Abstract
One
way to decrease the sensor uncertainties is to use calibration process. In this
study the sensor calibration method using the genetic algorithm (GA) based on
the corresponding values obtained by the reference standards is developed. As
the calibration characteristic, 2nd order polynomial is used. As an
example, GA based calibration of a differential pressure gauge using standard
pressure setting devices is examined.
Keywords
Measurement instrument Measurement uncertainty Calibration Genetic algorithm Differential pressure gauge
References
- Cooper WD. Electronic Instrumentation and Measurement Techniques. NJ, USA, Englewood Cliffs, Prentice Hall, Inc., 1978.
- Hacıyev Ç. Deney Verilerinin İşlenme Yöntemleri ve Mühendislik Uygulamaları. Ankara, Türkiye, Nobel Yayın Dağıtım Tic. Ltd. Şti. 2010.
- Betta G, Dell’Isola M. Frattolillo A. “Experimental design techniques for optimising measurement chain calibration”. Measurement, 30(2), 115-127, 2001.
- Khan SA, Shabani DT, Agarwala AK. “Sensor calibration and compensation using artificial neural network”. ISA Transactions, 42(3), 337-352, 2003.
- Glueck M, Oshinubi Manoli Y. “Automatic real-time offset calibration of gyroscopes”. IEEE Sensor Applications Symposium, Galveston, USA, 19-21 February 2013.
- Sarcevic P, Pletl S, Kincses Z. “Evolutionary algorithm based 9DOF sensor board calibration”. 12th International Symposium on Intelligent Systems and Informatics (SISY 2014), Subotica, Serbia, 11-13 September 2014.
- Kim MS, Yu SB, Lee KS. “Development of a high-precision calibration method for inertial measurement unit”. International Journal of Precision Engineering and Manufacturing, 15, 567-575, 2014.
- Xueliang P, Pei J, Chunsheng L. “The calibration method of three-axis magnetometer based on genetic algorithm”. Applied Mechanics and Materials, 722, 373-378, 2015.
- Yoon J. “ANN-based collaborative sensor calibration and GA-approach to sensor mutation management". 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), Hamamatsu, Japan, 9-13 July 2017.
- Michalewicz Z. Genetic Algorithms + Data Structures = Evolution Programs. New York, USA, Springer-Verlag, 1992.
- Cortes P, Larraneta J, Onieva L. “Genetic algorithm for controllers in elevator groups: Analysis and simulation during lunchpeak traffic”. Applied Soft Computing, 4(2), 59-174, 2004.
- Jacobson L, Kanber B. Genetic Algorithms in Java Basics, New York, USA, Apress, 2015.
Abstract
Sensörlerin belirsizliğini azaltma yöntemlerinden
biri, onların kalibrasyonunun yapılmasıdır. Bu çalışmada referans standartların
kullanımına dayanarak genetik algoritma (GA) ile sensör kalibrasyonunun
yapılması için algoritma geliştirilmiştir. Kalibrasyon karakteristiği olarak 2.
dereceden polinom ele alınmıştır. Örnek olarak diferansiyel basınç ölçücüsü ele
alınmış, standart basınç seti kullanımı ile onun GA tabanlı kalibrasyonu
yapılmıştır.
References
- Cooper WD. Electronic Instrumentation and Measurement Techniques. NJ, USA, Englewood Cliffs, Prentice Hall, Inc., 1978.
- Hacıyev Ç. Deney Verilerinin İşlenme Yöntemleri ve Mühendislik Uygulamaları. Ankara, Türkiye, Nobel Yayın Dağıtım Tic. Ltd. Şti. 2010.
- Betta G, Dell’Isola M. Frattolillo A. “Experimental design techniques for optimising measurement chain calibration”. Measurement, 30(2), 115-127, 2001.
- Khan SA, Shabani DT, Agarwala AK. “Sensor calibration and compensation using artificial neural network”. ISA Transactions, 42(3), 337-352, 2003.
- Glueck M, Oshinubi Manoli Y. “Automatic real-time offset calibration of gyroscopes”. IEEE Sensor Applications Symposium, Galveston, USA, 19-21 February 2013.
- Sarcevic P, Pletl S, Kincses Z. “Evolutionary algorithm based 9DOF sensor board calibration”. 12th International Symposium on Intelligent Systems and Informatics (SISY 2014), Subotica, Serbia, 11-13 September 2014.
- Kim MS, Yu SB, Lee KS. “Development of a high-precision calibration method for inertial measurement unit”. International Journal of Precision Engineering and Manufacturing, 15, 567-575, 2014.
- Xueliang P, Pei J, Chunsheng L. “The calibration method of three-axis magnetometer based on genetic algorithm”. Applied Mechanics and Materials, 722, 373-378, 2015.
- Yoon J. “ANN-based collaborative sensor calibration and GA-approach to sensor mutation management". 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), Hamamatsu, Japan, 9-13 July 2017.
- Michalewicz Z. Genetic Algorithms + Data Structures = Evolution Programs. New York, USA, Springer-Verlag, 1992.
- Cortes P, Larraneta J, Onieva L. “Genetic algorithm for controllers in elevator groups: Analysis and simulation during lunchpeak traffic”. Applied Soft Computing, 4(2), 59-174, 2004.
- Jacobson L, Kanber B. Genetic Algorithms in Java Basics, New York, USA, Apress, 2015.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Article |
| Authors | |
| Publication Date | October 12, 2018 |
| Published in Issue | Year 2018 Volume: 24 Issue: 5 |
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