Skip to main content
Top

2023 | OriginalPaper | Chapter

Structural Monitoring: Modal Tracking with LoRaWAN Wireless Systems and Automatic Cloud Algorithms

Authors : Matteo Maccanti, Paolo De Lellis, Andrea Sala, Marco Galli, Matteo Giorgi

Published in: Experimental Vibration Analysis for Civil Engineering Structures

Publisher: Springer Nature Switzerland

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Every structure needs to be monitored throughout its useful life, to ensure an adequate level of safety and due to external events - both natural and not – that can disturb its state of equilibrium. Moving from these demands, in recent years, Move Solutions has implemented a structural monitoring system, static and dynamic, consisting of a variety of completely wireless sensors, operating with LoRaWAN technology, together with a special Cloud platform developed with the aim of facilitating the analysis and visualization of data by the operators in charge of the activities. The system is based on excellent sensor synchronization (500 μs) through which a dataset conforming to OMA (Operational Modal Analysis) is obtained. From the accelerometric data, it is possible to extrapolate the daily frequencies and modal shapes using the FDD (Frequency Domain Decomposition) technique. For long-term monitoring, it is necessary to identify only structure modes of vibration among all those calculated by FDD; this is made possible by a multi-level clustering algorithm, designed by Move Solutions, that can differentiate useful vibrational modes from the “spurious” ones, which will be discarded. The following step is defined as Tracking, where the aim is to monitor the variations of the previously identified vibrational modes over time. The use of a wireless and fully automated monitoring system on the Cloud can give a big boost in simplifying the management of all infrastructures, cutting costs and digitizing processes.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literature
2.
go back to reference ETSI EN 300 220-1 V3.1.1: Short Range Devices (SRD) operating in the frequency range 25 MHz to 1000 MHz; Part 1: Technical characteristics and methods of measurement, February 2017 ETSI EN 300 220-1 V3.1.1: Short Range Devices (SRD) operating in the frequency range 25 MHz to 1000 MHz; Part 1: Technical characteristics and methods of measurement, February 2017
3.
go back to reference ETSI EN 300 220-2 V3.2.1: Short Range Devices (SRD) operating in the frequency range 25 MHz to 1000 MHz; Part 2: Harmonised Standard for access to radio spectrum for non specific radio equipment, June 2018 ETSI EN 300 220-2 V3.2.1: Short Range Devices (SRD) operating in the frequency range 25 MHz to 1000 MHz; Part 2: Harmonised Standard for access to radio spectrum for non specific radio equipment, June 2018
4.
go back to reference Leonardi, L., Bello, L.L., Battaglia, F., Patti, G.: Comparative assessment of the LoRaWAN medium access control protocols for IoT: does listen before talk perform better than ALOHA? Electronics 9(4), 553 (2020)CrossRef Leonardi, L., Bello, L.L., Battaglia, F., Patti, G.: Comparative assessment of the LoRaWAN medium access control protocols for IoT: does listen before talk perform better than ALOHA? Electronics 9(4), 553 (2020)CrossRef
6.
go back to reference Brincker, R., Zhang, L.: Modal Identification of output-only systems using frequency domain decomposition. Smart Mat. Struct. 10, 441–445 (2001)CrossRef Brincker, R., Zhang, L.: Modal Identification of output-only systems using frequency domain decomposition. Smart Mat. Struct. 10, 441–445 (2001)CrossRef
7.
go back to reference Sunjoong, K., Ho-Kyung, K.: Damping Identification of Bridges Under Nonstationary Ambient Vibration (2017) Sunjoong, K., Ho-Kyung, K.: Damping Identification of Bridges Under Nonstationary Ambient Vibration (2017)
8.
go back to reference Magalhães, F., Cunha, Á., Caetano, E.: Online automatic identification of the modal parameters of a long span arch bridge. Mech. Syst. Signal Process. 23(2), 316–329 (2009). ISSN 0888-3270 Magalhães, F., Cunha, Á., Caetano, E.: Online automatic identification of the modal parameters of a long span arch bridge. Mech. Syst. Signal Process. 23(2), 316–329 (2009). ISSN 0888-3270
11.
go back to reference Neu, E., Janser, F., Khatibi, A.A., Orifici, A.C.: Fully automated operational modal analysis using multi-stage clustering. Mech. Syst. Signal Process. 84(Part A), 308–323 (2017). ISSN 0888-3270 Neu, E., Janser, F., Khatibi, A.A., Orifici, A.C.: Fully automated operational modal analysis using multi-stage clustering. Mech. Syst. Signal Process. 84(Part A), 308–323 (2017). ISSN 0888-3270
13.
go back to reference Siringoringo, D., Fujino, Y., Nagayama, T.: Dynamic characteristics of an overpass bridge in a full-scale destructive test. J. Eng. Mech. 139, 691–701 (2013) Siringoringo, D., Fujino, Y., Nagayama, T.: Dynamic characteristics of an overpass bridge in a full-scale destructive test. J. Eng. Mech. 139, 691–701 (2013)
14.
go back to reference Spiridonakos, M.D., Chatzi, E.N., Sudret, B.: Polynomial chaos expansion of structures under operational variability. ASCE-ASME J. Risk Uncertain. Eng. Syst. (2016) Spiridonakos, M.D., Chatzi, E.N., Sudret, B.: Polynomial chaos expansion of structures under operational variability. ASCE-ASME J. Risk Uncertain. Eng. Syst. (2016)
15.
go back to reference Deraemaeker, A., Reynders, E., De Roeck, G., Kullaa, J.: Vibration-based structural health monitoring using output-only measurements under changing environment. Mech. Syst. Signal Process. 22, 34–56 (2018) Deraemaeker, A., Reynders, E., De Roeck, G., Kullaa, J.: Vibration-based structural health monitoring using output-only measurements under changing environment. Mech. Syst. Signal Process. 22, 34–56 (2018)
16.
go back to reference Rainieri, C., Fabbrocino, G., Magalhaes, F., Cunha, A.: Predicting the variability of natural frequencies and its causes by Second Order Blind Identification. Struct. Health Monit. 18, 486–507 (2018) Rainieri, C., Fabbrocino, G., Magalhaes, F., Cunha, A.: Predicting the variability of natural frequencies and its causes by Second Order Blind Identification. Struct. Health Monit. 18, 486–507 (2018)
17.
go back to reference Magalhaes, F., Cunha, A., Caetano, E.: Vibration based structural health monitoring of an arch bridge: from automated OMA to damage detection. Mech. Syst. Signal Process. 28, 212–228 (2012) Magalhaes, F., Cunha, A., Caetano, E.: Vibration based structural health monitoring of an arch bridge: from automated OMA to damage detection. Mech. Syst. Signal Process. 28, 212–228 (2012)
18.
go back to reference Avci, O., et al.: A review of vibration-based damage detection in civil structures: from traditional methods to Machine Learning and Deep Learning applications. Mech. Syst. Signal Process. 147, 107077 (2021) Avci, O., et al.: A review of vibration-based damage detection in civil structures: from traditional methods to Machine Learning and Deep Learning applications. Mech. Syst. Signal Process. 147, 107077 (2021)
Metadata
Title
Structural Monitoring: Modal Tracking with LoRaWAN Wireless Systems and Automatic Cloud Algorithms
Authors
Matteo Maccanti
Paolo De Lellis
Andrea Sala
Marco Galli
Matteo Giorgi
Copyright Year
2023
DOI
https://doi.org/10.1007/978-3-031-39109-5_47

Premium Partners