Thesis (MEng)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: Bridges are amongst the most important structures of any highway network. Once the bridge construction is complete and a bridge is put into service, it is subjected to deteriorations. An effective condition assessment, as a component of bridge management system, is therefore necessary to keep bridges in admissible conditions of safety and serviceability. In South Africa, some bridge authorities do not have sufficient funds to carry out bridge inspections at required intervals. In the case where bridge authorities have enough funds, a systematic inspection is performed, covering a number of bridges that are not in need of inspection. Inspection and maintenance for a limited number of bridges randomly chosen may result in an increase of the number of bridges in critical conditions. A bridge inspection prioritisation method that takes into account the need of inspection of bridges is therefore needed for South African highway bridges. This research provides a prioritisation method for concrete bridge inspections by integration of nonprofessional inspectors, imagery inspection and deterioration models. To achieve the research objectives of this study, a literature study has been carried out to understand bridge inspection practice in general and South African practice in particular. The literature helped also to identify previous works on bridge inspection prioritisation, the use of information from informal sources, imagery inspection and involvement of non-professionals in bridge inspection and use of deterioration models in bridge management. A survey has been conducted amongst South African bridge authorities in order to fill the literature gaps. Inventory and inspection data of bridges managed by South African National Roads Agency Limited (SANRAL) was used to develop a deterioration model by considering bridge characteristics such as bridge age, number of spans, and bridge type. Based on the literature review, results of surveys and estimated regression parameters, a bridge inspection prioritisation method has been developed. This method comprises three phases. The first phase is the initial screening that consists of an identification of bridges with critical defects that have not been repaired yet. These bridges, to which are added bridges that have not been inspected in the previous inspection, constitute the first inspection priority category. The second phase is an imagery screening which is an analysis of digital photographs for detection of defects that need urgent assessment by professional inspectors. The analysed photographs are taken by non-professional inspectors and uploaded to the Bridge Management System. The third phase is a grouping of bridges in inspection priority categories as a function of their physical characteristics and deteriorating factors using deterioration modelling. The method has been applied on SANRAL bridges using inspection ratings of 2011-2012. 422 SANRAL bridges have been categorised in the first inspection priority group by considering hydraulic related defects as critical. The third phase allowed to rank 522 possible combinations of bridges based on their characteristics. The developed method would help bridge authorities where inspection budget is limited, to prioritise bridge inspection as a function of needs of inspection. / AFRIKAANSE OPSOMMING: Brûe is ʼn belangrike deel van enige snelweg netwerk. Wanneer brugkonstruksie voltooi is en dit in diens gestel word, is die brug onderhewig aan skade en verval . 'n Doeltreffende toestandsassessering, as 'n komponent van ʼn brug bestuurstelsel, is dus nodig om brûe in ʼn toestand van veiligheid en diensbaarheid te hou. In Suid-Afrika het sommige brugowerhede nie genoeg fondse om bruginspeksies teen vereiste intervalle uit te voer nie. In die geval waar ʼn brugowerhede wel genoeg fondse het, word stelselmatige reekse inspeksies uitgevoer, waar brûe wat nie lukraaknoodwendig op daardie stadium inspeksie nodig het nie, ook soms ingesluit word. Inspeksie en onderhoud vir slegs 'n beperkte aantal brûe wat gekies word kan 'n toename veroorsaak in die aantal brûe wat in ʼn kritiese toestand is. 'n Bruginspeksie prioritiseringmetode wat brûe identifiseer vir inspeksie is dus nodig vir Suid-Afrikaanse brugowerhede. Hierdie navorsing stel 'n metode voor wat bruginspeksies prioritiseer deur gebruik te maak van nieprofessionele inspekteurs, inspeksie van foto’s en brugtoestandsvervalmodelle. Om die navorsings doelwitte van hierdie projek te bereik, is 'n literatuurstudie uitgevoer oor die praktyk van bruginspeksie in die algemeen, en meer spesifiek om die praktyk in Suid-Afrika te verstaan.. 'n Opname is voorts onder Suid-Afrikaanse brugowerhede uitgevoer om gapings in die literatuur aan te vul. Inventaris en inspeksie data van brûe wat bestuur word deur die Nasionale Padagentskap (SANRAL) is daarna gebruik om 'n toestand agteruitgangsmodel te ontwikkel deur die eienskappe soos brug ouderdom, aantal spanne en die tipe brug in ag te neem Gebaseer op die literatuur, resultate van opnames en beraamde regressie parameters is 'n brug inspeksie prioritiseringsmetode ontwikkel. Hierdie metode bestaan uit drie fases. Die eerste fase is die aanvanklike siftingsproses wat bestaan uit die identifisering van brûe met 'n kritiese defek wat nog nie herstel is sedert ʼn vorige inspeksie nie. Hierdie brûe, wat ingesluit word by ander brûe wat nie geïnspekteer was in die vorige inspeksie nie, is die eerste kategorie van inspeksie prioriteit. Die tweede fase is 'n ontleding van digitale foto's vir die opsporing van defekte wat dringende assessering deur professionele inspekteurs nodig het. Die foto's word geneem deur nie-professionele inspekteurs en dit word gelaai op die brug bestuurstelsel. Die derde fase is die groepering van brûe in inspeksie prioriteit kategorieë as 'n funksie van hul fisiese eienskappe en vervalfaktore met die hulp van agteruitgangsmodelle. Die metode is toegepas op die SANRAL brûe met die hulp van inspeksie graderings van 2011-2012. Deur die aanname van hidrouliese defekte as van kritiese belang, is 422 SANRAL brûe in die eerste inspeksie prioriteit gegroepeer. Die derde fase prioritiseer 522 moontlike kombinasies van brûe op grond van hul fisiese eienskappe. Die metode sal brugowerhede waar inspeksie begrotings beperk is, help om bruginspeksies te prioritiseer as 'n funksie van die noodsaaklikheid van inspeksie.

Identifying damage of a bridge from a vehicle moving over it is an attractive idea especially for those bridges without structural health monitoring systems as it is faster than putting sensors on the bridges. Many parts of highways and railways have been constructed on bridges and it is important to ensure that they are in good conditions. Therefore a large amount of bridges need to be monitored and for the sake of economy the monitoring should be efficient. If an instrumented vehicle can identify the occurrence and locations of damage by running over the bridges, it would save a lot of labor and time. As acceleration is easier to acquire, it is used as the main signal for damage detection. Research in this area is relatively little, not to mention the need to take into account road surface roughness and experimental verification. Frequencies can be conveniently extracted from the vehicle response. The damage can hence be identified based on the relationship between the change of frequencies and the fractional change of strain energy. A vehicle-bridge interaction system is used to simulate the process of a vehicle running over a bridge and obtain the vehicle response for investigation. The proposed method can identify damage of simply supported and multi-span continuous bridges taking into account road surface roughness and measurement noise. They are also validated in the laboratory where a simply supported bridge is modeled using an aluminum beam and the vehicle is modeled with aluminum vehicles. This method can limit the damage location to two potential locations. The multi-level multi-pass strategy makes use of the identification from the above method, applies genetic algorithm and lets the vehicle run over the bridge at various speeds. The unique damage location can then be identified. A numerical study for simply supported bridges and multi-span continuous bridges has verified its effectiveness. Continuous wavelet transform (CWT) can identify local changes in a signal as damage is assumed to cause local change to the vehicle response, which makes it suitable for damage detection from vehicle response. However, the road surface roughness and measurement noise often mask the information about damage. Smoothing technique and damage indicators are proposed to help with the identification. By validating the method with a numerical vehicle-bridge interaction system and model tests in the laboratory, the damage can be correctly identified. Additional masses and sinusoidal excitation force can help with the identification too. Repeated application of CWT involves applying the CWT to the coefficients of continuous wavelet again and again, which can also improve the results. If CWT is treated as a mathematical microscope, repeated application of CWT is like amplifying the signal several times. The effectiveness of the method has been verified numerically and experimentally. In summary, a convenient and efficient technique to test the conditions of bridges by putting sensors on a moving vehicle is proposed and the method is verified by numerical and experimental studies. It can provide an alternative or a useful complement to conventional structural health monitoring systems. / published_or_final_version / Civil Engineering / Doctoral / Doctor of Philosophy

Most existing structural health monitoring (SHM) techniques are based on measured acceleration data. Such practice, however, is highly expensive to operate, mainly due to cumbersome, time-consuming and expensive installation of sensors and their data acquisition systems. As an emerging noncontact method, the vision-based displacement sensor systems have attracted significant research interests and offered a promising alternative to the conventional sensors for SHM. However, most existing vision-based sensors require physical access to the structure to install a predesigned target panel, which has a higher contrast and thus is easier to track. Besides, most studies are carried out in controlled laboratory environments. The accuracy and robustness of vision sensors in the outdoor field conditions have not been fully investigated. It is also noted that current researches are mainly focusing on the measurement performance evaluation of vision sensors, without discussing the use of the measured displacement data for SHM. This dissertation develops a high-precision vision sensor system for remote and real-time measurement of multipoint structural displacements by tracking natural targets on structural surfaces. Two sets of software packages are developed respectively based on two advanced template matching algorithms (i.e., the upsampled cross correlation and the orientation code matching) incorporated with different subpixel techniques. Comprehensive experiments, including laboratory shaking table tests and field bridge tests, are carried out to evaluate its performance. Satisfactory agreements are observed between the displacements measured by the proposed vision sensor and those measured by high-performance reference displacement sensors. Moreover, this study examines the robustness of the vision sensor against ill environmental conditions such as dim light, background image disturbance and partial template occlusion. This dissertation further explores the potentials of the vision sensor for fast and inexpensive SHM applications, by demonstrating the usefulness of the displacement data for experimental modal analysis, finite element (FE) model updating, damage detection, etc. For a three-story frame structure, the modal analysis shows that the obtained natural frequencies and mode shapes from displacement measurements by using one camera match well with those by using four accelerometers. In fact, the vision sensor can achieve smoother mode shapes which would make damage localization more accurate, while the resolution of mode shapes from accelerometers is limited by the sensor number. This has been demonstrated from the damage detection result of beam structures based on the mode shape curvature (MSC) index. To address the needs for monitoring aging railway and highway bridges, coupled train-track-bridge and vehicle-bridge FE models are firstly developed to study the dynamic interactions between bridges and moving trains/vehicles. Subsequently, a time-domain model updating approach for railway bridges is proposed based on the in-situ measurement of the bridges’ dynamic displacement histories by the proposed vision sensor. This dissertation further proposes a bridge damage detection procedure that utilizes vehicle-induced displacement response and the MSC index without requiring prior knowledge about the traffic excitation.