Case Study: Overloaded Vehicle Monitoring of a Heavy Vehicle Overpass

Concerned with potential overloading of the pre-stressed concrete girders on a road bridge in QLD, Rockfield was engaged to install a strain gauge based heavy vehicle monitoring and classification system.

After completing an engineering assessment on a heavy vehicle overpass, load restrictions were enforced on the bridge to limit the passage of vehicle that are at high risk of damaging the structure. After enforcement of the load restrictions, it was suspected that overweight vehicles were still utilising the overpass without authorisation, posing an asset integrity risk to drivers and the asset owner.

The asset owner engaged Rockfield to provide an overloaded vehicle monitoring system to capture information on vehicles exceeding their permitted weight limits.

To avoid installation of a costly weigh in motion system within the bridge deck, Rockfield proposed a contactless overloaded vehicle monitoring solution using strain gauges on the underside of bridge girders. 16 high precision strain gauges were installed via epoxy bonding to avoid drilling into the pre-stressed units, and live vehicle traffic loads were captured and transmitted to an online dashboard service. An automatic number plate recognition (ANPR) camera was also commissioned and installed to provide confirmation of the overloaded vehicles and allow identification.

To calibrate the monitoring system, a series of load tests were conducted using a vehicle of known axle mass. The load testing provided a reference range for normal and abnormal vehicle load conditions, allowing Rockfield’s cloud platform to isolate and detect any potentially abnormal and overloaded vehicles. Alongside the strain data, vehicle speeds were calculated and provided to the client.

Rockfield’s online dashboard service was configured and provided to the client to be able to log in and view videos of the overloaded vehicles, access monitoring data, and interrogate key metrics. Email alerts were also configured so that the client is notified whenever a potentially overloaded vehicle traversed the bridge.

Regular reports were also issued, summarising key events over a given period, and providing more in-depth custom analytics refined in consultation with the client.

Typically, weigh in motion systems used to detect overweight vehicles are an expensive ordeal that requires excavation of the road base. By using high precision strain gauges Rockfield is able to provide a monitoring system that can alert asset owners of unauthorised or overloaded vehicles with minimal downtime and civil works. Alongside the vehicle monitoring, the strain data captured by the system can be used for further engineering analysis of live loads to review and adjust load limits in the future.

Through Rockfield’s cloud-based data platform, AI/ML models and statistical analysis can be leveraged to classify vehicles and provide high level insights into what kinds of vehicles are traversing the structure, and how each vehicle type causes different loading behaviour. Combining field strain data with on-site video, Rockfield have specially trained AI models that can classify vehicles into distinct classes, count axle groups and axle configurations, and track vehicle position as it traverses the bridge.

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