When will the bridge collapse? Can it still hold all the traffic passing by? There is a big windmill park going to be build next year, how will that affect the remaining lifespan? What is the optimal maintenance plan?  

We are blessed with a dense infrastructure network in the Netherlands. These constructions were once designed and built based on assumptions about material properties and traffic conditions that were appropriate for that time.  

But modern times show increasing traffic intensity. Heavier vehicles driving faster and closer together. Combined with uncertainties in material behavior this results in an unprecedented workload for the coming years as a consequence. This calls for technological breakthrough in the way we approach the replacement and maintenance of these large infrastructural structures.  

The problems with current bridgemonitoring

At this point in time most bridges are maintained time based. They are inspected anually, maintained following a schedule that is based on models and updated when inspections show a divergent deterioation process. This leads to sudden reactive corrective measures, closing lanes, reducing speed or having engineers present to repair on the spot.

• Degradation processes are not well known
• Only periodic assesment
• Data quality (availiability and accuracy)
• Relieability (Drift)

What about wireless sensors?
Problems with drift. These challenges include but are not limited to powering the system and therefore harvest energy, limited communication bandwidth and range, data loss, time synchronization, and signal length. Note that in the context of this review paper, synchronization is separate from drift.

Robust sensing system

Studies show that the loss of stiffness in any given structural component is concidered by many a relieable indicator of damage. This can be done by measuring the irregularities in the deflected shape of the structure. Using sensors with a high spatial resolution, high quality measurements and relieable signal processing.

Advantages of photonics based sensing:

• Easy to cover large distance
• 24/7 data
• Great dynamic range
• Low energy consumption
• No energy needed on sensing location (passive sensing)
• Flexible both in form and application
• Instinsically safe

What should be measured?

There are several parameters that should be measured to predict the remaining lifetime of a steel bridge:

Corrosion rate
The rate at which the steel in the bridge is corroding should be measured to predict how much longer the bridge can withstand the wear and tear of the environment.

Structural integrity
The condition of the steel beams, girders, and other structural components should be inspected and measured to ensure that they are still strong enough to support the load of the bridge.

Load-carrying capacity
The amount of weight the bridge can safely support should be measured to ensure that it can continue to handle the expected load.

Fatigue strength
The ability of the steel to withstand repeated loading and unloading should be measured to predict how much longer the bridge can withstand these stresses.

Deformations
The amount of deflection or bending in the steel components should be measured to ensure that they are not becoming too stressed or weakened.

Crack growth
Any cracks that are present in the steel should be monitored to predict how much longer the bridge can withstand these defects.

How can FBG-sensors contribute? 

FBG-sensors (fiber Bragg grating sensors) can contribute to the prediction of the remaining lifetime of a steel bridge by providing continuous, real-time monitoring of these parameters. These sensors can be embedded in the steel structure and provide accurate, reliable data on the condition of the bridge. This can help engineers to identify any potential issues before they become major problems, allowing for timely repairs and maintenance.

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