Structural Health Monitoring Reliability Enhancement by an Automated Sensor Tuning Procedure

Autor: Alessandro Marzani, Michelangelo Maria Malatesta, Denis Bogomolov, Federica Zonzini, Nicola Testoni, Luca De Marchi
Přispěvatelé: michelangelo maria malatesta, federica zonzini, denis bogomolov, nicola testoni, luca de marchi, alessandro marzani
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Scopus-Elsevier
Popis: Nowadays, Structural Health Monitoring (SHM) is rising as the most promising collection of tools to enhance the safety of structures belonging to different contexts, including the civil, aerospace and industrial fields. SHM applications require a minimum level of reliability and accuracy, thus demanding for self-test analysis and calibration procedures. Typically, these procedures are carried out manually by means of expensive bench instruments, resulting to be time consuming and cumbersome. Moreover, in–situ sensor calibration is not always possible, especially in large scale scenarios or harsh environments. To overcome these limitations, the current work proposes an innovative tuning procedure purposely designed for stamp–size and low–power sensor node prototypes developed within the SHM research group of the Advanced Research Center of Electronic Systems (ARCES) of the University of Bologna. In particular, the capability to perform an automatic tuning procedure without any kind of external bench instrument is demonstrated, allowing for a simplification of the procedure and on–line self–test analysis, speeding up the process. The extraction of the main tuning parameters (such as time constants, voltage biases, time shifts) and their automatic estimation have been embedded within the sensor node firmware. Finally, an experimental campaign has been executed to validate the performance of the entire procedure.
Databáze: OpenAIRE