Pump Digital Twin and Maintenance Dashboard
Centrifugal pump fluid-mechanical digital twin predicting cavitation inception and impeller wear.
Project Overview
Combines real-time pressure transducers, flow meters, and vibration sensors with a physics-informed digital twin model to calculate pump hydraulic efficiency, detecting cavitation before pump damage occurs. ### Practical Student Engineering Solution Fully functional hardware demonstration prototype equipped with dedicated microcontrollers, precision sensors, actuators, and an interactive cloud/mobile telemetry dashboard. ### Key Learning Outcomes - Embedded C / MicroPython firmware architecture and sensor interfacing - IoT telemetry protocols (MQTT / HTTP / BLE / LoRaWAN) - Power regulation, hardware debugging, and PCB design principles - Comprehensive technical documentation aligned with IEEE academic standards
Modern commercial and industrial infrastructure requires automated, real-time sensing and telemetry. Conventional manual monitoring suffers from high latency, human error, and lack of predictive fault visibility for Pump Digital Twin and Maintenance Dashboard.
A turnkey engineering prototype integrating high-precision sensor modules, dedicated microcontroller unit, and cloud telemetry protocols to automate measurement, trigger alert thresholds, and provide remote dashboard control.