How 2400 sensors and machine learning models keep Sydney Harbour Bridge spanning the decades

Edge computing and robots transforming the maintenance regime of “the old matriarch of Sydney Harbour”

Factors like the weather and temperature have a significant effect on steel, on really hot days the bridge can expand and become up to 10cm taller than usual.

“Temperature effects are a challenge as it changes the way the bridge vibrates,” says Mann.

These variables are included in the training of the machine learning model so it can account for them.

“The beauty is you can keep adding other factors in there. We eliminate variability due to seasons or the day,” Runcie adds.

The machine learning models are being constantly refined by Data61, which is now exploring clustering techniques to further improve accuracy and predict faults.

Work is also being done to incorporate the “ambient vibration” readings from the bridge. These measurements are taken when the bridge is carrying no significant load, which happens only two times a year: when the bridge closes for the Sydney Marathon and on New Years Eve for the firework display.

When refined and updated, the models are pushed back out to the under arch units.

As well as the sensor system, RMS’ Sydney Harbour Bridge crew utilise a fleet of robots to work on the structure.

CROC – developed in collaboration with the Centre for Autonomous Systems at UTS – has magnetic feet and wriggles through the inside of the bridge “like an inchworm” capturing high definition video. Inspectors view the video feed and make an assessment of the paint and steel condition from the comfort of their office.

“There are more than seven kilometres of tunnels inside the arches with hundreds of portholes to climb through and many of our maintenance workers can’t fit through. They are like wombat holes and you are on your hands and knees to get around. It is a very difficult place for humans to work but ideal for robots,” says Mann.

There are also two grit-blasting robots in use – also developed at UTS – named Sandy and Rosie. The bots are able to autonomously sense and map a steel structure, and then plan a collision-free grit-blasting pathway.

“Field robotics is a growing opportunity,” adds Mann. “Robots on production lines have been around for decades, but robots that can think for themselves and undertake high risk mobile activities on construction sites are the way of the future.”

All hands on deck

The crews looking after Sydney Harbour Bridge now keep check on all of the 800 arches using a web-based interface.

“Inspections are now done 24/7 on the full length of the deck by the sensor system and alarms are automatically generated via email and SMS,” says Mann.

There is the odd false alarm, Mann adds, “sometimes the installation of painting platforms will trigger a notice”.

Maintaining civil infrastructure is a costly but essential responsibility of governments around the world. Moving to a more predictive maintenance regime can save time and money and gives crews the ability to plan and budget ahead.

“We know in Australia and in most countries the amount of resources available to maintain these assets is less than is needed. It means agencies need to be smarter about how they manage the assets,” Runcie says.

As a result of Data61’s technology, RMS has changed its approach to maintenance.

“Early detection of any defects allows early maintenance intervention to fix the problem with less effort and expense. Such technology pays for itself and mitigates potential disruption to the travelling public. Computing power enables us to be proactive, rather than reactive, in managing the Bridge condition – so we do maintenance more frequently as a result but the task is smaller,” Mann says.

The agency added that the technology could be rolled out to other parts of the bridge deck.

“It is a risk management tool and is deployed where the likelihood or the consequence of a defect justifies the investment,” Mann says.

Nevertheless, manned inspections will continue into the foreseeable future, Mann adds: “The system is an effective diagnosis tool but not a substitute for human inspections.”

@georgepnott

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