Poincaré plot features from vibration signal for gearbox fault diagnosis

Ruben Medina, Ximena Alvarez, Diana Jadan, Mariela Cerrada, Rene Vinicio Sanchez, Jean Carlo Macancela

Research output: Contribution to conferencePaper

Abstract

This paper describes a method for fault diagnosis in gearboxes using features extracted from the Poincare plot of the vibration signal. Several features describing the geometrical shape of the Poincare plot are calculated and three of these features are selected for performing the classification of 10 types of faults recorded in the gearbox vibration signal dataset. A multi-class Error-Correcting Output Code Support Vector Machine is trained for performing the classification of faults. The cross-validation performed show that the highest accuracy attained is 95.3% when signals recorded using the load L1 are considered.

Original languageEnglish
Pages1-6
Number of pages6
DOIs
StatePublished - 4 Jan 2018
Event2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017 - Salinas, Ecuador
Duration: 16 Oct 201720 Oct 2017

Conference

Conference2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017
Abbreviated titleETCM 2017
CountryEcuador
CitySalinas
Period16/10/1720/10/17

Keywords

  • Gearbox faults classification
  • Multi-class Support Vector Machines
  • Poincare plots
  • Rotatory machines

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