Detecção de barras quebradas em motores de indução utilizando sensor magnetostrictivo composto aplicado em redes de Bragg em fibras ópticas

AC induction motors are the most common motors used in industrial motion. They are widely used in industrial applications for its simplicity, rugged design, low-cost, low maintenance and direct connection to an AC power source. However, one of the faults occurring in induction motor is the rotor bar breakage that may rapidly spread to a functional failure with catastrophic consequences. Despite the low cost of an induction motor, production losses due to a functional failure in the motor may be of the order, or greater than, the cost of the motor itself and therefore, the cost advantages that can be achieved with predictive maintenance justify research in monitoring techniques that can indicate the evolution of the conditions before a failure occurs. In this work, a magnetic sensor based on fiber Bragg grating (FBG) and magnetostrictive composite made of Terfenol-D particulates immersed in epoxy resin matrix applied to induction motor is shown to be capable of detecting rotor broken bars in high voltage induction motors, even when the motor is installed in a dangerous atmosphere, due to the insulation provided by the optical fiber sensor. To the best of our knowledge, this work demonstrates by the first time an FBG based magnetic sensor applied to monitor an induction motor with the capability to distinguish defective bars, whereas at the same time, conventional technique of current signature at low loading levels failed to indicate the motor severity.

Grantor dc:publisher

Universidade Federal do Rio de Janeiro

Year dc:date.issued

2017

Author dc:creator

• Bieler, Geraldo

Advisor dc:contributor.advisor

• Werneck, Marcelo Martins

• Engenharia elétrica
• Motor de indução
• Sensores à fibra óptica
• Redes de Bragg

Statement dc:rights

• Acesso Aberto

Language dc:language

por

Handle dc:identifier.uri

http://hdl.handle.net/11422/8200

OAI identifier oai:identifier

oai:pantheon.ufrj.br:11422/8200