Nombre del libro
- 2018 International Joint Conference on Neural Networks, IJCNN 2018 - Proceedings
Feature extraction analysis using filter banks for faults classification in induction motors Contribución en una conferencia
Perfil
editorial
- Institute of Electrical and Electronics Engineers Inc.
Thesis author
- Jhonattan Bulla
- Oscar D. Flórez
Resumen
- Different studies have been worked about induction motor bearings fault detection using digital signal processing and pattern recognition techniques. However, performance of these techniques is related with the use of correct features. This paper presents an analysis of the use of filter banks with uniform and nonuniform frequency subbands to features extraction from vibration signals. Classification was developed by an artificial neural network with feedforward connections. Results identifies that the employment of filter banks improve the accuracy in 23% for six considered classes related with faults in bearings.
autores
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http://vivoweb.org/ontology/core#FacultyMemberOrjuela Cañón, Alvaro David
fecha de publicación
- 2018-10-10
Área temática
Identidad
Identificador de objeto digital (DOI)
Número Estándar Internacional de Libros (ISBN)
- 9781509060146