SMARTMOT

This project is intended to develop new solutions for electric motors condition monitoring based on the combined analysis of electric quantities, such as currents and stray fluxes, giving continuity to the successful research carried out by the team in previous projects. The ultimate objective is to implement these solutions into a smart sensor prototype that can be used for monitoring the condition of different types of motors (induction motors (IM), wound field synchronous motors (WFSM), permanent magnet machines (PMM), synchronous reluctance machines (SRM)), regardless of their operating conditions. The developed solutions will mean a step forward in the area because they will rely on pioneering methods that combine steady-state and transient analysis and because the sensor will incorporate a module that will enable the estimation of the motor efficiency and its actual correlation with its health. Finally, the developed smart sensor will operate in an autonomous way, i.e., without user intervention, which will require the use of advanced artificial intelligence (AI) methods for its development.

To achieve these objectives, the project will be divided into two main parts: The first part will deal with the extension of the technologies based on the advanced analysis of stray-fluxes and currents to new operating conditions, as well as to other motor typologies. The target is to extrapolate the application of these technologies to other IM operating conditions in which these methods have been barely applied in the past, as well as to other types of motors in which their application is still pending (PMM, SRM). The widespread use of these latter typologies in many recent applications (e.g. electric vehicles) opens a broad scope of future possibilities to this research. The second project part will be focused on the development of smart sensors based on combined analysis of currents and stray-fluxes that can be applied to any electric motor to diagnose its health, regardless of its size and operating conditions. The system must also be able to determine the efficiency of the motor. The idea is to merge the advanced techniques developed in the first stage onto intelligent smart sensors that are aimed to diagnose the condition of the motor and determine its efficiency, enabling their correlation, so that a quantitative indicator of the efficiency decrement caused by the motor healths deterioration is obtained. The developed sensors will incorporate signal and image processing capabilities, as well as AI algorithms to reach an automatic diagnostic of the motor condition. Moreover, different smart sensor solutions and configurations will be considered, including both autonomous sensors that are able to carry out the integral diagnostic process, as well as distributed sensors that will transfer the collected data to a remote central diagnostic unit. This opens up doors to new cutting-edge solutions based on networks of interconnected smart sensors, an idea that is suited for the new Industry 4.0 context.

Duration: September 2022- September 2025                                             Principal Investigators: Prof. JOSE A ANTONINO-DAVIU, Prof. LARISA DUNAI