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Kiriş Benzeri Sistemler için Kuvvet Tanı ve Sistem Tanımlama için Yeni Bir Yaklaşım: Mod Tarif

Yıl 2022, Cilt: 9 Sayı: 2, 436 - 451, 31.05.2022
https://doi.org/10.31202/ecjse.956081

Öz

Yapı sağlığı izleme yöntemleri yapının işleyişi sırasında, yapı çevresel titreşimlere maruz iken, sistemi tanımayı dolayısıyla hasarı tespit etmeyi hedefler. Bu çalışmada, çevresel titreşimler için geçerli olabilecek mod tarif yöntemi aktarılmaktadır. Bu çalışmada önerilen ve farklı iki kuvvet etkime konumuna göre mod değişkenlerinin hesaplanmayı hedefleyen mod tarif yöntemi modal plan yöntemini kullanır. Modal planların bu çalışmada kullandığı yöntem serbest titreşimler için geçerli bir yöntemdir. Böylece, bu çalışma ile yazına yeni olarak, hem serbest titreşimler hem de çevresel titreşimler için geçerli olabilecek bir yöntem aktarılmıştır.
Genel olarak, çevresel titreşim analizlerinde yapıya etkiyen kuvvetler ölçülmez. Fakat bu çalışmada yazına yeni olarak kiriş benzeri sistemlerde modal planlar kullanılarak, kuvvetler ölçülmeden kuvvet konumunun tahmini çevresel titreşimler altında yapılabileceği gösterilmiştir. Sistem tanımlama adımındaki muhtemel hatanın en aza indirilebilmesi için kuvvet etkime konumunun çözümleme yapılan serbestlik derecesine yakın olmasının ve hedef frekans aralığına göre veri örnekleme sıklığının belirlenmesinin önemi vurgulanmıştır.

Kaynakça

  • Tufan T., An investigation of system identification and damage estimation using modal plots, count plots and a damage indicator. Doktora Tezi, Boğaziçi Universitesi, İstanbul, 2019.
  • Derriso, M. M., Olson E. E., DeSimio M. P., Military Aircraft, In Encyclopedia of Structural Health Monitoring, Wiley, Blackwell, Hoboken, NJ, USA, 1, 2009.
  • Qiao, B., Ao, C., Mao, Z., & Chen, X., Non-convex sparse regularization for impact force identification. Journal of Sound and Vibration, 115311, 2020.
  • Manns, Luke, Michael McHugh, and Akbar Khatibi, Impact force identification on composite aerospace structures under flight conditions. In APISAT 2019: Asia Pacific International Symposium on Aerospace Technology, p. 25. Engineers Australia, 2019.
  • Saleem, Muhammad M., and Hongki Jo, Impact force localization for civil infrastructure using augmented Kalman Filter optimization. Smart Structures and Systems 23, no. 2, 123-139, 2019. Yang J. N., Application of optimal control theory to civil engineering structures. Journal of the engineering Mechanics Division, 101(6), 819-838, 1975.
  • Peeters B., System identification and damage detection in civil engeneering. Doktora Tezi, Katholieke Universiteit Leuven, 2000.
  • Ren W. X., Zong Z. H., Output-only modal parameter identification of civil engineering structures. Structural Engineering and Mechanics, 17(3-4), 429-444, 2004.
  • Krishnanunni, C. G., Raj, R. S., Nandan, D., Midhun, C. K., Sajith, A. S., Ameen, M., Sensitivity-based damage detection algorithm for structures using vibration data. Journal of Civil Structural Health Monitoring. 13;9(1):137-51, 2019.
  • Vashisht, R., Viji, H., Sundararajan, T., Mohankumar, D., Sumitra S., Structural Health Monitoring of Cantilever Beam, a Case Study—Using Bayesian Neural Network and Deep Learning. InStructural Integrity Assessment (pp. 749-761), Springer, Singapore, 2020.
  • Beyen, K., Titreşim verisiyle güncellenmiş sonlu eleman modeliyle hasar simulasyonu. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 32(2), 2017.
  • Heylen W., Lammens S., Sas P., Modal analysis theory and testing. Department of Mechanical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium, 1997.
  • Armstrong D.M., Sibbald A., Fairfield C.A., Forde M.C., Modal analysis for masonry arch bridge spandrell wall separation identification. NDT & E International, 28(6), 377-386, 1995.
  • Schoukens J., Pintelon R., Rolain Y., Time domain identification, frequency domain identification. Equivalencies! Differences?. In American Control Conference, 2004. Proceedings of the 2004 (Vol. 1, pp. 661-666). IEEE, 2004.
  • Schwarz G., Estimating the dimension of a model. The annals of statistics, 6(2), 461-464, 1978.
  • Zhang L., Yao Y., Lu M., An improved time domain polyreference method for modal identification. Mechanical Systems and Signal Processing, 1(4), pp.399-413, 1987.
  • Zhang L., Wang T., Tamura Y., A frequency–spatial domain decomposition (FSDD) method for operational modal analysis. Mechanical systems and signal processing, 24(5), pp.1227-1239, 2010.
  • Akaike H., A new look at the statistical model identification. IEEE transactions on automatic control, 19(6), pp.716-723, 1974.
  • De Roeck G., Peeters B., Ren W. X., Benchmark study on system identification through ambient vibration measurements. In Proceedings of IMAC-XVIII, the 18th International Modal Analysis Conference, San Antonio, Texas, 1106-1112, 2000.
  • Allemang, R. J., The modal assurance criterion–twenty years of use and abuse, Sound and vibration, 37(8), 14-23, 2003.
  • Tufan T., Akalp S., Modal plot - System identification and fault detection. Structuctural Control and Health Monitoring, e2347, 2019.
  • Vicario F., Phan M. Q., Betti R., Longman R.W., Output‐only observer/Kalman filter identification (O3KID). Structural Control and Health Monitoring, 22(5), 847-872, 2015.
  • Juang J.N., Pappa R.S., An eigensystem realization algorithm for modal parameter identification and model reduction. Journal of guidance, control, and dynamics, 8(5), 620-627, 1985.
  • McRAE D.J., K-means clustering using multivariate data. Classification Soc. Bull, 2(2), p.62, 1970.
  • Perera, R., Torres, L., Ruiz, A., Barris, C. and Baena, M., An EMI-Based Clustering for Structural Health Monitoring of NSM FRP Strengthening Systems. Sensors, 19(17), p.3775, 2019.
  • Hartigan J.A., Wong M.A., Algorithm AS 136: A k-means clustering algorithm. Journal of the Royal Statistical Society. Series C (Applied Statistics), 28(1), pp.100-108, 1979.
  • Ohkami Y., Tanaka H., Estimation of the Force and Location of an Impact Exerted on a Spacecraft. JSME International Journal Series C Mechanical Systems, Machine Elements and Manufacturing, 41, no. 4, 829-835, 1998.
  • Qiao, B., Mao, Z., Liu, J., Zhao, Z. and Chen, X., Group sparse regularization for impact force identification in time domain. Journal of Sound and Vibration, 445, pp.44-63, 2019.
  • Qiu, B., Zhang, M., Li, X., Qu, X., Tong, F., Unknown impact force localisation and reconstruction in experimental plate structure using time-series analysis and pattern recognition. International Journal of Mechanical Sciences. Jan 15;166:105231, 2020.
  • Oskoui, E.A., Taylor, T., Ansari, F., Method and sensor for monitoring weight of trucks in motion based on bridge girder end rotations. Structure and Infrastructure Engineering, 3;16(3):481-94, 2020.
  • James, G.H., Carne. T. G., Damping measurements on operating wind turbines using the natural excitation technique (NExT). In 11th ASME Wind Energy Symposium presented at the Energy Sources Technology Conference and Exhibition, vol. 12, p. 75-81, 1992.

A New Approach to Force Estimation and System Identification in Beam-like Structures: Mode Description

Yıl 2022, Cilt: 9 Sayı: 2, 436 - 451, 31.05.2022
https://doi.org/10.31202/ecjse.956081

Öz

Structural health monitoring methods aim to identify the system and therefore the damage in the system during the operation of the structure, the building is exposed to environmental vibrations. In this study, the mode description method which is valid for environmental vibrations is proposed. The mode description which aims to estimate the modal parameters according to the two or more different input force locations uses modal plots. The method used by modal plans in this study is a valid method for free vibrations. Thus, in this study a method that can be applied for both free vibrations and environmental vibrations is proposed which is novel to the literature.
In general, the forces acting on the structure are not measured in ambient vibration analyzes. However, in this sudy, with the modal plot, estimation of the input force position under environmental vibrations without measuring the input forces is shown for the beam-like structures which is novel to the literature. For the system identification step to be performed with minimum error, the input force location must be close to the degree of freedom analyzed and the frequency of data sampling rate should be chosen according to the target frequency range.

Kaynakça

  • Tufan T., An investigation of system identification and damage estimation using modal plots, count plots and a damage indicator. Doktora Tezi, Boğaziçi Universitesi, İstanbul, 2019.
  • Derriso, M. M., Olson E. E., DeSimio M. P., Military Aircraft, In Encyclopedia of Structural Health Monitoring, Wiley, Blackwell, Hoboken, NJ, USA, 1, 2009.
  • Qiao, B., Ao, C., Mao, Z., & Chen, X., Non-convex sparse regularization for impact force identification. Journal of Sound and Vibration, 115311, 2020.
  • Manns, Luke, Michael McHugh, and Akbar Khatibi, Impact force identification on composite aerospace structures under flight conditions. In APISAT 2019: Asia Pacific International Symposium on Aerospace Technology, p. 25. Engineers Australia, 2019.
  • Saleem, Muhammad M., and Hongki Jo, Impact force localization for civil infrastructure using augmented Kalman Filter optimization. Smart Structures and Systems 23, no. 2, 123-139, 2019. Yang J. N., Application of optimal control theory to civil engineering structures. Journal of the engineering Mechanics Division, 101(6), 819-838, 1975.
  • Peeters B., System identification and damage detection in civil engeneering. Doktora Tezi, Katholieke Universiteit Leuven, 2000.
  • Ren W. X., Zong Z. H., Output-only modal parameter identification of civil engineering structures. Structural Engineering and Mechanics, 17(3-4), 429-444, 2004.
  • Krishnanunni, C. G., Raj, R. S., Nandan, D., Midhun, C. K., Sajith, A. S., Ameen, M., Sensitivity-based damage detection algorithm for structures using vibration data. Journal of Civil Structural Health Monitoring. 13;9(1):137-51, 2019.
  • Vashisht, R., Viji, H., Sundararajan, T., Mohankumar, D., Sumitra S., Structural Health Monitoring of Cantilever Beam, a Case Study—Using Bayesian Neural Network and Deep Learning. InStructural Integrity Assessment (pp. 749-761), Springer, Singapore, 2020.
  • Beyen, K., Titreşim verisiyle güncellenmiş sonlu eleman modeliyle hasar simulasyonu. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 32(2), 2017.
  • Heylen W., Lammens S., Sas P., Modal analysis theory and testing. Department of Mechanical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium, 1997.
  • Armstrong D.M., Sibbald A., Fairfield C.A., Forde M.C., Modal analysis for masonry arch bridge spandrell wall separation identification. NDT & E International, 28(6), 377-386, 1995.
  • Schoukens J., Pintelon R., Rolain Y., Time domain identification, frequency domain identification. Equivalencies! Differences?. In American Control Conference, 2004. Proceedings of the 2004 (Vol. 1, pp. 661-666). IEEE, 2004.
  • Schwarz G., Estimating the dimension of a model. The annals of statistics, 6(2), 461-464, 1978.
  • Zhang L., Yao Y., Lu M., An improved time domain polyreference method for modal identification. Mechanical Systems and Signal Processing, 1(4), pp.399-413, 1987.
  • Zhang L., Wang T., Tamura Y., A frequency–spatial domain decomposition (FSDD) method for operational modal analysis. Mechanical systems and signal processing, 24(5), pp.1227-1239, 2010.
  • Akaike H., A new look at the statistical model identification. IEEE transactions on automatic control, 19(6), pp.716-723, 1974.
  • De Roeck G., Peeters B., Ren W. X., Benchmark study on system identification through ambient vibration measurements. In Proceedings of IMAC-XVIII, the 18th International Modal Analysis Conference, San Antonio, Texas, 1106-1112, 2000.
  • Allemang, R. J., The modal assurance criterion–twenty years of use and abuse, Sound and vibration, 37(8), 14-23, 2003.
  • Tufan T., Akalp S., Modal plot - System identification and fault detection. Structuctural Control and Health Monitoring, e2347, 2019.
  • Vicario F., Phan M. Q., Betti R., Longman R.W., Output‐only observer/Kalman filter identification (O3KID). Structural Control and Health Monitoring, 22(5), 847-872, 2015.
  • Juang J.N., Pappa R.S., An eigensystem realization algorithm for modal parameter identification and model reduction. Journal of guidance, control, and dynamics, 8(5), 620-627, 1985.
  • McRAE D.J., K-means clustering using multivariate data. Classification Soc. Bull, 2(2), p.62, 1970.
  • Perera, R., Torres, L., Ruiz, A., Barris, C. and Baena, M., An EMI-Based Clustering for Structural Health Monitoring of NSM FRP Strengthening Systems. Sensors, 19(17), p.3775, 2019.
  • Hartigan J.A., Wong M.A., Algorithm AS 136: A k-means clustering algorithm. Journal of the Royal Statistical Society. Series C (Applied Statistics), 28(1), pp.100-108, 1979.
  • Ohkami Y., Tanaka H., Estimation of the Force and Location of an Impact Exerted on a Spacecraft. JSME International Journal Series C Mechanical Systems, Machine Elements and Manufacturing, 41, no. 4, 829-835, 1998.
  • Qiao, B., Mao, Z., Liu, J., Zhao, Z. and Chen, X., Group sparse regularization for impact force identification in time domain. Journal of Sound and Vibration, 445, pp.44-63, 2019.
  • Qiu, B., Zhang, M., Li, X., Qu, X., Tong, F., Unknown impact force localisation and reconstruction in experimental plate structure using time-series analysis and pattern recognition. International Journal of Mechanical Sciences. Jan 15;166:105231, 2020.
  • Oskoui, E.A., Taylor, T., Ansari, F., Method and sensor for monitoring weight of trucks in motion based on bridge girder end rotations. Structure and Infrastructure Engineering, 3;16(3):481-94, 2020.
  • James, G.H., Carne. T. G., Damping measurements on operating wind turbines using the natural excitation technique (NExT). In 11th ASME Wind Energy Symposium presented at the Energy Sources Technology Conference and Exhibition, vol. 12, p. 75-81, 1992.
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Tarık Tufan 0000-0001-9324-2401

Yayımlanma Tarihi 31 Mayıs 2022
Gönderilme Tarihi 22 Haziran 2021
Kabul Tarihi 24 Aralık 2021
Yayımlandığı Sayı Yıl 2022 Cilt: 9 Sayı: 2

Kaynak Göster

IEEE T. Tufan, “Kiriş Benzeri Sistemler için Kuvvet Tanı ve Sistem Tanımlama için Yeni Bir Yaklaşım: Mod Tarif”, ECJSE, c. 9, sy. 2, ss. 436–451, 2022, doi: 10.31202/ecjse.956081.