TIA DATA-GEN (MATLAB Synthetic Data Generator for Electro Mechanical parts) is a synthetic data generator for common electro mechanical parts, including electric DC motors and a hydraulic shaft.
The purpose of TIA DATA-GEN is to generate synthetic of Fault data from the model elements. Hence, the generation of such data enables users to have a model-driven digital twin for common DC motor, gearbox and hydraulic shaft and their associated components.
TIA DATA-GEN utilizes several 1st order models: DC motor and gearbox models, and a hydraulic press model. For both of these models, random sources of errors (degradation of the components) are introduced. A load representative to what they may experience in real world is then applied. Virtual sensors will collect data for several specific degradation scenarios. The outcome is a supervised and annotated dataset. The latter will be used in training a ML classifier. The classifier will be used to monitor the condition of the machine in operation and provide early warning for potential fault.
In the context of COGNITWIN, the TIA DATA-GEN output will be useful in conducting the predictive maintenance of the modelled elements.