Filtern
Erscheinungsjahr
Dokumenttyp
- Beitrag zu einem Tagungsband (24) (entfernen)
Referierte Publikation
- nein (24) (entfernen)
Schlagworte
- Non-destructive testing (4)
- Concrete (3)
- Debonding (2)
- Inspection (2)
- Monitoring (2)
- Non-Destructive Testing (2)
- Ontology (2)
- RSSI (2)
- Acoustic emission (1)
- Active thermography (1)
Organisationseinheit der BAM
Opportunities and limitation of non-destructive testing in condition assessment of bridge structures
(2009)
The amount of new knowledge about bridges, materials they are made of, deterioration processes for the different materials, resulting defects, methods for early detection of them and related causes for damage increases day by day. Often the knowledge remains in the heads of ageing specialists leaving the inspection teams or universities. This paper presents a feasibility study about application of a new tool from artificial intelligence to model and organize bridge engineering knowledge from a domain expert´s view. Exemplarily, knowledge and not only data from bridge testing in the field and in the laboratory were formalized for the presentation of the functionality of ontologies.
Cast iron arch bridges were built in the late 18th and early 19th century across Europe. After the famous Iron Bridge in the Ironbridge Gorge in Coalbrookdale in England, being now part of the UNESCO world heritage, many cast iron bridges followed and substituted timber bridges. A series of cast iron bridges has been built in central Europe, in Laasan, Breslau, (now Wrocław), in Berlin, Potsdam, Bad Muskau and Schwerin. The paper gives an overview about the current state of some remaining cast iron arch bridges, typical damage cases, material properties and rehabilitation. Most of the old cast iron arch bridges serve as pedestrian bridges. Some of these bridges have been strengthened to increase the traffic load. Different rehabilitation measures as substitution of parts of the bridges and strengthening using Carbon Reinforced Polymers (CFRP) are discussed.
Berlin Main Station is the largest multi-level station in Europe. Its daily passenger number amounts to over 300.000. Structures built for such a large number of people require a high-level safety standard. The station was built on the inner city site of the historic Lehrter Bahnhof. The conditions for building and start of operation were challenging by several reasons. The typical sandy ground with a high level of groundwater makes the permanent static stability of such a complex structure difficult. Several completed, ongoing, and planned construction activities in the immediate vicinity of the station influence the ground settlement of the whole area. On basis of the structural design an impact prediction was calculated, which expected certain vertical displacements particularly between the single columns of the outer concrete bridges of the building. These columns support the glass roof construction, which only allows a defined limit of displacement. In order to avoid damage, a concept for monitoring and adjusting potentially occurring displacements was developed for installation at the outer bridges of the station.
Structural health monitoring contributes to early damage detection in the built infrastructure. During the last two decades, the sensor networks transferred from wired to wireless sensor networks.
Several methods exist to measure moisture in building materials. Most of the introduced commercial humidity measurement methods as provide information about the local or near surface moisture. A feasibility study is presented to demonstrate, how the Received Signal Strength Indicator (RSSI) of a BlueTooth® Low Energy (BLE) signal, transmitted from the BLE-module embedded in building materials with changing moisture content. The BLE-module communicates with a mobile Smart Device as tablet or mobile phone. The RSSI indicates to what extend the received signal strength is changed due to moisture, while the transmitted signal strength remains constant.
The amount of new knowledge about bridges, about the materials they are made of, deterioration processes for the different materials, typical defects, methods for early detection of them and related causes for damage increases day by day. Often the knowledge remains in the heads of ageing specialists leaving the inspection teams or universities. This paper presents a feasibility study about application of a new tool from artificial in-telligence, ontology, for modeling and organizing bridge engineering knowledge from a domain expert´s view. Exemplarily, knowledge and not only data from bridge testing in the field and in the laboratory were formalized for the presentation of the functionality of ontologies. The open source ontology editor Protégé was ap-plied to test the feasibility.
The presented development of a damping model is a research component of an experimental feasibility study about moisture in building materials measured with Bluetooth® Low Energy (BLE) signals. This study may be part of a structural health monitoring aiming on early damage detection in the built infrastructure and is increasingly focusing on wireless sensor Network technology. It is investigated, how the Received Signal Strength Indicator (RSSI) of a BLE signal, transmitted from the BLE-module embedded in building materials with changing moisture content is damped. The BLE-module communicates with a mobile Smart Device as tablet or mobile phone via 2.45 GHz-ISMfrequency band where water dipoles start to oscillate. If the BLE-signal transfers through a moist material, the moisture Content influences the RSS-Indicator. The damping model demonstrates this damping effect on RSSI by the abstraction of the reality observed in a real system.
In this research, laboratory experiments were carried out to investigate the feasibility of using ground penetrating radar (GPR) for corrosion detection and/or monitoring, and the mechanism of corrosion caused GPR signal changes, taking into account the influence of several parameters: Chloride, rebar size and cover depth. With the understanding of the mechanism, a novel method for detecting reinforcement corrosion in concrete with GPR is proposed, together with a series of signal processing toolkits for corrosion visualization and image comparison.