On-line system for faults detection in induction motors based on PCA

Dissertation to obtain the degree of Master in Electrical and Computer Engineering

Nowadays in the industry there many processes where human intervention is replaced by electrical machines, especially induction machines due to his robustness, performance and low cost. Although, induction machines are a high reliable device, they are also susceptible to faults. Therefore, the study of induction machine state is essential to reduce human and financial costs. The faults in induction machines can be divided mainly into two types: electrical faults and mechanical faults. Electrical faults represent between 40% and 50% of the reported faults and can be divided essentially in 2 types: stator unbalances and broken rotor bars. Taking into account the high dependency of induction machines and the massive use of automatic processes the industrial level, it is necessary to have diagnostic and monitoring systems these machines. It is presented in this work an on-line system for detection and diagnosis of electrical faults in induction motors based on computer-aided monitoring of the supply currents. The main objective is to detect and identify the presence of broken rotor bars and stator short-circuits in the induction motor. The presence of faults in the machine causes different disturbances in the supply currents. Through a stationary reference frame, such as αβ transform it is possible to extract and manipulate the results obtained from the supply currents using Eigen decomposition.