Structural health monitoring of an existing PC box girder bridge with distributed HCFRP sensors in a destructive test

Structural Health Monitoring is becoming an increasingly common tool to obtain the long-term performance of infrastructures and buildings. Many structural health monitoring systems were developed and applied to different bridges in the world. However, very little is known on the applications in extreme cold environment. Fu Sui Bridge, a 1070 m variable cross-section continuous box-girder bridge, is located in the coldest province -- Heilongjiang province, China. In order to monitor the static and dynamic responses of the bridge under the traffic and environmental variation, a long-term continuous monitoring system was designed and installed on Fu Sui Bridge in April 2012. A hydrostatic leveling system was used to measure the displacement and fiber Bragg grating sensors were used to measure strain, acceleration and temperature. Moreover, other necessary components including data acquisition and transmission, data calculation and analysis software are also described. Summer and winter monitoring data are also presented. This paper focuses on: (1) the design and installation of the long-term continuous monitoring system hardware and (2) the operating pattern and function of the automatic monitoring system. After more than one year successful conducting, the system has provided a large amount of data records for daily management and research of the bridge. This system can be applied to extremely cold region.

Download Full-text

Finite element modeling of a full-scale five-girder bridge for structural health monitoring

Structural Health Monitoring ◽

10.1177/1475921710379515 ◽

2010 ◽

Vol 10 (5) ◽

pp. 449-465 ◽

Cited By ~ 7

Author(s):

William S Ragland ◽

Dayakar Penumadu ◽

Richard T Williams

Keyword(s):

Finite Element ◽

Structural Health Monitoring ◽

Finite Element Modeling ◽

Health Monitoring ◽

Full Scale ◽

Element Modeling ◽

Structural Health ◽

Girder Bridge

Download Full-text

PENENTUAN NILAI DEFLEKSI MAKSIMUM PADA JEMBATAN STEEL BOX GIRDER BERDASARKAN DATA NILAI ROTASI

Jurnal Muara Sains, Teknologi, Kedokteran dan Ilmu Kesehatan ◽

10.24912/jmstkik.v5i2.11014 ◽

2021 ◽

Vol 5 (2) ◽

pp. 411

Author(s):

David Surachmat ◽

Made Suangga

Keyword(s):

Structural Health Monitoring ◽

Monitoring System ◽

Global Positioning System ◽

Health Monitoring ◽

Box Girder ◽

Health Monitoring System ◽

Structural Health ◽

Structural Health Monitoring System ◽

Steel Box Girder ◽

Global Positioning

Structural health monitoring system plays a crucial role in order to ensure a well-maintained bridge condition. There are a number of methods that may be utilized in order to conduct the monitoring process, namely the use of Global Positioning System (GPS). Despite its accuracy, the use of GPS is deemed costly. A more practical and economical approach to predicting deflection is the use of tiltmeter to obtain rotational values. This research studied the accuracy of simple span steel box girder deflection that is obtained from regression formulae. The analysis showed that a 3D linear and quadratic regression with two rotation data provided the best accuracy if compared with 2D. Keywords: deflection; rotation; structural health monitoring system; tiltmeter AbstrakPemantauan kesehatan struktur jembatan (structural health monitoring system) sangat penting dilakukan untuk memastikan jembatan tetap dalam kondisi yang memadai. Banyak cara yang dapat dilakukan untuk memonitor kondisi jembatan, salah satunya dengan menggunakan Global Positioning System (GPS). Walaupun menghasilkan data yang akurat, penggunaan GPS dipandang menghabiskan biaya yang relatif besar. Adapun solusi yang lebih praktis dan murah untuk memprediksi defleksi yaitu dengan menggunakan tiltmeter dengan data rotasi. Pada studi ini, telah dipelajari tingkat akurasi defleksi jembatan steel box girder dengan bentang sederhana dari hasil persamaan regresi dengan data rotasi. Hasil analisis menunjukkan bahwa model regresi linear dan kuadratik 3D untuk 2 data rotasi memiliki tingkat akurasi lebih baik jika dibandingkan dengan model regresi linear dan kuadratik 2D untuk 2 data rotasi.

Download Full-text