Browsing by Author "Arellano Espitia, Francisco"
Now showing items 1-20 of 40
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Analysis of machine learning based condition monitoring schemes applied to complex electromechanical systems
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Conference report
Restricted access - publisher's policyIn the modern industry framework, the application of condition monitoring schemes over electromechanical systems is being subjected to demanding requirements. Currently, the massive digitalization of industrial assets ... -
Anomaly detection in electromechanical systems by means of deep-autoencoder
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Conference report
Open AccessAnomaly detection in manufacturing processes is one of the main concerns in the new era of the Industry 4.0 framework. The detection of uncharacterized events represents a major challenge within the operation monitoring ... -
Autoencoder based feature reduction analysis applied to electromechanical systems condition monitoring
(Institute of Electrical and Electronics Engineers (IEEE), 2019)
Conference report
Restricted access - publisher's policyCondition monitoring in electromechanical systems represents, currently, one of the most critical challenges dealing with the advancement and modernization in intelligent manufacturing. In this regard, machine learning ... -
Bases de datos: Introducción y caso de aplicación
(2023-10-27)
Audiovisual
Open Access -
Deep learning based condition monitoring approach applied to power quality
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Conference report
Restricted access - publisher's policyCondition monitoring applied to power quality involves several techniques and procedures for the assessment of the electrical signal. Data-driven approaches are the most common methodologies supported on data and signal ... -
Deep learning based methodologies applied to industrial electromechanical systems monitoring
(Universitat Politècnica de Catalunya, 2023-10-10)
Doctoral thesis
Open Access(English) In recent years, there has been significant attention from both the academic and industry sectors towards condition-based maintenance of rotating systems. This attention stems from the high relevance of these ... -
Deep learning-based partial transfer fault diagnosis methodology for electromechanical systems
(2023)
Conference report
Restricted access - publisher's policyRecently, transfer learning technology has provided valuable solutions to problems that are present in machinery with industrial applications. Through the use of transfer learning, basic diagnostic problems have been well ... -
Deep-compact-clustering based anomaly detection applied to electromechanical industrial systems
(Multidisciplinary Digital Publishing Institute (MDPI), 2021-08-30)
Article
Open AccessThe rapid growth in the industrial sector has required the development of more productive and reliable machinery, and therefore, leads to complex systems. In this regard, the automatic detection of unknown events in machinery ... -
Diagnosis electromechanical system by means CNN and SAE: an interpretable-learning study
(Institute of Electrical and Electronics Engineers (IEEE), 2022)
Conference report
Open AccessCyber-physical systems are the response to the adaptability, scalability and accurate demands of the new era of manufacturing called Industry 4.0. They will become the core technology of control and monitoring in smart ... -
Diagnosis methodology based on deep feature learning for fault identification in metallic, hybrid and ceramic bearings
(Multidisciplinary Digital Publishing Institute (MDPI), 2021-08-30)
Article
Open AccessScientific and technological advances in the field of rotatory electrical machinery are leading to an increased efficiency in those processes and systems in which they are involved. In addition, the consideration of advanced ... -
Docker: Creación de contenedores
(2023-10-20)
Audiovisual
Open Access -
Docker: Instalación de Docker
(2023-10-20)
Audiovisual
Open Access -
Evaluation of multiclass novelty detection algorithms for electric machine monitoring
(Institute of Electrical and Electronics Engineers (IEEE), 2019)
Conference report
Restricted access - publisher's policyThe detection of unexpected events represents, currently, one of the most critical challenges dealing with electromechanical system diagnosis. In this regard, machine learning based algorithms widely applied in other fields ... -
Grafana: Configuración de dashboard
(2023-10-30)
Audiovisual
Open Access -
Grafana: Configuración de fuente de datos
(2023-10-27)
Audiovisual
Open Access -
Grafana: Configuración de Grafana
(2023-10-20)
Audiovisual
Open Access -
InfluxDB: Creación de base de datos PDI
(2023-10-20)
Audiovisual
Open Access -
InfluxDB: Escritura en bases de datos PDI
(2023-10-20)
Audiovisual
Open Access -
InfluxDB: Lectura y filtrado de datos PDI
(2023-10-20)
Audiovisual
Open Access -
Interoperabilidad industrial: Concepto y consideraciones previas
(2023-10-27)
Audiovisual
Open Access
