Control and diagnostics

Description :

Research activities focus on diagnostics, fault detection and monitoring of industrial electrical equipment through modeling and identification techniques as well as signal processing. These control and diagnostic techniques are carried out on industrial electrical systems, with a view to developing methods ranging from the detection of electrical and mechanical faults in complex systems to the definition of a fault-tolerant control. The monitoring of an electromechanical system with non-invasive sensors (our team is interested in infrared thermography and related classification techniques) is an interesting solution in industrial applications. This solution has advantages especially in the case of monitoring mechanical systems that are not easily accessible. The analysis of the electrical and magnetic signals measurable on the electric drive machine such as the voltage, the supply current or the dispersion flow, allow the examination of the state of the complete system. In the same way, other electrical quantities calculated from the basic signals give relevant information for monitoring the same system. In addition, the non-invasive sensors do not require a modification of the installation and do not introduce additional space with reasonable implantation costs. For the diagnosis, we develop intelligent current techniques and we test new approaches.

Keywords : Industrial Processes, Electrical Equipment, Dependability, Fault Diagnostics, Maintenance, Intelligent Algorithms, Modeling, Simulation, Nondestructive Testing, Remote Sensing, Data Fusion, Classification