Any cost efficient assessment, maintenance and strengthening process requires specific information about the current condition state of a structure. Currently, this information is mainly provided by visual inspections. However, the aging of the bridge population demands for an increasing inspection effort producing considerable costs. Furthermore, most of the time, periodical visual in spections do not provide up to date information about the condition state of bridges. This yields an increasing demand for more rationalized, autonomous and continuous inspection technologies.
Continuous monitoring with physical sensors has the potential to provide up to date information. Furthermore, it furnishes information about processes which changes in time like live loads, fatigue damage, vibrations, temperature etc. which are difficult to assess using other methods. However, to achieve this goal at reasonable prices, a significant effort is needed to standardize the monitoring process with regard to data acquisition, analysis and management. A key feature of any effective monitoring system is its ability to perform autonomously a diagnostic of the state of health of a bridge. This offer the potential to perform inspections on demand, reducing significantly the inspection costs.
The goal of continuous monitoring is not to supersede traditional inspection but to optimize the inspection process with modern smart tools. This allows increasing the reliability of the obtained information, to reduce the human intervention as far as possible and to improve the benefit costs ratio. Civil engineering structures are mainly large and complex physical systems consisting of many heterogeneous components. A monitoring of all components with sensors is economically and technologically not feasible. Therefore, the monitoring process has to be restricted to a limited number of components. This can be achieved by identifying simple condition indicators and assessing these indicators by measurements.
The objective of the Work Package 5 is to develop and test an innovative, reliable and cost-effective technology for continuous monitoring of railway bridges. To achieve this goal, four key topics will be addressed.
A guideline which defines a monitoring methodology addressing the specific needs of railway bridges. A guideline is essential to simplify and speed-up the planning and implementation of a monitoring system at sustainable costs. This methodology specifies the data acquisition, analysis and management process to cover the information demand which is needed to sustain an up to date assessment of the state of serviceability and safety of railway bridges. To be economically feasible, the monitoring process has to be restricted to as few structural elements as possible. The selection of these components and the sensor location has to be dictated by the objective to provide at any time a fast and reliable estimate of the state of health of a railway bridge.
Special efforts will be made to develop novel optical fibre and MEMS-sensors. For applications in railway bridges optical fibre sensors are very attractive because of their high immunity to electromagnetic fields, their long term stability and their robustness in harsh environments. Micro-Electro-Mechanical-Systems (MEMS) are the first choice if there is a need for cheap, robust and small sensors. Monitoring systems with cheap sensors are essential for to be accepted by the industry. The activity is focused on the development of
a novel sensor sheet with embedded optical fibre sensors, able to detect, localize and monitor the opening of several cracks with just a single fibre
an optimized fibre optic Bragg grating sensor system for strain measurement on large structures
an array of MEMS-sensors to track defects in terms of crack formation and propagation in concrete at real time using acoustic emission techniques.
A reliable, scalable, flexible and time synchronized local area communication infrastructure between sensors and data acquisition system. The communication infrastructure is based on a wireless local area network and has to support various physical sensors distributed over a wide area. Wireless sensor networks are appealing because on large and medium size bridges they are more economical than laying kilometres of conduits. This reduces significantly the installation costs of a monitoring system. In some applications, cabled sensors are impractical or produce high maintenance costs due to man-made or natural causes. The close sensors building the nodes of this network are equipped with data conditioners and analogue to digital converters to digitalize the sensor signals.
A computer-aided automatic smart data processing tool. Automatic data processing is a key feature for a successful data management of a continuous monitoring process. The measurement of dynamic processes produces a large amount of data which has to be significantly reduced to be useful for further processing. The data reduction is done by a smart continuous analysis of the acquired data. This analysis is supported by an autonomous diagnostic and fault-detection methodology. To be able to detect abnormal state conditions, this methodology has to consider the effects of changing ambient and operational conditions on structural behaviour.
WSP ConsultingKORTES group
University of Oulu
Rheinisch-Westfälische Tech Hochschule
Wroclaw University of Technology
Universidade do Minho Portugal
Luleå University of Technology
Materials Testing and Research (EMPA)
City University London