HARMONIC ANALYSIS OF ACCELERATOR SIGNALS USING CHEETAH OPTIMIZATION ALGORITHM
Yıl 2024,
Cilt: 2 Sayı: 2, 51 - 57, 30.12.2024
Kadir Yasin Sunca
,
Serdar Koçkanat
Öz
In this paper, harmonic estimation of the harmonic signal obtained from the shaking table used by civil and earthquake engineers to simulate earthquake signals with the help of accelerometers is performed with the Cheetah Optimization Algorithm. Afterwards, the amplitude and phase values of the signal will be compared and evaluated with some algorithms in the literature. As a result, the reliability of the Cheetah Optimization Algorithm will be discussed and the analysis of earthquake signals will enable more accurate estimation.
Kaynakça
- 1.Keller, Edward A., and Duane E. DeVecchio. Natural hazards:earth's processes as hazards, disasters, and catastrophes.Routledge, 2019.
- 2.X. Ji, K. Kajiwara, T. Nagae, R. Enokida, M. Nakashima, Asubstructure shaking table test for reproduction ofearthquake responses of high-rise buildings, Earthq. Eng.Struct. Dyn. 38 (12)(2009) 1381–1399,
http://dx.doi.org/10.1002/eqe.907 .
- 3.Prasad, Bharat Bhushan. İleri zemin dinamiği ve depremmühendisliği . PHI Öğrenme Pvt. Ltd., 2011.
- 4.K. Seki, M. Iwasaki, M. Kawafuku, H. Hirai, K. Yasuda,Improvement of control performance in shaking-tables byfeedback compensation for reaction force, in: Proceedings of 2008 34th Annual Conference of the IEEE IndustrialElectronics Society, Orlando, FL, 2008, pp. 2551–2556,http://dx.doi.org/10.1109/IECON.2008.4758358 .
- 5.J.-J. Yao, S.-H. Hu, W. Fu, J.-W. Han, Impact of excitation signalupon the acceleration harmonic distortion of anelectrohydraulic shaking table, J. Vib. Control 17 (7) (2011)
1106–1111, http://dx.doi.org/10.1177/1077546310366579.
- 6. Ingale, Rajesh. "Harmonic analysis using FFT andSTFT." International Journal of Signal Processing, ImageProcessing and Pattern Recognition 7.4 (2014): 345-362.
- 7.J. Yao, H. Yan, R. Xiao, D. Di, G. Jiang, S. Gao, H. Yu, Sinusoidalacceleration harmonic estimation using the extendedKalman filter for an electrohydraulic servo shaking table, J. Vib. Control 21 (8) (2013) 1566–1579,
http://dx.doi.org/10.1177/1077546313499392 .
- 8. J. Yao, D. Di, G. Jiang, G. Shuang, H. Yan, Real-time accelerationharmonics estimation for an electro-hydraulic servo shaking table using Kalman filter with a linear model, IEEE Trans. Control Syst. Technol. 22 (2) (2014) 794–800, http://dx.doi.org/10.1109/TCST.2013.2256136 .
- 9.J. Yao, R. Xiao, S. Chen, D. Duato, G. Shuang, H. Yu,Acceleration harmonic identification algorithm based on theunscented Kalman filter for shaking signals of an electro- hydraulic servo shaking table, J. Vib. Control 21 (16) (2014)3205–3217, http://dx.doi.org/10.1177/1077546314521849
- 10. J. Yao, H. Yu, M. Dietz, R. Xiao, S. Chen, T. Wang, Q. Niu,Acceleration harmonic estimation for a hydraulic shakingtable by using particle swarm optimization, Trans. Inst.Meas. Control 39 (5) (2017) 738–747,
http://dx.doi.org/10.1177/0142331215619975 .
- 11.S. Kockanat, Acceleration harmonic estimation for hydraulicshaking table using bat algorithm, Eur. J. Sci. Technol. (15)(2019) 387–393, http://dx.doi.org/10.31590/ejosat.536755 .
- 12.S. Kockanat, Acceleration harmonic estimation using anapproach based artificial bee colony algorithm: A hydraulicshaking table application, in: 27th Signal Processing andCommunications Applications Conference (SIU), 2019, pp. 1– 4, https://doi.org/10.1109/SIU.2019.8806377 .
- 13.Kockanat, S. (2020). Acceleration harmonics estimation andelimination with MABC–RLS algorithm: Simulation andexperimental analyses on shaking table. Applied SoftComputing, 92, 106377, https://doi.org/10.1016/j.asoc.
2020. 106377 .
- 14. Klein, Carlos Eduardo, Viviana Cocco Mariani, and Leandro dos Santos Coelho. "Cheetah Based Optimization Algorithm:A Novel Swarm Intelligence Paradigm." ESANN. 2018.
- 15. O’Brien, S. J., Johnson, W. E., Driscoll, C. A., Dobrynin, P. &Marker, L. Conservation genetics of the cheetah: lessonslearned and new opportunities. J. Hered. 108, 671–677(2017). https://doi.org/10.1093/jhered/esx047.
- 16.Krausman, P. R. & Morales, S. M. Acinonyx jubatus. Mamm. Species 2005, 1–6 (2005).
- 17.Estes, R. D. The Behavior Guide to African Mammals:Including Hoofed Mammals, Carnivores (Primates. Universityof California Press, 2012).
- 18.Yao, J., Yu, H., Dietz, M., Xiao, R., Chen, S., Wang, T. and Niu,
Q.(2017). Acceleration harmonic estimation for a hydraulicshaking table by using particle swarm optimization.Transactions of the Institute of Measurement and Control,39(5), 738–747
ÇİTA OPTİMİZASYON ALGORİTMASI KULLANARAK İVMEÖLÇER SİNYALLERİNİN HARMONİK ANALİZİ
Yıl 2024,
Cilt: 2 Sayı: 2, 51 - 57, 30.12.2024
Kadir Yasin Sunca
,
Serdar Koçkanat
Öz
Bu makalede, inşaat ve deprem mühendislerinin deprem sinyallerini simüle etmek için kullandıkları sarsma tablasından ivmeölçer yardımıyla alınan harmonikli sinyalin Çita Optimizasyon Algoritmasıyla harmonik kestirimi yapılmıştır. Daha sonrasında sinyalin genlik ve faz değerleri literatürdeki bazı algoritmalar ile karşılaştırılması yapılacak ve değerlendirilecektir. Sonuç olarak Çita Optimizasyon Algoritmasının güvenirliği tartışılacak ve deprem sinyallerinin analizi daha doğru bir şekilde kestirim yapılmasına olanak sağlanacak.
Kaynakça
- 1.Keller, Edward A., and Duane E. DeVecchio. Natural hazards:earth's processes as hazards, disasters, and catastrophes.Routledge, 2019.
- 2.X. Ji, K. Kajiwara, T. Nagae, R. Enokida, M. Nakashima, Asubstructure shaking table test for reproduction ofearthquake responses of high-rise buildings, Earthq. Eng.Struct. Dyn. 38 (12)(2009) 1381–1399,
http://dx.doi.org/10.1002/eqe.907 .
- 3.Prasad, Bharat Bhushan. İleri zemin dinamiği ve depremmühendisliği . PHI Öğrenme Pvt. Ltd., 2011.
- 4.K. Seki, M. Iwasaki, M. Kawafuku, H. Hirai, K. Yasuda,Improvement of control performance in shaking-tables byfeedback compensation for reaction force, in: Proceedings of 2008 34th Annual Conference of the IEEE IndustrialElectronics Society, Orlando, FL, 2008, pp. 2551–2556,http://dx.doi.org/10.1109/IECON.2008.4758358 .
- 5.J.-J. Yao, S.-H. Hu, W. Fu, J.-W. Han, Impact of excitation signalupon the acceleration harmonic distortion of anelectrohydraulic shaking table, J. Vib. Control 17 (7) (2011)
1106–1111, http://dx.doi.org/10.1177/1077546310366579.
- 6. Ingale, Rajesh. "Harmonic analysis using FFT andSTFT." International Journal of Signal Processing, ImageProcessing and Pattern Recognition 7.4 (2014): 345-362.
- 7.J. Yao, H. Yan, R. Xiao, D. Di, G. Jiang, S. Gao, H. Yu, Sinusoidalacceleration harmonic estimation using the extendedKalman filter for an electrohydraulic servo shaking table, J. Vib. Control 21 (8) (2013) 1566–1579,
http://dx.doi.org/10.1177/1077546313499392 .
- 8. J. Yao, D. Di, G. Jiang, G. Shuang, H. Yan, Real-time accelerationharmonics estimation for an electro-hydraulic servo shaking table using Kalman filter with a linear model, IEEE Trans. Control Syst. Technol. 22 (2) (2014) 794–800, http://dx.doi.org/10.1109/TCST.2013.2256136 .
- 9.J. Yao, R. Xiao, S. Chen, D. Duato, G. Shuang, H. Yu,Acceleration harmonic identification algorithm based on theunscented Kalman filter for shaking signals of an electro- hydraulic servo shaking table, J. Vib. Control 21 (16) (2014)3205–3217, http://dx.doi.org/10.1177/1077546314521849
- 10. J. Yao, H. Yu, M. Dietz, R. Xiao, S. Chen, T. Wang, Q. Niu,Acceleration harmonic estimation for a hydraulic shakingtable by using particle swarm optimization, Trans. Inst.Meas. Control 39 (5) (2017) 738–747,
http://dx.doi.org/10.1177/0142331215619975 .
- 11.S. Kockanat, Acceleration harmonic estimation for hydraulicshaking table using bat algorithm, Eur. J. Sci. Technol. (15)(2019) 387–393, http://dx.doi.org/10.31590/ejosat.536755 .
- 12.S. Kockanat, Acceleration harmonic estimation using anapproach based artificial bee colony algorithm: A hydraulicshaking table application, in: 27th Signal Processing andCommunications Applications Conference (SIU), 2019, pp. 1– 4, https://doi.org/10.1109/SIU.2019.8806377 .
- 13.Kockanat, S. (2020). Acceleration harmonics estimation andelimination with MABC–RLS algorithm: Simulation andexperimental analyses on shaking table. Applied SoftComputing, 92, 106377, https://doi.org/10.1016/j.asoc.
2020. 106377 .
- 14. Klein, Carlos Eduardo, Viviana Cocco Mariani, and Leandro dos Santos Coelho. "Cheetah Based Optimization Algorithm:A Novel Swarm Intelligence Paradigm." ESANN. 2018.
- 15. O’Brien, S. J., Johnson, W. E., Driscoll, C. A., Dobrynin, P. &Marker, L. Conservation genetics of the cheetah: lessonslearned and new opportunities. J. Hered. 108, 671–677(2017). https://doi.org/10.1093/jhered/esx047.
- 16.Krausman, P. R. & Morales, S. M. Acinonyx jubatus. Mamm. Species 2005, 1–6 (2005).
- 17.Estes, R. D. The Behavior Guide to African Mammals:Including Hoofed Mammals, Carnivores (Primates. Universityof California Press, 2012).
- 18.Yao, J., Yu, H., Dietz, M., Xiao, R., Chen, S., Wang, T. and Niu,
Q.(2017). Acceleration harmonic estimation for a hydraulicshaking table by using particle swarm optimization.Transactions of the Institute of Measurement and Control,39(5), 738–747