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Two Decades of Reliable Structural Health Monitoring
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Two Decades of Reliable Structural Health Monitoring

The structural health monitoring system on the 25 de Abril Bridge demonstrates how long-term monitoring, continuous system evolution and advanced data acquisition technologies work together to ensure safety, reliability and efficient operation over decades.

A Bridge Engineering Masterpiece

Spanning the Tagus River, the 25 de Abril Bridge links Lisbon with Almada. Opened in 1966, this iconic suspension bridge extends 2.3 kilometres, with a main span of 1,013 metres and two side spans of 483 metres each. A stiffening truss carries six lanes of road traffic on the upper deck and two railway lines on the lower level. The rigid beam design is suspended by 1,344 vertical hangers and supported by four main cables. Often compared to the Golden Gate Bridge due to its connection with the American Bridge Company, it is a clear example of infrastructure where reliability, safety, and long-term performance are essential.

Red suspension bridge spanning a wide river with traffic crossing, viewed from above with a city in the background.
The 25 de Abril Bridge in Lisbon, Portugal

The Need for Structural Health Monitoring

As traffic volumes increased and the bridge underwent major upgrades, the structural demands on the 25 de Abril Bridge rose significantly, making advanced structural health monitoring essential. The 1999 expansion added extra road lanes and a rail deck, placing the structure in a new operating regime. To address this, a continuous monitoring system was introduced to closely track structural behaviour. This permanent SHM system has been in operation for over two decades, providing real-time, high-quality data and enabling engineers to actively safeguard the bridge’s performance, safety, and long-term durability.

Reliable, decentralised DAQ for long-term Structural Monitoring

The SHM system was originally built on Gantner Instruments’ e.bloxx data acquisition (DAQ) platform, designed for long-term structural monitoring of critical infrastructure. A network of 210 sensors is connected to 13 synchronised, decentralised DAQ sub-systems distributed across the bridge. This decentralised measurement approach places signal conditioning close to the sensors, minimising analogue cabling and ensuring high data quality. The system supports multi-frequency data acquisition, combining strain gauges, MEMS accelerometers, inclinometers, displacement sensors and temperature sensors to capture both static and dynamic behaviour. Fibre optic communication and GPS time synchronisation ensure accurate, high-resolution data across the entire structure.

Data Acquisition Systems installed on 25 de Abril Bridge
Data Acquisition Systems installed on 25 de Abril Bridge (Source: LNEC)

Future-Proof SHM with Q.bloxx Upgrade

Over more than 20 years of continuous operation, the system has proven its reliability in long-term bridge monitoring. It enables early detection of structural changes, supports predictive maintenance strategies and helps asset owners reduce lifecycle costs while improving safety. This successful deployment demonstrates how robust DAQ systems are essential for effective structural health monitoring of bridges and other critical infrastructure.

To ensure future readiness, the system is now being upgraded to Gantner Instruments’ Q.bloxx data acquisition platform. This upgrade follows a backward-compatible design strategy, allowing existing SHM systems to evolve without disruption while integrating advanced data processing, higher performance and enhanced scalability. With this transition, the 25 de Abril Bridge continues to set a benchmark in long-term structural health monitoring, providing civil engineers and asset owners with a proven solution for maintaining the safety, reliability and performance of complex infrastructure over decades.

Designed for autonomous operation, the system functions as a standalone DAQ with automatic power-on capability, operating independently of a PC while managing all critical tasks, including data processing, local storage, and buffering, to guarantee continuous, reliable monitoring throughout the construction process.

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