PRIN 2022 CALL. DECREE NO. 104 OF 2 FEBRUARY 2022
TITOLO DEL PROGETTO: 20227Y5NZ2 - Reshaping the Role of Measurement in the 4.0 Era: towards a Cyber-Physical Measurement system for Advanced Monitoring Applications
CUP CODE: D53D23001050006
Budget: € 84.960,00
Poliba R.U. CoordinatorDr. Nicola Giaquinto
National P.I.: Leopoldo Angrisani - University of ROME "La Sapienza"
Brief project description
The project concerns the evolution of measurement and monitoring systems in the context of cyber-physical systems and Industry 4.0 technologies. The objective is to overcome the traditional role of measurement systems as simple data acquisition tools, transforming them into active components capable of integrating measurement, modelling, simulation and advanced processing.
The project develops the Cyber-Physical Measurement Systems (CPMS) paradigm. The case study concerns distributed measurement systems based on time-domain reflectometry (TDR), applied to the detection of water and variations in the dielectric properties of the monitored medium. The research unit of the Polytechnic University of Bari contributes primarily to the development of the digital twin of the measurement system, through models capable of reproducing the behaviour of distributed TDR systems under real and non-ideal conditions, and of supporting TDR inversion, simulation and uncertainty evaluation.
Purpose
The main objectives of the research unit of the Polytechnic University of Bari concern
CUP CODE: D53D23001050006
Budget: € 84.960,00
Poliba R.U. CoordinatorDr. Nicola Giaquinto
National P.I.: Leopoldo Angrisani - University of ROME "La Sapienza"
Brief project description
The project concerns the evolution of measurement and monitoring systems in the context of cyber-physical systems and Industry 4.0 technologies. The objective is to overcome the traditional role of measurement systems as simple data acquisition tools, transforming them into active components capable of integrating measurement, modelling, simulation and advanced processing.
The project develops the Cyber-Physical Measurement Systems (CPMS) paradigm. The case study concerns distributed measurement systems based on time-domain reflectometry (TDR), applied to the detection of water and variations in the dielectric properties of the monitored medium. The research unit of the Polytechnic University of Bari contributes primarily to the development of the digital twin of the measurement system, through models capable of reproducing the behaviour of distributed TDR systems under real and non-ideal conditions, and of supporting TDR inversion, simulation and uncertainty evaluation.
Purpose
The main objectives of the research unit of the Polytechnic University of Bari concern:
construction of digital twins of distributed TDR systems under real conditions;
electromagnetic and computational modelling of the measurement system;
development of techniques for the automatic inversion and interpretation of reflectograms;
use of the CPMS for measurement-system simulation and uncertainty evaluation;
application to the distributed monitoring of water and moisture.
Expected results
The project involves digital twins, electromagnetic and computational models, TDR inversion techniques and algorithms for the automatic processing of reflectograms. Methodologies for the quantitative evaluation of uncertainty, experimental validation in the laboratory and methodological results useful for future CPMS applications are also envisaged.
Achieved results
The results achieved can be summarised as follows:
A digital twin of a TDR system based on a two-wire sensor was developed for the quantitative estimation of the soil moisture profile. The model integrates the relationship between soil moisture and dielectric constant, the transverse electromagnetic behaviour of the sensor and the longitudinal behaviour of the sensing line.
A TDR inversion methodology based on grey-box models was developed, capable of reproducing reflectograms measured under non-ideal operating conditions, including in the presence of irregular signals and incomplete knowledge of the system's electromagnetic parameters.
The digital twin was used for the realistic simulation of the measurement system and for the quantitative evaluation of uncertainty through Monte Carlo simulations representative of variations in the physical system.
A two-stage TDR inversion procedure was introduced to improve the accuracy of water localization along the distributed sensor, combining a flexible reconstruction of the dielectric profile with a parametric estimation of the perturbed region.
A data-driven approach to TDR inversion based on transformer neural networks was developed for the automatic reconstruction of distributed capacitance profiles from reflectograms, without iterative optimization procedures.
The methodologies developed were validated through simulations and laboratory experimental campaigns. The results confirm the effectiveness of the approach for water localization, moisture estimation, and the metrological evaluation of distributed TDR systems.
Expected results
The project involves digital twins, electromagnetic and computational models, TDR inversion techniques and algorithms for the automatic processing of reflectograms. Methodologies for the quantitative evaluation of uncertainty, experimental validation in the laboratory and methodological results useful for future CPMS applications are also envisaged.
Achieved results
The results achieved can be summarised as follows:
A digital twin of a TDR system based on a two-wire sensor was developed for the quantitative estimation of the soil moisture profile. The model integrates the relationship between soil moisture and dielectric constant, the transverse electromagnetic behaviour of the sensor and the longitudinal behaviour of the sensing line.
A TDR inversion methodology based on grey-box models was developed, capable of reproducing reflectograms measured under non-ideal operating conditions, including in the presence of irregular signals and incomplete knowledge of the system's electromagnetic parameters.
The digital twin was used for the realistic simulation of the measurement system and for the quantitative evaluation of uncertainty through Monte Carlo simulations representative of variations in the physical system.
A two-stage TDR inversion procedure was introduced to improve the accuracy of water localization along the distributed sensor, combining a flexible reconstruction of the dielectric profile with a parametric estimation of the perturbed region.
A data-driven approach to TDR inversion based on transformer neural networks was developed for the automatic reconstruction of distributed capacitance profiles from reflectograms, without iterative optimization procedures.
The methodologies developed were validated through simulations and laboratory experimental campaigns. The results confirm the effectiveness of the approach for water localization, moisture estimation, and the metrological evaluation of distributed TDR systems.
