substantially faster than other classification algorithms. Sudan stain is a convenient technique for evaluating ME in pre-transplant liver biopsies, providing reliable contrast and facilitating fast and accurate quantification through the machine learning algorithms tested.

scholarly journals Bias Truck Tire Deformation Analysis with Finite Element Modeling

2020 ◽  
Vol 10 (12) ◽  
pp. 4326
Author(s):  
Józef Pelc
Keyword(s):  
Incompressible Material ◽  
Axisymmetric Deformation ◽  
Thermal Shrinkage ◽  
Deformation Analysis ◽  
Truck Tire ◽  
Non Linear ◽  
Strain Relationship ◽  
Tire Modeling ◽  
Total Lagrangian Formulation

This paper presents a method for modeling of pneumatic bias tire axisymmetric deformation. A previously developed model of all-steel radial tire was expanded to include the non-linear stress–strain relationship for textile cord and its thermal shrinkage. Variable cord density and cord angle in the cord-rubber bias tire composite are the major challenges in pneumatic tire modeling. The variabilities result from the tire formation process, and they were taken into account in the model. Mechanical properties of the composite were described using a technique of orthotropic reinforcement overlaying onto isotropic rubber elements, treated as a hyperelastic incompressible material. Due to large displacements, the non-linear problem was solved using total Lagrangian formulation. The model uses MSC.Marc code with implemented user subroutines, allowing for the description of the tire specific properties. The efficiency of the model was verified in the simulation of mounting and inflation of an actual bias truck tire. The shrinkage negligence effect on cord forces and on displacements was examined. A method of investigating the influence of variation of cord angle in green body plies on tire apparent lateral stiffness was proposed. The created model is stabile, ensuring convergent solutions even with large deformations. Inflated tire sizes predicted by the model are consistent with the actual tire sizes. The distinguishing feature of the developed model from other ones is the exact determination of the cord angles in a vulcanized tire and the possibility of simulation with the tire mounting on the rim and with cord thermal shrinkage taken into account. The model may be an effective tool in bias tire design.

scholarly journals Determination of non-linear refractive index of laser crystals and ceramics via different optical techniques

2020 ◽  
Vol 8 ◽  
pp. 100065
Author(s):  
Laurent Lamaignère ◽  
Guido Toci ◽  
Barbara Patrizi ◽  
Matteo Vannini ◽  
Angela Pirri ◽  
...  
Keyword(s):  
Refractive Index ◽  
Optical Techniques ◽  
Linear Refractive Index ◽  
Non Linear ◽  
Laser Crystals

Turbofan Engine Robust H-∞ Dynamical Output Feedback Control Design Based on LMI Method

2005 ◽  
Author(s):  
Xi Wang ◽  
Daoliang Tan ◽  
Tiejun Zheng
Keyword(s):  
Output Feedback ◽  
Linear Models ◽  
Nonlinear Models ◽  
Design Method ◽  
State Space Model ◽  
Output Feedback Control ◽  
Linear Matrix ◽  
Turbofan Engine ◽  
Engine Simulation ◽  
Linear State

This paper presents an approach to turbofan engine dynamical output feedback controller (DOFC) design in the framework of LMI (Linear Matrix Inequality)-based H∞ control. In combination with loop shaping and internal model principle, the linear state space model of a turbofan engine is converted into that of some augmented plant, which is used to establish the LMI formulations of the standard H∞ control problem with respect to this augmented plant. Furthermore, by solving optimal H∞ controller for the augmented plant, we indirectly obtain the H∞ DOFC of turbofan engine which successfully achieves the tracking of reference instructions and effective constraints on control inputs. This design method is applied to the H∞ DOFC design for the linear models of an advanced multivariate turbofan engine. The obtained H∞ DOFC is only in control of the steady state of this turbofan engine. Simulation results from the linear and nonlinear models of this turbofan engine show that the resulting controller has such properties as good tracking performance, strong disturbance rejection, and satisfying robustness.

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