Temperature Effect on Continuous Modal Parameter Identification of Cable Stayed Bridge
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Bibliografische Angaben
Autor(en): |
Inamullah Khan
(Bridge Engineering Department, Civil Engineering School, Southwest Jiaotong University, Chengdu, Sichuan Province, China.)
Deshan Shan (Bridge Engineering Department, Civil Engineering School, Southwest Jiaotong University, Chengdu, Sichuan Province, China.) Qiao Li (Bridge Engineering Department, Civil Engineering School, Southwest Jiaotong University, Chengdu, Sichuan Province, China.) Feilong Nan (Bridge Engineering Department, Civil Engineering School, Southwest Jiaotong University, Chengdu, Sichuan Province, China.) |
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Medium: | Tagungsbeitrag | ||||
Sprache(n): | Englisch | ||||
Tagung: | IABSE Conference: Structural Engineering: Providing Solutions to Global Challenges, Geneva, Switzerland, September 2015 | ||||
Veröffentlicht in: | IABSE Conference Geneva 2015 | ||||
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Seite(n): | 636-643 | ||||
Anzahl der Seiten (im PDF): | 8 | ||||
Jahr: | 2015 | ||||
DOI: | 10.2749/222137815818357683 | ||||
Abstrakt: |
In order to carry out the continuous modal parameter identification, temperature plays a vital role to effect the modal parameters identification process, therefore to investigate the temperature effect on modal frequencies is of extreme importance. For this purpose Sutong bridge a long span cable stayed bridge, having a main span of 1088m was selected as a case study, then the temperature effect was investigated on the real life data obtained from Sutong bridge. Furthermore continuous modal parameter identification was carried out using covariance driven recursive stochastic subspace identification (CO-RSSI), specially keeping in view the temperature effect on the natural frequency of cable stayed bridge and it was revealed form the analysis that there exist a positive correlation between the identified frequency and temperature. The results obtained provides very useful information and will prove to be very effective in bridge health monitoring specially for dealing with the temperature effect on continuous long term operational monitoring. |