Cyber-Physical Integration and Experimental Validation of Impeller Failures Using IoT-Enabled Digital Twin Framework

This interdisciplinary study investigates impeller failure using a
combined digital and experimental approach, establishing a proof of concept
for cyber-physical integration. First, a CAD model was developed and its
structural integrity is validated using Finite Element Analysis (FEA) to
ensure the impeller could withstand operational loads and dynamic stresses,
following the methodology outlined in [1]. Next, an IoT-enabled digital twin
framework was implemented with Arduino-based sensors (temperature,
humidity, vibration) to monitor 3D-printed impellers made from 316L
stainless steel and AlSi10Mg aluminium. The sensors were integrated with
a custom test rig driven by a motor capable of 10,000 rpm, with data acquired
via analog/digital interfaces and visualized in Node-RED, streaming in real
time to an IoT cloud platform. Impeller experiments ran for over 80 hours
and were tested under two corrosive conditions: (i) engine oil (5W-30) and
(ii) saltwater. SEM/EDS analysis revealed carbon deposits on oil-exposed
samples and aluminium oxide on saltwater-exposed ones, while further SEM
imaging showed pitting and corrosion. Alicona surface roughness tests
confirmed degradation under dynamic loads. Preliminary real-time
monitoring demonstrated the of predictive maintenance alerts, though fullscale validation remains future work. Overall, the developed framework
provides a robust basis for physical testing with digital representation,
offering strong potential for predictive maintenance.