[ Modelado de un sistema de inferencia difusa tipo Mamdani para el diagnóstico de envejecimiento de motores eléctricos ]
Volume 21, Issue 1, March 2016, Pages 34–42
Sergio Carlos Ponce Flores1, Perfecto Malaquías Quintero Flores2, and José Luis Hernández Corona3
1 Computational Systems Department, Tecnological Institute of Apizaco, National Technological of Mexico, México
2 Computation and Systems Department, National Technological of Mexico, Technological Institute of Apizaco, Carretera Apizaco-Tzompantepec, Tlaxcala, México
3 Department of Industrial Maintenance Engineering, Technological University of Tlaxcala, Carretera a el Carmen Xalpatlahuaya, Tlaxcala, México
Original language: French
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Fuzzy systems have been used in maintenance and have achieved successful results, however, there are many fields of application inside the area that haven't been sufficiently explored, such as in this case, the diagnosis of electric motors aging. In this work, the basis of fuzzy systems is reviewed making emphasis to the Mamdani inference model and its application for the diagnosis of electrical motors aging is proposed, with the finality of obtaining an aging coefficient that can be used as a fundamental element in industrial maintenance. For the antecedent part are considered as principal variables the temperature, the electric current and the voltage, and for the consequent part the output is the aging coefficient. The system was based in an electric motor which specifications were used to model the system. The knowledge base of the system was extracted from the documentation available, the constant monitory of induction motors and expert's knowledge. The system was applied using a set of hypothetic data to show the system behavior and results showed that the system could be successfully used to represent the human knowledge and benefits of its application are represented with fastest and safest diagnosis, reduction of human errors, improvements in reliability of the motors operation, among others.
Author Keywords: fuzzy logic, fuzzy systems, maintenance, Mamdani model, electric motors aging.
Volume 21, Issue 1, March 2016, Pages 34–42
Sergio Carlos Ponce Flores1, Perfecto Malaquías Quintero Flores2, and José Luis Hernández Corona3
1 Computational Systems Department, Tecnological Institute of Apizaco, National Technological of Mexico, México
2 Computation and Systems Department, National Technological of Mexico, Technological Institute of Apizaco, Carretera Apizaco-Tzompantepec, Tlaxcala, México
3 Department of Industrial Maintenance Engineering, Technological University of Tlaxcala, Carretera a el Carmen Xalpatlahuaya, Tlaxcala, México
Original language: French
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Fuzzy systems have been used in maintenance and have achieved successful results, however, there are many fields of application inside the area that haven't been sufficiently explored, such as in this case, the diagnosis of electric motors aging. In this work, the basis of fuzzy systems is reviewed making emphasis to the Mamdani inference model and its application for the diagnosis of electrical motors aging is proposed, with the finality of obtaining an aging coefficient that can be used as a fundamental element in industrial maintenance. For the antecedent part are considered as principal variables the temperature, the electric current and the voltage, and for the consequent part the output is the aging coefficient. The system was based in an electric motor which specifications were used to model the system. The knowledge base of the system was extracted from the documentation available, the constant monitory of induction motors and expert's knowledge. The system was applied using a set of hypothetic data to show the system behavior and results showed that the system could be successfully used to represent the human knowledge and benefits of its application are represented with fastest and safest diagnosis, reduction of human errors, improvements in reliability of the motors operation, among others.
Author Keywords: fuzzy logic, fuzzy systems, maintenance, Mamdani model, electric motors aging.
How to Cite this Article
Sergio Carlos Ponce Flores, Perfecto Malaquías Quintero Flores, and José Luis Hernández Corona, “Modelling of a Mamdani fuzzy inference system for the diagnosis of electric motors aging,” International Journal of Innovation and Scientific Research, vol. 21, no. 1, pp. 34–42, March 2016.
