Hydraulic systems are used in several industrial applications, including manufacturing, automobiles and energy for example. Monitoring the condition of hydraulic equipment is essential to maintain high productivity and reduce the costs of system process. Best practices have been evolving from reactive maintenance to predictive maintenance, with intelligent fault diagnosis, using recent advances in industrial Internet of Things, artificial intelligence, edge computing, etc. Beyond design, the digital twins offer advantages in predictive maintenance and provides a new paradigm for fault diagnosis. The CETIM's "Fluid & Sealing Technologies" department proposes to present its R&D work to illustrate the concept of a digital twin of a fluidic loop. For this purpose, a closed hydraulic loop has been instrumented. It is equipped with a pump, a heat exchanger, a tank, a regulation valve and three piping sections. The objective of the study is to identify process faults (pipe clogging, exchanger performance degradation, etc.). These defects are manifested by a difference between the process variables (pressure, flow, and temperature) evaluated by the model and measured on the physical loop.