SOA Based Integrated Software to Develop Fault Diagnosis Models Using Machine Learning in Rotating Machinery

Mariela Cerrada, Fannia Pacheco, Rene Vinicio Sanchez, Diego Cabrera, Jean MacAncela, Pablo Lucero

Research output: Contribution to conferencePaper

2 Scopus citations

Abstract

© 2017 IEEE. Fault detection and diagnostic software (FDDS) supports technicians and engineers to deal with operational matters, in major cases related to complicated systems and advanced technology that require higher performance expectation. Information and communication technologies play an importantrole for implementing efficient maintenance software, therefore, the development of FDDS is posed as an industrial necessity. In case of industrial rotating machinery, data-driven FDDS using available vibration signals, or other related signals monitored from sensors, is currently viewed as an industrial informatics requirement. This paper proposes the application of a Service Oriented Architecture (SOA) to implement an integrated tool for automatically developing and testing machine learning based fault diagnosis models in rotating machinery. As a result, a generic architecture is obtained which is able to build and implement diagnosis models in similar devices or processes. A condition monitoring software application, using the proposed SOA, was implemented in Java and deployed on a computational environment to test its performance in a experimental test bed, under realistic fault mechanical conditions in a gearbox.
Translated title of the contributionSoftware integrado basado en SOA para desarrollar modelos de diagnóstico de fallas utilizando el aprendizaje automático en maquinaria rotativa
Original languageEnglish (US)
Pages28-37
Number of pages10
DOIs
StatePublished - 7 Jun 2017
EventProceedings - 11th IEEE International Symposium on Service-Oriented System Engineering, SOSE 2017 -
Duration: 7 Jun 2017 → …

Conference

ConferenceProceedings - 11th IEEE International Symposium on Service-Oriented System Engineering, SOSE 2017
Period7/06/17 → …

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