The Experts below are selected from a list of 150 Experts worldwide ranked by ideXlab platform
Yasin Korkmaz - One of the best experts on this subject based on the ideXlab platform.
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Computation of the pressure altitude using adaptive neuro fuzzy inference system for Air Data Computer in Aircrafts
2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU), 2011Co-Authors: Ilke Turkmen, Yasin KorkmazAbstract:For a safe flight and accurate Air navigation, the key Data are calculated using Air Data Computer (ADC). Altitude information is one of the important parameter computed by the ADC. According to Aircraft type, accuracy of the altitude corrected using tables or charts showing the actual corrections in altitude information special to the Aircraft. This correction is important in any high performance and jet Aircraft. In this paper, adaptive neuro fuzzy system (ANFIS) are used to calculate altitude information more easily and accurately using Data obtained from tables formed under standard atmosphere conditions. The pressure altitude values obtained using proposed ANFIS model don't need to correction.
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Uçaklardaki Hava Veri Bilgisayarinda Basinç İrtifasinin Bulanik Mantik Sistemine Dayali Uyarlanir Ağ İle Hesaplanmasi Computation of the Pressure Altitude Using Adaptive Neuro Fuzzy Inference System for Air Data Computer in Aircrafts
2011Co-Authors: Yasin KorkmazAbstract:For a safe flight and accurate Air navigation, the key Data are calculated using Air Data Computer (ADC). Altitude information is one of the important parameter computed by the ADC. According to Aircraft type, accuracy of the altitude corrected using tables or charts showing the actual corrections in altitude information special to the Aircraft. This correction is important in any high performance and jet Aircraft. In this paper, adaptive neuro fuzzy system (ANFIS) are used to calculate altitude information more easily and accurately using Data obtained from tables formed under standard atmosphere conditions. The pressure altitude values obtained using proposed ANFIS model don’t need to correction. 1. GIRIŞ
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ISSPIT - The pressure altitude computation using artificial neural network for Air Data Computer
The 10th IEEE International Symposium on Signal Processing and Information Technology, 2010Co-Authors: Ilke Turkmen, Yasin KorkmazAbstract:Air Data Computer (ADC) calculates the key Data necessary for performing a safe flight and accurate Air navigation. Altitude information is one of the important parameter computed by the ADC. Accuracy of the altitude corrected using tables or charts showing the actual corrections in altitude information special to Aircraft type. This correction is important in any high performance and jet Aircraft. In order to correct these imperfections, certain calibrations need to be made within the ADC. In this paper, artificial neural networks (ANNs) are used to calculate altitude information more easily and accurately using Data obtained from tables formed under standard atmosphere conditions.
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the pressure altitude computation using artificial neural network for Air Data Computer
International Symposium on Signal Processing and Information Technology, 2010Co-Authors: Ilke Turkmen, Yasin KorkmazAbstract:Air Data Computer (ADC) calculates the key Data necessary for performing a safe flight and accurate Air navigation. Altitude information is one of the important parameter computed by the ADC. Accuracy of the altitude corrected using tables or charts showing the actual corrections in altitude information special to Aircraft type. This correction is important in any high performance and jet Aircraft. In order to correct these imperfections, certain calibrations need to be made within the ADC. In this paper, artificial neural networks (ANNs) are used to calculate altitude information more easily and accurately using Data obtained from tables formed under standard atmosphere conditions.
Ilke Turkmen - One of the best experts on this subject based on the ideXlab platform.
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An alternative neural Airspeed computation method for Aircrafts
Aircraft Engineering and Aerospace Technology, 2018Co-Authors: Ilke TurkmenAbstract:Purpose This paper aims to present an alternative Airspeed computation method based on artificial neural networks (ANN) without requiring pitot-static system measurements. Design/methodology/approach The Data set used to train proposed neural model is obtained from the Digital Flight Data Acquisition Unit records of a Boeing 737 type commercial Aircraft for real flight routes. The proposed method uses the flight parameters as inputs of the ANN. The Levenberg–Marquardt training algorithm was used to train the neural model. Findings The predicted Airspeed values obtained with ANN are in good agreement with the measured Airspeed values. The proposed neural model can be used as an alternative Airspeed computation method. Practical implications The proposed alternative Airspeed computation method can be used when the Air Data Computer or pitot-static system has failed. Originality/value The proposed method uses flight parameters as inputs for the ANN. As such, Airspeed is calculated using flight parameters instead of the pitot-static system measurements.
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SIU - Airspeed computation with ANN using FDR records
2012 20th Signal Processing and Communications Applications Conference (SIU), 2012Co-Authors: Ilke Turkmen, Hakan AkbulutAbstract:Airspeed is one of the most important parameters of the Aircrafts. It is measured by the “pitot static system”. It is very difficult to measure true Airspeed because of the Air pressure varies with altitude and temperature. While TAS can be calculated using Air Data Computer in new generation Aircrafts, the computation of the TAS requires utilizing some tables and diagrams using outer Air temperature and pressure in other Aircrafts. This state causes additional task for pilots. In this study, in order to overcome this problem, an artificial neural network (ANN) model is proposed to calculate TAS using F800 type FDR records of CN-235 CASA Aircrafts. The proposed model is also an alternative method that could be used to calculate TAS for new generation Aircrafts.
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Computation of the pressure altitude using adaptive neuro fuzzy inference system for Air Data Computer in Aircrafts
2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU), 2011Co-Authors: Ilke Turkmen, Yasin KorkmazAbstract:For a safe flight and accurate Air navigation, the key Data are calculated using Air Data Computer (ADC). Altitude information is one of the important parameter computed by the ADC. According to Aircraft type, accuracy of the altitude corrected using tables or charts showing the actual corrections in altitude information special to the Aircraft. This correction is important in any high performance and jet Aircraft. In this paper, adaptive neuro fuzzy system (ANFIS) are used to calculate altitude information more easily and accurately using Data obtained from tables formed under standard atmosphere conditions. The pressure altitude values obtained using proposed ANFIS model don't need to correction.
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ISSPIT - The pressure altitude computation using artificial neural network for Air Data Computer
The 10th IEEE International Symposium on Signal Processing and Information Technology, 2010Co-Authors: Ilke Turkmen, Yasin KorkmazAbstract:Air Data Computer (ADC) calculates the key Data necessary for performing a safe flight and accurate Air navigation. Altitude information is one of the important parameter computed by the ADC. Accuracy of the altitude corrected using tables or charts showing the actual corrections in altitude information special to Aircraft type. This correction is important in any high performance and jet Aircraft. In order to correct these imperfections, certain calibrations need to be made within the ADC. In this paper, artificial neural networks (ANNs) are used to calculate altitude information more easily and accurately using Data obtained from tables formed under standard atmosphere conditions.
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the pressure altitude computation using artificial neural network for Air Data Computer
International Symposium on Signal Processing and Information Technology, 2010Co-Authors: Ilke Turkmen, Yasin KorkmazAbstract:Air Data Computer (ADC) calculates the key Data necessary for performing a safe flight and accurate Air navigation. Altitude information is one of the important parameter computed by the ADC. Accuracy of the altitude corrected using tables or charts showing the actual corrections in altitude information special to Aircraft type. This correction is important in any high performance and jet Aircraft. In order to correct these imperfections, certain calibrations need to be made within the ADC. In this paper, artificial neural networks (ANNs) are used to calculate altitude information more easily and accurately using Data obtained from tables formed under standard atmosphere conditions.
Darlene S. Mosser-kerner - One of the best experts on this subject based on the ideXlab platform.
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Flight test results from fiber optic control system integration (FOCSI) fiber optic total pressure transducer
Fly-by-Light, 1994Co-Authors: John W. Berthold, Stuart E. Reed, Darlene S. Mosser-kernerAbstract:We have previously reported on the development of a temperature compensated, self- referenced, microbend fiber optic pressure transducer for total pressure measurement. This transducer outputs the sum of altitude-dependent background pressure and dynamic pressure proportional to Air speed. During flight tests at NASA Dryden, this fiber optic pressure transducer was installed in the same pitot pressure line as the existing electronic pressure transducer in the Air Data Computer. Pressure Data were simultaneously recorded from the transducers during flight tests. Presented in this paper is the comparison and analysis of the Data from both transducers and a summary of the results.
John W. Berthold - One of the best experts on this subject based on the ideXlab platform.
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Flight test results from fiber optic control system integration (FOCSI) fiber optic total pressure transducer
Fly-by-Light, 1994Co-Authors: John W. Berthold, Stuart E. Reed, Darlene S. Mosser-kernerAbstract:We have previously reported on the development of a temperature compensated, self- referenced, microbend fiber optic pressure transducer for total pressure measurement. This transducer outputs the sum of altitude-dependent background pressure and dynamic pressure proportional to Air speed. During flight tests at NASA Dryden, this fiber optic pressure transducer was installed in the same pitot pressure line as the existing electronic pressure transducer in the Air Data Computer. Pressure Data were simultaneously recorded from the transducers during flight tests. Presented in this paper is the comparison and analysis of the Data from both transducers and a summary of the results.
Jacek Pieniazek - One of the best experts on this subject based on the ideXlab platform.
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The cheap Air Data Computer for aviation applications
Aircraft Engineering and Aerospace Technology, 2006Co-Authors: Jacek Pieniazek, Tomasz RogalskiAbstract:Purpose – To present both the construction and sample applications of the small, low‐cost Air Data Computer (ADC) with CAN interface, which has been designed at Avionics Department of Rzeszow Technical University.Design/methodology/approach – The ADC has been developed as a partial task during realization of few aviation projects. It uses cheap piesoresistive pressure sensors with digital temperature compensation to calculate following flight Data: altitude, Airspeed computed in two ways as instrumental Airspeed and true Airspeed, altitude rate, and atmosphere parameters: pressure, temperature and Air density. This device is small and lightweight then it can be used on boards of both small Aircraft and unmanned flying vehicles.Findings – This paper provides information about designed ADC's measurements accuracy. Also it informs about possibilities of the presented device uses.Practical implications – The lightweight low‐cost ADC can reduce both price and weight of complete control systems different types ...
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Software compensation for Air Data Computer sensors
Optoelectronic and Electronic Sensors V, 2003Co-Authors: Jacek PieniazekAbstract:Sensors for the Air Data Computer must be precise in wide operating environment conditions. Besides choosing the best sensor for these purposes further accuracy improvement is necessary. Calibration method, in which temperature effects and non-linearity are taken into consideration, is presented in the paper. Static pressure probe error is another problem. For Air Data Computers, assigned for the small Aircraft with augmented control system, software compensation of the static pressure error is implemented using access from another devices information and angle of attack computation. The soft angle of attack simulation tests show the method property.