Moritz Rommel, summer semester 2013

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Introduction

Damage to or collapse of bridges leads not only to enormous economic damage but also puts human lives at risk. Influences on the load bearing capacity and traffic safety of bridge structures due to, for example, environmental impacts or increased traffic volume should therefore always be taken into consideration and monitored. One option is the structural health monitoring of bridges (the continuous monitoring) using suitable sensor systems.

Analysis methods

The choice of the analysis method is always based on a specific goal. This could be determined by setting a known state (e.g. maximum expansion, flexure or strain due to wind) and triggering of an “alert signal” when this is exceeded. Or different measurands can be set up at several strategic points of the construction and connected. The evaluated data could then be used, for example, as the basis for lifespan prognoses. The points in time that the signals are generated also have to be based on the goal. Signals can be collected at specific time intervals over a specific time period (discrete time measured data acquisition) or specifically, to determine the impacts of a certain event (event-based measured data acquisition). It is possible, that a specific event is recognized by the measuring system. [1]

Measurands

The optimal combination of different measurands, which have to be collected at the right point in time and with the right method, should have the best possible alignment with the goal. Many different measurands can be considered, e.g.:

Measurement systems

Several measurement systems can be used to distinguish the type of data collection, the data transmission and the data analysis. The first distinction is between wired and wireless systems. A significant disadvantage of wired systems is the cable run from sensor to the central computer. In the case of large bridge structures, in which several sensors are installed over the entire structure, many meters of cable are necessary and thus the cable management is probably effort-intensive and costly. It is better to use digital signals that are not particularly troublesome than analogous signals. For acoustic emission testing (AET) [2] and vibration analysis at bridges, sufficiently powerful computer components performance, storage capacity as well as an adequate power supply is required to cope with the corresponding data volumes. The data volume is often so large that from a practical point of view, only an event-based data acquisition is possible. In contrast, the collection of data from a single application such as the collection of relative air moistures has a very small data volume and thus is possible over long time periods [1].

Wired systems

Since the 1980s, field bus systems have been used. Further development of these systems consists of sending digital data via standardised protocols. Thus, it is possible to send information from several sensors using the same cable and the wiring effort was significantly reduced. Additionally, fibre-optic systems are used. These consist of an optical wave guide which often consists of glass. These methods can be divided into extrinsic methods where the fibre only serves as a transfer medium and intrinsic methods where the fibre itself is the sensor. Sensors for strain, temperature, acceleration, inclination and pore-water pressure can be developed with this technology. Fibre-optic sensor systems are very robust in relation to environmental impacts and electromagnetic fields. Due to their small size, low price and the ability to measure over long distances, fibre-optic systems are an interesting alternative to continuous monitoring with conventional sensors, in particular, in extreme environments [1].

Wireless systems

In this area, different sensors are used. For example, passive wireless sensors which have their own power supply and those which are supplied by the electromagnetic fields of a nearby reader. And further, active wireless sensors are used. These comprise, besides different sensors with their own power supply, a processor, storage and components for data transmission. A key criterion for all wireless sensors is a most possible extendable period of power supply. As radio transmission is a substantial energy consumer, the duration and intensity has to be kept as low as possible [1]. The use of very precise seismometers for modal analysis and acceleration sensors for the SEA is often connected to high costs. A promising technical development is known as the MEMS sensors [2]. Electrical and mechanical components can be placed on these small chips. In addition to low energy consumption, these sensors have the advantage that they are very cost-effective due to mass-production. In addition to moisture and temperature, such sensors can already be used in several other areas [1].

Fig. 1: Schematic diagram of monitoring a bridge with wireless sensor networks [1]

Wireless sensor networks

Relevant measurands are collected using sensor nodes (motes) at the desired locations of the bridge and likely saved and partially analysed. Motes send the evaluated information via radio to the computer host. The central computer saves the data and additionally serves for extended data analysis. Data can be sent from the central computer via a suitable interface (e.g. a GPRS/UMTS modem) to the person responsible for interpretation (see fig. 1). Several network topologies can be considered for sensor networks. Multi-hop topologies offer the possibility to send data to the engineer in charge using less energy [3]. Through collective connection of partial areas of the sensor network into so-called clusters, it is possible that because of the linking and analysis of several measurands in the cluster itself, only relevant data have to be transmitted via radio. Thus, power efficiency can be continuously enhanced (see fig. 2) [1]. Recently, wireless sensor networks have been described and successfully used in [2] and [4].

Fig 2: Example of a multi-hop sensor network with cluster formation [1]

Literature

  1. C. U. Große, M. Krüger (Hrsg.): Einsatz von Sensorik an Brückenbauwerken. FE 88.001/2009, Schlussbericht, (2010).
  2. C. U. Große, M. Krüger, D. S. Glaser (Hrsg.): Wireless Acoustic Emission Sensor Networks for Structural Health Monitoring in Civil Engineering. ECNDT–Tu.1.7.3 (2006).
  3. C. U. Große (Hrsg.): Arbeitsblätter im Rahmen der Vorlesung: Zerstörungsfreie Prüfung, Skript, Technische Universität München (2012).
  4. M. J. Chae, H. S. Yoo, Kim J.Y., M. Y. Cho (Hrsg.): Development of a wireless sensor network system for suspension bridge health monitoring. In: Automation in Construction 21 (2012), p. 237-252.

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