Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/46447
Title: An Unsupervised Method based on Support Vector Machines and Higher-Order Statistics for Mechanical Faults Detection
Keywords: Support vector machines
Fault detection
Feature extraction
Higher order statistics
Monitoring
Máquina de vetores de suporte
Falhas mecânicas - Detecção
Estatísticas de ordem superior
Issue Date: May-2020
Publisher: Institute of Electrical and Electronic Engineers - IEEE
Citation: BORGES, F. et al. An Unsupervised Method based on Support Vector Machines and Higher-Order Statistics for Mechanical Faults Detection. IEEE Latin America Transactions, [S. I.], v. 18, n. 06, p. 1093-1101, Jun. 2020. DOI: 10.1109/TLA.2020.9099687.
Abstract: In this paper an unsupervised method to detect mechanical faults using support vector machines and higher-order statistics is proposed. The method extracts compact vector features - based on higher-order statistics - from vibration signals and uses the one-class support vector machine to build a closed region around the data from the health structure. The method was evaluated considering two cases: fault detection in a cantilever beam and in a three-phase induction motor. In both cases, the vibrations were collected by a 3 axis accelerometer sensor. The acquisition system was controlled by an open-source electronic prototyping ARDUINO ® platform. After collecting the data, higher-order statistics-based features were extracted. These features were presented to the one-class support vector machine for fault detection. The proposed method was capable of identifying a closed region in a two-dimensional space so that events inside this region are signed as no faults and events outside this region are signed as faults. The method has two important characteristics: (i) it requires only healthy mechanical structures to be designed, and (ii) it operates in a low dimensional space (only two) constructed by the higher-order statistics features, which requires low computational cost in the operational phase.
URI: https://ieeexplore.ieee.org/document/9099687
http://repositorio.ufla.br/jspui/handle/1/46447
Appears in Collections:DAT - Artigos publicados em periódicos
DEG - Artigos publicados em periódicos

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.