Exploració per autor "Delgado Prieto, Miquel"
Ara es mostren els items 1-20 de 107
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A novel condition monitoring scheme for bearing faults based on Curvilinear Component Analysis and hierarchical neural networks
(2012)
Text en actes de congrés
Accés restringit per política de l'editorialMostly the faults in electrical machines are related with the bearings. Thus, a reliable bearing condition monitoring scheme able to detect either local or distributed defects are mandatory to avoid a breakdown in the ... -
A novel deep learning-based diagnosis method applied to power quality disturbances
(2021-05-02)
Article
Accés obertMonitoring electrical power quality has become a priority in the industrial sector background: avoiding unwanted effects that affect the whole performance at industrial facilities is an aim. The lack of commercial equipment ... -
Accurate Bearing Faults Classification based on Statistical-Time Features, Curvilinear Component Analysis and Neural Networks
(2012)
Text en actes de congrés
Accés restringit per política de l'editorialBearing faults are the commonest form of malfunction associated with electrical machines. So far, the research has been carried out mainly in the detection of localized faults, but the diagnosis of distributed faults ... -
Active learning based laboratory towards engineering education 4.0
(2019)
Text en actes de congrés
Accés obertUniversities have a relevant and essential key role to ensure knowledge and development of competencies in the current fourth industrial revolution called Industry 4.0. The Industry 4.0 promotes a set of digital technologies ... -
Activity-aware HVAC power demand forecasting
(2018-07-01)
Article
Accés obertThe forecasting of the thermal power demand is essential to support the development of advanced strategies for the management of local resources on the consumer side, such as heating ventilation and air conditioning (HVAC) ... -
Advances in power quality analysis techniques for electrical machines and drives: a review
(2022-03-01)
Article
Accés obertThe electric machines are the elements most used at an industry level, and they represent the major power consumption of the productive processes. Particularly speaking, among all electric machines, the motors and their ... -
An acoustic emission activity detection method based on short-term waveform features: application to metallic components under uniaxial tensile test
(2020-08-01)
Article
Accés obertThe Acoustic Emission (AE) phenomenon has been used as a powerful tool with the purpose to either detect, locate or assess damage for a wide range of applications. Derived from its monitoring, one major current challenge ... -
Analysis of machine learning based condition monitoring schemes applied to complex electromechanical systems
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Text en actes de congrés
Accés restringit per política de l'editorialIn 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)
Text en actes de congrés
Accés obertAnomaly 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)
Text en actes de congrés
Accés restringit per política de l'editorialCondition 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 ... -
Automatic model calibration for coupled HVAC and building dynamics using Modelica and Bayesian optimization
(Elsevier, 2022-12)
Article
Accés restringit per política de l'editorialIn recent years, increasing the energy efficiency of the building has become one of the objectives of facility managers. In this sense, monitoring-based commissioning and automated fault detection have demonstrated to be ... -
Automatización industrial : diseño de automatismos programados
(Iniciativa Digital Politècnica. Oficina de Publicacions Acadèmiques Digitals de la UPC, 2022-06)
Llibre
Accés restringit a la comunitat UPCEste libro pretende servir de ayuda durante el aprendizaje en el diseño de automatismos programados, tanto para procesos discretos (i.e. considerando exclusivamente variables binarias), como continuos (i.e. considerando ... -
Bases de datos: Introducción y caso de aplicación
(2023-10-27)
Audiovisual
Accés obert -
Bearing fault detection by a novel condition-monitoring scheme based on statistical-time features and neural networks
(Institute of Electrical and Electronics Engineers (IEEE), 2013-08)
Article
Accés restringit per política de l'editorialBearing degradation is the most common source of faults in electrical machines. In this context, this work presents a novel monitoring scheme applied to diagnose bearing faults. Apart from detecting local defects, i.e., ... -
Bearing fault diagnosis by EXIN CCA
(IEEE Computer Society Publications, 2012)
Text en actes de congrés
Accés obertEXIN CCA is an extension of the Curvilinear Component Analysis (CCA), which solves for the noninvariant CCA projection and allows representing data drawn under different operating conditions. It can be applied to data ... -
Bearings fault detection using inference tools
(In-Tech, 2011-09)
Capítol de llibre
Accés obertThe most used electric machine in the industry is the Induction Motor (IM), due to its simplicity and reduced cost. The analysis of the origin of IMs failures exhibits that the bearings are the major source of fault, and ... -
Chromatic monitoring of gear mechanical degradation based on acoustic emission
(Institute of Electrical and Electronics Engineers (IEEE), 2017-11-01)
Article
Accés obertThis paper presents a methodology for the feature estimation of a new fault indicator focused on detecting gear mechanical degradation under different operating conditions. Preprocessing of acoustic emission signal is ... -
Condition monitoring strategy based on an optimized selection of high-dimensional set of hybrid features to diagnose and detect multiple and combined faults in an induction motor
(Elsevier, 2021-06-01)
Article
Accés obertThe development of novel condition monitoring strategies represents a critical challenge to ensure the effectiveness and reliability of complex industrial processes. Indeed, the interconnectivity of multiple variables ... -
Condition monitoring strategy based on spectral energy estimation and linear discriminant analysis applied to electric machines
(2018)
Text en actes de congrés
Accés obertCondition-based maintenance plays an important role to ensure the working condition and to increase the availability of the machinery. The feature calculation and feature extraction are critical signal processing that allow ... -
Condition monitoring system for characterization of electric motor ball bearings with distributed fault using fuzzy inference tools
(2010-05-06)
Article
Accés obertThe present work shows a condition monitoring system applied to electric motors ball bearings. Unlike most of the previous work on this area, which is mainly focused on the location of single-point defects in bearing ...
