Digital Twin of a Pipe Conveying Fluid: Flow Rate Anomaly Detection and Quantification via Multi-fidelity Kalman Filters and Event Based Cameras Signals

Numerical results of a digital twin (DT) framework for a pipe conveying fluid recorded using two event-based cameras (EVB). The DT framework consists of an unscented Kalman filter (UKF) for parameter identification and a linear Kalman filter (LKF) coupled with dynamic mode decomposition (DMD) for real-time monitoring and anomaly detection. The test case concerns a 75-second recording with a time interval of 0.025 s for a change in flow velocity in the pipe carrying the fluid occurring at t = 18.4 s. The flowrate is the unknown parameter and is initialized as 5.84 m/s and is then reduced to 5.21 m/s. Details of the implementation are available in the associated article. A README.txt file is available below for the description of each file.