STRUCTURAL HEALTH MONITORING AND DIAGNOSTICS

Our company offers continuous real-time monitoring of the structural behavior of civil works and infrastructures, achieved through a proven system based on years of experience and patented methods that combine expertise in the field of structural engineering, cloud computing, state-of-the-art sensors, and advanced data analysis.

ANALYSIS

Possibility of Plus and/or Light equipment. Preliminary FEM modeling, analysis of damage scenarios, choice of Performance Indicators, sensor types, and measurement points, design of monitoring system

MONITORING

Model-driven and/or data-driven approaches. Continuous on-site and on-cloud control of monitoring system data. Engineering-structural analysis for defining threshold levels that activate automatic alerts.

DIAGNOSIS

Identification, interpretation, and structural diagnostics of anomalies found in data.

News and Events

STRUCTURAL DIAGNOSTICS
OUR METHOD

step one

Review of available documentation, integration of diagnostic and mechanical characterization campaigns
1
Studio della documentazione disponibile, integrazione di campagne diagnostiche e di caratterizzazione meccanica

step two

Preliminary FEM modeling, identification of damage scenarios, definition of Key Performance Indicators, sensor types, and measurement points.
2
Modellazione FEM preliminare, individuazione degli scenari di danno, definizione dei Performance Indicators,  della tipologia di sensori e dei punti di misura

step three

Design, production assistance, and installation of monitoring system.
3
Progettazione, assistenza in fase di produzione ed installazione del sistema di monitoraggio

step four

Performing static and dynamic load testing using controlled and properly purpose-built conditions, followed by updating the numerical model to finalize damage scenarios.
4
Prove di carico statiche e dinamiche in condizioni controllate,studiate ad hoc, e aggiornamento del modello numerico per la finalizzazione degli scenari di danno

step five

Definition of increasing gravity safety threshold levels.
5
Definizione di livelli di soglia per la sicurezza a gravità crescente

step six

Big Data Analysis and development of predictive models.
6
Analisi dei dati e sviluppo di modelli predittivi

step seven

Continuous detection of anomalies, data archiving in the cloud, and big data analysis.
7
Rilevamento in continuo delle anomalie, archiviazione dei dati nel cloud e big data analisi

step eight

Visualization of results on dedicated dashboard and periodic detailed reporting.
8
Visualizzazione dei risultati su Dashboard dedicata e reportistica periodica di dettaglio

STRUCTURAL HEALTH MONITORING
DENSE SENSING

Model-driven and data-driven monitoring with a capillary network of sensors permanently installed on the structure, ensuring robustness, reliability, and continuity of control. Distributed computational intelligence at each level of the monitoring system.

SENSOR-NODE LEVEL

  • Computational capacity at the sensor level
  • Variable and remotely adjustable sampling rate
  • Calculation of synthetic parameters
  • Different types of sensors in a single measurement point
  • Sensors remotely activatable and configurable

GATEWAY LEVEL

  • Intelligent signal acquisition
  • Continuous data transfer according to pre-established periodicity depending on the sensor
  • Transfer to the cloud of only significant and non-redundant information
  • Streaming transfer (all data) in case of anomalous events
  • Real-time pre-analysis and continuous comparison with threshold conditions
  • Autorecovery in case of malfunctioning anomalies

CLOUD LEVEL

  • Data and metadata archiving
  • Short and long-term analysis of data
  • Run of ad hoc structural algorithms
  • Periodic comparison with threshold conditions
  • Structural diagnostics and proactive maintenance support
  • Robustness against false alarms
Integrating smart sensors, diagnostics, structures, and expertise for a more intelligent network.

Insights &
Competitive Edge

Let's talk about numbers...
+25km (9 miles) monitored
+8highway operators
+8engineering skills
+150monitored structures
3locations
6prestigious universities partnering
+30tb of data
5patents
+6years of experience in monitoring
+40years of experience in structural engineering
+50employees
+3Ksmart sensors on tunnels
+11ksmart sensors on viaducts
+500spans
*Click on the highway name to view details of the monitored structures.
Autostrada A32 a32
Autostrada Comune Torino ct
Autostrada A6 a6
Autostrada A15 a15
Autostrada Roma-Firenze r-f
Autostrada A1 a1
Autostrada A21 a21
Autostrada A5 a5
Autostrada A24 a24
Autostrada A25 a25
Basicila di San Pietro - Roma SP

Some of our clients

portfolio

Case history
PEDESTRIAN STEEL FOOTBRIDGE WITH STAYED ARCH

The monitoring system has been specifically designed in terms of number and positioning of sensors to capture the complex dynamic response of the structure. By means of FEM modeling of damage scenarios, appropriate dynamic thresholds have been calculated for the continuous monitoring of the state of the stays and the evolution over time of the response of the footbridge deck.

UNREINFORCED CAST-IN-PLACE HIGHWAY TUNNEL
The monitoring system consists of 28 transverse measurement sections aimed at controlling the tensile and deformation evolution of the tunnel lining over time. The monitoring system, consisting of MEMS inclinometers integrated with post-installed local tension-deformation sensors within the lining, allows for both local and global monitoring of the structure's response. The diagnostics are complemented by nonlinear FEM modeling and a real-time alert service for any structural issues.
CONCRETE/STEEL HYBRID SINGLE CELL BOX WITH EXTERNAL POST-TENSIONED CABLES HIGHWAY VIADUCT
The monitoring aims at analyzing the behavior of post-tensioned cables during the bridge's operation, through time and frequency domain analyses. Real-time monitoring is a key tool to provide useful information for the detection of possible effects induced by ongoing deterioration or fatigue processes. The analysis allows a comparison between the expected modal parameters and the measured natural frequencies in the initial monitoring conditions, with consequent definition of corresponding attention and alarm threshold levels set for automatic alerting of the operator.
PRECAST CONCRETE SEGMENTS HIGHWAY TUNNEL
The structural monitoring and diagnostics of the two tunnel tubes are supported by a complex non-linear FEM modeling, through which, for each monitoring section, the deformation and the evolution of its ovalization with respect to the evolution of the ongoing landslide phenomenon are evaluated. In cable sections where the mechanical characterization and the surrounding stratigraphic conditions are completely similar, a Data-Driven approach is used to extend the Performance Indicators and monitor the most significant structural response parameters at all measurement sections.
R&D and Innovation

Learn more about the services offered for
Research.

  • University collaboration agreements
  • Laboratory testing/site full-scale testing
  • National and International Research Projects
  • Innovation & Applied Research
  • Scientific Publications
Learn more