Bridging a tech gap: How smart sensors can help defective bridges

When the 52-year-old Ponte Morandi bridge collapsed during a torrential rainstorm in Genoa, Italy in 2018, the catastrophe claimed the lives of 43 people.

The suspected cause of the collapse was corrosion and deterioration and highlighted the structural health challenge of other ageing bridges around the world.

The aftermath of the collapse of the Ponte Morandi bridge in Genoa, Italy in 2018. Credit: AdobeStock

The Ponte Morandi bridge was replaced by the San Giorgio bridge almost two years later. Credit: AdobeStock.

While bridges are vital for economic and social growth, it is expensive to monitor their structural deterioration: the Australasian Corrosion Association estimates the annual cost of maintaining Australia’s bridges is $8 billion.

Yet there is an urgent demand for technologies that can accurately provide an assessment of a bridge’s condition.

A large number of bridges in Australia are more than 50 years old, requiring regular inspection and maintenance.

The NSW Smart Sensing Network (NSSN) Grand Challenge project has now developed smart fibre optic sensors which can monitor corrosion in concrete structures and help extend the service life of a bridge.

The Project’s Chief Investigator and Australian Research Council (ARC) and DECRA Fellow at the University of Sydney, Dr Ali Hadigheh says the high-performance fibre optics are cost-effective and can check for strain, cracks and corrosion in reinforced concrete bridges.

“There are many bridges in Australia that are exposed to harsh conditions such as salty water and temperature fluctuations which, in some cases, can lead to severe deterioration,” Dr Hadigheh says.
 
“Increasing traffic load, rising sea levels and increased atmospheric CO2 due to climate change are all exacerbating structural deterioration, highlighting the need for continuous health monitoring of bridges.”

He says early detection of steel corrosion in reinforced concrete structures can enable early, efficient, and cost-effective interventions.

“Our sensing technology and machine learning models enable accurate and early detection of defects in reinforced concrete bridges using only a single fibre Bragg gratings (FBGs) sensor, reducing the cost and simplifying the data analysis process,” Dr Hadigheh says.

“A fibre Bragg grating is like a tiny mirror inside an optical fibre that reflects only a specific wavelength of light. It can be used to measure strain, temperature, or pressure in structures like bridges or pipelines by detecting changes in the wavelength of light reflected.”

The Grand Challenge project team also tested the fibre optic sensors in a digital model of a concrete bridge.

The sensor prototypes were found to be capable of capturing and modelling reliable structural analytics in real-time.

The outcomes have been published in the journal Structures.

The unique digital model is now being used as a teaching resource in a University of Sydney Civil Engineering course, with hopes that it will be rolled out to university students across Australia.

The NSSN Grand Challenge project was a collaboration between researchers from Civil Engineering, Physics, Mechanical Engineering, and Material Science from two universities: the University of Sydney and UNSW, and industry partner Transport for NSW (TfNSW).

The smart fibre optic sensors will be tested on the Oyster Channel Bridge (pictured) at Yamba in Northern NSW this year. Credit: TfNSW

NSSN Natural Hazards & Smart Cities Theme Leader Peter Runcie says the project is an excellent example of the type of project that the NSW Smart Sensing Network supports through its annual Grand Challenge Fund.

“The fund requires the participation of at least two universities which builds relationships in the research sector and brings more research capability to bear,” Mr Runcie says. 
“By matching industry project funding, we ensure there is a strong focus on impact.”

TfNSW Senior Bridge Engineer Dr Hamid Fatemi says it is exciting to be supporting the project through real-world testing capabilities.

“TfNSW is hoping to trial the NSSN’s technology this year through a real-time corrosion data acquisition system on the Yamba Road bridge, which spans the Oyster Channel in northern NSW,” Dr Fatemi says.

“When the bridge next undergoes maintenance work, we’re aiming to install fibre optics in the reinstated concrete to collect raw data from the corrosion state of the structure for artificial intelligence analysis, via machine learning, such as reinforcement steel corrosion potential.

“The outcome of this testing could be used to develop future Building Information Models (BIM) and create future 3D digital replicas (digital twins) of existing bridges and structures in our transport network – using the AI technology to display corrosion or structural conditions in the real time – as and when it occurs.”

Next steps

The NSSN project team has been collaborating with chemists to create intelligent and highly sensitive coatings for fibre optic sensors, which will hopefully be ready to be used by TfNSW in the Yamba Road bridge.

The aim is for the coated fibre optic sensors to directly monitor moisture, corrosion and chemicals surrounding steel reinforcement in the bridge. 

TfNSW is looking to develop a learning-assisted sensing system, which will help with structural health monitoring (SHM) on site.

Diane Nazaroff