An Industrial Internet-of-Things (IIOT) Infrastructure for Digital Twin Models of Control Valves

The visualization and understanding of the internal flow behaviour of valves installed in process units will resolve the complexity and unpredictability involved in designing, monitoring, and optimizing the operation and improve the productivity of the valves in all areas of application. Present scopes of digital twin technology in valve modelling and prediction have focused on historical data monitoring to develop prediction models that require data-matching and real-data validation through processes that may be prone to subjective experimental error. With a focus on a novel approach to realistic data acquisition and management in digital twin implementations, modelling and visualization of internal flow-geometry interaction can be attained in real-time operation using univariate time-series
hydrodynamic profile of fluid transport through a series of computer routines launched on a microcontroller-based platform managing and transmitting (IOT) across independent cyber-physical components. This intervention bridges the gaps regarding independent validation and prediction processes in digital twin models of valves.