As traffic loads increase and bridges age the need for structural health monitoring is growing. With the digitalization of our society, new non-contact full-field measurement techniques have been developed. These techniques have the potential to be used in monitoring of existing bridges. Today visual inspections are carried out every sixth year. These only give a rough estimate of the structure's health and only provide information about the surface of the structure. In addition to these inspections, traditional sensors like linear variable differential transformers and strain gauges are used to measure parameters such as displacement and strain. For existing bridges in reinforced concrete it is especially important to monitor reinforcement strains, as high strains could be indicative of overloading of the structure or even that a failure is about to occur. The methods available to measure reinforcement strain in existing bridges today are not very effective and have some limitations. The aim of this thesis is thus to evaluate the possibility to predict reinforcement strain based on surface strain measurements obtained by a non-contact full-field optical measurement system. In this study the software ARAMIS was used to measure surface strains, and traditional strain gauges were used to measure reinforcement strain. Strain distribution were evaluated at the initiation of cracks, during sections of cyclic loading and at a load close to the yielding point of the reinforcement. A correlation factor between the strain registered in the software and the strain obtained from the strain gauges was introduced. Based on the results in this study it is not possible to predict exact reinforcement strain based on surface measurements. Digital image correlation does however show potential to be used as a non-contact full-field measurement technique for in-situ measurements. Before this is reality there is still a need for further research in this area.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-70090 |
| Date | January 2018 |
| Creators | Lindmark, Jenny |
| Publisher | Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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