scholarly journals Semigroup of Finite-State Deterministic Intuitionistic Fuzzy Automata with Application in Fault Diagnosis of an Aircraft Twin-Spool Turbofan Engine

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Sajida Kousar ◽  
Farah Aslam ◽  
Nasreen Kausar ◽  
Yaé Ulrich Gaba
Keyword(s):  
Fault Diagnosis ◽  
Early Stage ◽  
Engine Performance ◽  
Turbofan Engine ◽  
Inference System ◽  
Turbofan Engines ◽  
Intuitionistic Fuzzy ◽  
Finite State ◽  
Air Cooler ◽  
Fuzzy Automata

The twin-spool turbofan engine is an important component of almost every modern aircraft. Fault detection at an early stage can improve engine performance and health. The current research is based on the construction of an inference system for fault diagnosis in a generalized fuzzy environment. For such an inference system, finite-state deterministic intuitionistic fuzzy automata (FDIFA) are established. A semigroup of FDIFA and its algebraic properties including substructures and structure-preserving maps are studied. The FDIFA semigroups are used as variables for the inference system, and FDIFA semigroup homomorphisms are used to indicate the relation between variables. The newly established model is then applied to diagnose the possible fault and their nature in aircraft twin-spool turbofan engines by modelling the performance of the supercharger and air cooler.

scholarly journals F-16 turbofan engine monitoring system

2019 ◽  
Vol 177 (2) ◽  
pp. 23-35
Author(s):  
Sławomir SZRAMA
Keyword(s):  
Monitoring System ◽  
Health Management ◽  
Engine Performance ◽  
Turbofan Engine ◽  
Turbofan Engines ◽  
Maintenance System ◽  
Management Concept ◽  
And Performance ◽  
Engine Maintenance ◽  
Engine Reliability

The multirole F-16 is the most advanced aircraft in the Polish Air Forces. It has been equipped with the very modern, sophisticated and advanced turbofan engine F100-PW-229. Due to the fact, that there is only one engine, its reliability, durability, efficiency and performance are the crucial factors for the safety reasons. In the article author researched maintenance system of the F100 turbofan engines, to describe Engine Monitoring System features. Engine Monitoring System (EMS) is the key element in the engine prognostic and health monitoring. The EMS provides engine fault indicators to the pilots and technicians and with the engine performance trending affects the F-16 flight safety risk and enhanced engine maintenance management concept. The main goal of this article was to provide information on the F-16 Engine Monitoring System and its impact on the aircraft airworthiness and F-16 fleet readiness resulting from the engine reliability. It is also an introduction to the F-16 Engine Health Management concept.

An Intuitionistic Fuzzy Based Novel Approach to CPU Scheduler

2020 ◽  
Vol 16 (4) ◽  
pp. 316-328
Author(s):  
Supriya Raheja
Keyword(s):  
Fuzzy Inference ◽  
The Other ◽  
Simulation Environment ◽  
Inference System ◽  
Intuitionistic Fuzzy ◽  
Novel Approach ◽  
Continuous Feedback ◽  
Simulation Results ◽  
Effectiveness And Efficiency ◽  
Unique Capability

Background: The extension of CPU schedulers with fuzzy has been ascertained better because of its unique capability of handling imprecise information. Though, other generalized forms of fuzzy can be used which can further extend the performance of the scheduler. Objectives: This paper introduces a novel approach to design an intuitionistic fuzzy inference system for CPU scheduler. Methods: The proposed inference system is implemented with a priority scheduler. The proposed scheduler has the ability to dynamically handle the impreciseness of both priority and estimated execution time. It also makes the system adaptive based on the continuous feedback. The proposed scheduler is also capable enough to schedule the tasks according to dynamically generated priority. To demonstrate the performance of proposed scheduler, a simulation environment has been implemented and the performance of proposed scheduler is compared with the other three baseline schedulers (conventional priority scheduler, fuzzy based priority scheduler and vague based priority scheduler). Results: Proposed scheduler is also compared with the shortest job first CPU scheduler as it is known to be an optimized solution for the schedulers. Conclusion: Simulation results prove the effectiveness and efficiency of intuitionistic fuzzy based priority scheduler. Moreover, it provides optimised results as its results are comparable to the results of shortest job first.

Active fault tolerant control of turbofan engines with actuator faults under disturbances

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Yan-Hua Ma ◽  
Xian Du ◽  
Lin-Feng Gou ◽  
Si-Xin Wen
Keyword(s):  
Active Fault ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Feedback Controller ◽  
Actuator Faults ◽  
Error Feedback ◽  
Turbofan Engine ◽  
Turbofan Engines ◽  
Interval Observer ◽  
State Error

AbstractIn this paper, an active fault-tolerant control (FTC) scheme for turbofan engines subject to simultaneous multiplicative and additive actuator faults under disturbances is proposed. First, a state error feedback controller is designed based on interval observer as the nominal controller in order to achieve the model reference rotary speed tracking control for the fault-free turbofan engine under disturbances. Subsequently, a virtual actuator based reconfiguration block is developed aiming at preserving the consistent performance in spite of the occurrence of the simultaneous multiplicative and additive actuator faults. Moreover, to improve the performance of the FTC system, the interval observer is slightly modified without reconstruction of the state error feedback controller. And a theoretical sufficiency criterion is provided to ensure the stability of the proposed active FTC system. Simulation results on a turbofan engine indicate that the proposed active FCT scheme is effective despite of the existence of actuator faults and disturbances.

scholarly journals A Comprehensive Review of Winding Short Circuit Fault and Irreversible Demagnetization Fault Detection in PM Type Machines

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3309 ◽  
Author(s):  
Zia Ullah ◽  
Jin Hur
Keyword(s):  
Fault Diagnosis ◽  
Early Stage ◽  
Short Circuit ◽  
Industrial Applications ◽  
Operational Environment ◽  
Compact Structure ◽  
Torque Density ◽  
Prime Concern ◽  
Attractive Option ◽  
The Impact

Contemporary research has shown impetus in the diagnostics of permanent magnet (PM) type machines. The manufacturers are now more interested in building diagnostics features in the control algorithms of machines to make them more salable and reliable. A compact structure, exclusive high-power density, high torque density, and efficiency make the PM machine an attractive option to use in industrial applications. The impact of a harsh operational environment most often leads to faults in PM machines. The diagnosis and nipping of such faults at an early stage have appeared as the prime concern of manufacturers and end users. This paper reviews the recent advances in fault diagnosis techniques of the two most frequently occurring faults, namely inter-turn short fault (ITSF) and irreversible demagnetization fault (IDF). ITSF is associated with a short circuit in stator winding turns in the same phase of the machine, while IDF is associated with the weakening strength of the PM in the rotor. A detailed literature review of different categories of fault indexes and their strengths and weaknesses is presented. The research trends in the fault diagnosis and the shortcomings of available literature are discussed. Moreover, potential research directions and techniques applicable for possible solutions are also extensively suggested.

Analysis of Effect of Advanced Technique Configurations on Overall Performance of High Bypass Turbofan Engine

2014 ◽  
Author(s):  
Liu Jian Jun
Keyword(s):  
Air Flow ◽  
Engine Performance ◽  
Performance Model ◽  
Direct Drive ◽  
Nozzle Throat ◽  
Advanced Technique ◽  
Turbofan Engine ◽  
Overall Performance ◽  
Cooling Air Flow ◽  
Cooling Air

An analytical study was undertaken using the performance model of a two spool direct drive high BPR 300kN thrust turbofan engine, to investigate the effects of advanced configurations on overall engine performance. These include variable bypass nozzle, variable cooling air flow and more electric technique. For variable bypass nozzle, analysis on performance of outer fan at different conditions indicates that different operating points cannot meet optimal performance at the same time if the bypass nozzle area kept a constant. By changing bypass nozzle throat area at different states, outer fan operating point moves to the location where airflow and efficiency are more appropriate, and have enough margin away from surge line. As a result, the range of variable area of bypass nozzle throat is determined which ensures engine having a low SFC and adequate stability. For variable cooling airflow, configuration of turbine cooling air flow extraction and methodology for obtaining change of cooling airflow are investigated. Then, base on temperature analysis of turbine vane and blade and resistance of cooling airflow, reduction of cooling airflow is determined. Finally, using performance model which considering effect of cooling air flow on work and efficiency of turbine, variable cooling airflow effect on overall performance is analyzed. For more electric technique, the main characteristic is to use power off-take instead of overboard air extraction. Power off-take and air extraction effect on overall performance of high bypass turbofan engine is compared. Investigation demonstrates that power offtake will have less SFC.

scholarly journals Anfis to Detect Brain Tumor Using MRI

2018 ◽  
Vol 7 (3.27) ◽  
pp. 209
Author(s):  
Susmita Mishra ◽  
M Prakash ◽  
A Hafsa ◽  
G Anchana
Keyword(s):  
Fuzzy Logic ◽  
Brain Tumor ◽  
Graphical Representation ◽  
Fuzzy Inference ◽  
Early Stage ◽  
Histogram Equalization ◽  
Input Image ◽  
Inference System ◽  
Magnetic Resonance Imaging Mri ◽  
Contrast Stretching

Processing of Magnetic Resonance Imaging(MRI) is one of the widely known best techniques to diagnose brain tumor since it gives better results than ultrasound or X-Ray images. The main objective is to diagnose the presence and extraction of brain tumor using MRI images. Image preprocessing includes contrast stretching, noise filtering and Adaptive Histogram Equalization(AHE). AHE gives a graphical representation of digital image without enhancing above the desired level. The next stage involves transferring the redundant information in input image to reduced set of features is called feature selection and is done by color, shape or texture of an image. Image is segmented using incorporation of Artificial Neural Networks(ANN) and Fuzzy logic called Adaptive Neuro-Fuzzy Inference System(ANFIS) wherein we get the desired output to differentiate tumor affected and normal image with its severity level. Since we deal with uncertainty much more, fuzzy logic serves as a vibrant tool in representing human knowledge as IF-THEN rules. MATLAB has been implemented in detection and extraction of tumor at an early stage. 

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