Boğaziçi Köprüsü Hareketlerinin Zaman Dizileri Analizi İle Belirlenmesi

Bu makalede; Asya ile Avrupa kıtalarını birbirine bağlayan İstanbul Boğaziçi Köprüsü’nün tabliye ve kulelerinin rüzgar kuvveti, sıcaklık değişimleri ve trafi k yükü gibi etkiyen yükler altındaki yanal, boylamasına ve düşey hareketleri, zaman dizileri analizi ile araştırılmış ve belirlenmiştir. Analiz sonucu, dizilerdeki trend bileşenlerinin, köprünün kısa süreli gözlemlerinde uzun zamanlı periyodik hareketinden kaynaklandığı tespit edilmiştir. Dizilerin periyodik bileşen analizinde ise, köprünün frekanslarını belirleyebilmek için dizilere alçak geçişli fi ltreleme işlemi uygulanmıştır. Dizilerin zaman alanından frekans alanına geçişi ise Hızlı Fourier Dönüşümü HFD ile sağlanmış ve dizilerin güç spektrumları hesaplanmıştır. Güç spektrumlarından tespit edilen frekansların köprünün beklenen davranışını yansıttığı görülmüştür. Özellikle köprü tabliyesinin rüzgar kuvveti ve trafi k yükünden kaynaklanan çok sayıda anlamlı periyodik hareketlere sahip olduğu tespit edilmiştir. Son olarak da zaman dizilerinin stokastik bileşenleri Otoregresif AR ve Otoregresif Hareketli Ortalama ARMA modellerle belirlenmiştir. Sonuç olarak, zaman dizileri analizi ile köprünün gözlenen hareketlerinde beklenmedik herhangi bir durum tespit edilememiştir

Determining Movements of Bosporus Bridge Using Time Series Analysis

In this paper, the movements of the apron and pylons of Istanbul Bosporus Bridge, which connects Asia to Europe, were observed under different stress factors such as wind speeds, temperature changes and traffi c load, and time series analyses were conducted to determine and examine the lateral, longitudinal and vertical movements of bridge’s apron and pylons. In the analysis of time series trend, periodical and stochastic components in the series representing the movements of the bridge were determined. As a result of the analysis made for the short termed observations it was determined that the trend components in the series originated from the long term periodical movements of the bridge. In the analysis of the periodical components of the series on the other hand, the low-pass fi ltering processes were applied to the series to determine frequencies of the bridge. The transformation of the series from time domain to frequency domain was carried out using Fast Fourier Transform FFT , and the power spectrums of series were also computed. It has been found that the frequencies obtained from power spectrums refl ect the expected movements of the bridge. It has also been found out that the bridge deck sustains signifi cant periodical movements resulting from wind force and traffi c load. Finally the stochastic components of time series has been determined with the use of Auto-Regressive AR and Auto-Regressive Moving Average ARMA models. As a result, no unexpected condition has been determined with the time series analysis in the observed movements of the bridge.

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