On-line Condition Monitoring, Fault Detection and Diagnosis in Electrical Machines and Power Electronic Converters

The objective of this PhD research is to develop robust, and non-intrusive condition monitoring methods for induction motors fed by closed-loop inverters. The flexible energy forms synthesized by these connected power electronic converters greatly enhance the performance and expand the operating region of induction motors. They also significantly alter the fault behavior of these electric machines and complicate the fault detection and protection. The current state of the art in condition monitoring of power-converter-fed electric machines is underdeveloped as compared to the maturing condition monitoring techniques for grid-connected electric machines. This dissertation first investigates the stator turn-to-turn fault modelling for induction motors (IM) fed by a grid directly. A novel and more meaningful model of the motor itself was developed and a comprehensive study of the closed-loop inverter drives was conducted. A direct torque control (DTC) method was selected for controlling IM’s electromagnetic torque and stator flux-linkage amplitude in industrial applications. Additionally, a new driver based on DTC rules, predictive control theory and fuzzy logic inference system for the IM was developed. This novel controller improves the performance of the torque control on the IM as it reduces most of the disadvantages of the classical and predictive DTC drivers. An analytical investigation of the impacts of the stator inter-turn short-circuit of the machine in the controller and its reaction was performed. This research sets a based knowledge and clear foundations of the events happening inside the IM and internally in the DTC when the machine is damaged by a turn fault in the stator. This dissertation also develops a technique for the health monitoring of the induction machine under stator turn failure. The developed technique was based on the monitoring of the off-diagonal term of the sequence component impedance matrix. Its advantages are that it is independent of the IM parameters, it is immune to the sensors’ errors, it requires a small learning stage, compared with NN, and it is not intrusive, robust and online. The research developed in this dissertation represents a significant advance that can be utilized in fault detection and condition monitoring in industrial applications, transportation electrification as well as the utilization of renewable energy microgrids. To conclude, this PhD research focuses on the development of condition monitoring techniques, modelling, and insightful analyses of a specific type of electric machine system. The fundamental ideas behind the proposed condition monitoring technique, model and analysis are quite universal and appeals to a much wider variety of electric machines connected to power electronic converters or drivers. To sum up, this PhD research has a broad beneficial impact on a wide spectrum of power-converter-fed electric machines and is thus of practical importance

CONTROL PI DIFUSO PARALELO PARA CORREGIR LA RESPUESTA DE UN CONTROL PI CLÁSICO DE CORRIENTE DE LÍNEA EN UN RECTIFICADOR TRIFÁSICO / Shunt Fuzzy PI Control Compensating a Line Current PI Control Response in a Three Phase Rectifier

Este trabajo presenta la simulación de un sistema de control de corriente difuso conectado en paralelo con un controlde corriente PI clásico desintonizado. El objetivo del sistema es corregir la corriente de la línea de alimentación en unrectificador trifásico. El control PI difuso es un sistema de inferencia difusa Takagi-Sugeno (SID T-S) de orden cero que seconecta en paralelo con el control PI clásico para compensar su respuesta y lograr que la corriente de la línea se sincroniceen fase con el voltaje de alimentación. Las simulaciones se llevaron a cabo en un procesador digital de señales (DSP) deAnalog Devices 21061.ABSTRACTThis work presents the simulation of a fuzzy PI control connected in shunt topology with a line current mistuned PIcontrol. The goal of the system is to correct the line current in a three phase rectifier. The fuzzy PI control is a zero-orderTakagi-Sugeno Fuzzy Inference System (FIS T-S) connected in parallel with a classical mistuned PI control to compensateits response and achieve power factor correction. The simulations were carried out in an Analog Devices 21061 digitalsignal processor (DSP).Keywords: Three phase rectifier, Fuzzy control, Takagi-Sugeno Fuzzy inference system, Power Factor, Proportional-Integral control