Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms
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Changduk Kong
,
Semyeong Lim
Abstract
The Neural Networks is mostly used to engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base.
This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measuring performance data, and proposes a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks. Each real engine performance model, which is named as the base performance model that can simulate a new engine performance, is inversely made using its performance test data. Therefore the condition monitoring of each engine can be more precisely carried out through comparison with measuring performance data.
The proposed diagnostic system identifies firstly the faulted components using Fuzzy Logic, and then quantifies faults of the identified components using Neural Networks leaned by fault learning data base obtained from the developed base performance model. In leaning the measuring performance data of the faulted components, the FFBP (Feed Forward Back Propagation) is used. In order to user's friendly purpose, the proposed diagnostic program is coded by the GUI type using MATLAB.
©[2013] by Walter de Gruyter Berlin Boston
Articles in the same Issue
- Masthead
- Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms
- Effect of the Axial Spacing between Vanes and Blades on a Transonic Gas Turbine Performance and Blade Loading
- Study on Design of High Efficiency and Light Weight Composite Propeller Blade for a Regional Turboprop Aircraft
- Effects of Rotor Blade Scaling on High-Pressure Turbine Unsteady Loading
- The Use of Air Injection Nozzles for the Forced Excitation of Axial Compressor Blades
- Effect of Grid Generated Turbulence on Near Field Characteristics of Round Jets
- Study of Shock Wave Control by Suction & Blowing on a Highly-loaded Transonic Compressor Cascade
- Research for the Fluid Field of the Centrifugal Compressor Impeller in Accelerating Startup
- Study of Underexpanded Sonic Jets by Numerical Simulation
- Experimental and Numerical Study of Gap Size and Cooling Flow Rate Effects on Tip Flow of Gas Turbine Blade
- Numerical Investigations of Slip Phenomena in Centrifugal Compressor Impellers
Articles in the same Issue
- Masthead
- Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms
- Effect of the Axial Spacing between Vanes and Blades on a Transonic Gas Turbine Performance and Blade Loading
- Study on Design of High Efficiency and Light Weight Composite Propeller Blade for a Regional Turboprop Aircraft
- Effects of Rotor Blade Scaling on High-Pressure Turbine Unsteady Loading
- The Use of Air Injection Nozzles for the Forced Excitation of Axial Compressor Blades
- Effect of Grid Generated Turbulence on Near Field Characteristics of Round Jets
- Study of Shock Wave Control by Suction & Blowing on a Highly-loaded Transonic Compressor Cascade
- Research for the Fluid Field of the Centrifugal Compressor Impeller in Accelerating Startup
- Study of Underexpanded Sonic Jets by Numerical Simulation
- Experimental and Numerical Study of Gap Size and Cooling Flow Rate Effects on Tip Flow of Gas Turbine Blade
- Numerical Investigations of Slip Phenomena in Centrifugal Compressor Impellers
