Exploració per autor "Cariño Corrales, Jesús Adolfo"
Ara es mostren els items 1-20 de 21
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A data-driven-based industrial refrigeration optimization method considering demand forecasting
(2020-05-21)
Article
Accés obertOne of the main concerns of industry is energy efficiency, in which the paradigm of Industry 4.0 opens new possibilities by facing optimization approaches using data-driven methodologies. In this regard, increasing the ... -
Data analytics for performance evaluation under uncertainties applied to an industrial refrigeration plant
(Institute of Electrical and Electronics Engineers (IEEE), 2019-01-01)
Article
Accés obertArtificial intelligence has bounced into industrial applications contributing several advantages to the field and have led to the possibility to open new ways to solve many actual problems. In this paper, a data-driven ... -
Data-driven operation performance evaluation of multi-chiller system using self-organizing maps
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Text en actes de congrés
Accés restringit per política de l'editorialIndustrial plants performance evaluation has become a difficult task due to the machinery complexity. Multi-chiller systems take up big proportion of energy in food and beverage companies. Complex refrigeration generation ... -
Distributed neuro-fuzzy feature forecasting approach for condition monitoring
(Institute of Electrical and Electronics Engineers (IEEE), 2014)
Text en actes de congrés
Accés restringit per política de l'editorialThe industrial machinery reliability represents a critical factor in order to assure the proper operation of the whole productive process. In regard with this, diagnosis schemes based on physical magnitudes acquisition, ... -
Enhanced Industrial Machinery Condition Monitoring Methodology based on Novelty Detection and Multi-Modal Analysis
(Institute of Electrical and Electronics Engineers (IEEE), 2016-10-19)
Article
Accés obertThis paper presents a condition-based monitoring methodology based on novelty detection applied to industrial machinery. The proposed approach includes both, the classical classification of multiple a priori known scenarios, ... -
Evaluation of novelty detection methods for condition monitoring applied to an electromechanical system
(InTech, 2017-05-31)
Capítol de llibre
Accés obertDealing with industrial applications, the implementation of condition monitoring schemes must overcome a critical limitation, that is, the lack of a priori information about fault patterns of the system under analysis. ... -
Fault detection and identification methodology under an incremental learning framework applied to industrial electromechanical systems
(Universitat Politècnica de Catalunya, 2017-09-08)
Tesi
Accés obertCondition Based Maintenance is a program that recommends actions based on the information collected and interpreted through condition monitoring and has become accepted since a decade ago by the industry as a key factor ... -
Fault detection and identification methodology under an incremental learning framework applied to industrial machinery
(Institute of Electrical and Electronics Engineers (IEEE), 2018-09-03)
Article
Accés obertAn industrial machinery condition monitoring methodology based on ensemble novelty detection and evolving classification is proposed in this study. The methodology contributes to solve current challenges dealing with ... -
Hierarchical classification scheme based on identification, isolation and analysis of conflictive regions
(Institute of Electrical and Electronics Engineers (IEEE), 2014)
Text en actes de congrés
Accés restringit per política de l'editorialAbstract: A great deal of effort is being made to increase accuracy and reliability of Condition Based Maintenance systems; for instance, by improved feature selection strategies or optimization approaches of classifier ... -
Improving the energy efficiency of industrial refrigeration systems by means of data-driven load management
(2020-09-05)
Article
Accés obertA common denominator in the vast majority of processes in the food industry is refrigeration. Such systems guarantee the quality and the requisites of the final product at the expense of high amounts of energy. In this ... -
Incremental learning framework-based condition monitoring for novelty fault identification applied to electromechanical systems
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Text en actes de congrés
Accés obertA great deal of investigations are being carried out towards the effective implementation of the 4.0 Industry new paradigm. Indeed, most of the machinery involved in industrial processes are intended to be digitalized ... -
Incremental novelty detection and fault identification scheme applied to a kinematic chain under non-stationary operation
(2019-01-01)
Article
Accés obertClassical methods for monitoring electromechanical systems lack two critical functions for effective industrial application: management of unexpected events and the incorporation of new patterns into the knowledge database. ... -
Industrial process condition forecasting methodology based on neo-fuzzy neuron and self-organizing maps
(2019-08-01)
Article
Accés obertThe condition forecasting of industrial processes represents a key factor to allow the future generation of industrial manufacturing plants. In this regard, this paper presents a novel soft-computing based methodology for ... -
Industrial process monitoring by means of recurrent neural networks and Self Organizing Maps
(IEEE Press, 2016)
Text en actes de congrés
Accés obertIndustrial manufacturing plants often suffer from reliability problems during their day-to-day operations which have the potential for causing a great impact on the effectiveness and performance of the overall process and ... -
Industrial time series modelling by means of the neo-fuzzy neuron
(Institute of Electrical and Electronics Engineers (IEEE), 2016-09-20)
Article
Accés obertAbstract—Industrial process monitoring and modelling represents a critical step in order to achieve the paradigm of Zero Defect Manufacturing. The aim of this paper is to introduce the Neo-Fuzzy Neuron method to be applied ... -
Multimodal forecasting methodology applied to industrial process monitoring
(2017-09-20)
Article
Accés obertIEEE Industrial process modelling represents a key factor to allow the future generation of industrial manufacturing plants. In this regard, accurate models of critical signals need to be designed in order to forecast ... -
Novelty detection based condition monitoring scheme applied to electromechanical systems
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Text en actes de congrés
Accés obertThis study is focused on the current challenges dealing with electromechanical system monitoring applied in industrial frameworks, that is, the presence of unknown events and the limitation to the nominal healthy condition ... -
Semisupervised refrigeration plant cooling disaggregation by means of deep neural network ensemble
(Institute of Electrical and Electronics Engineers (IEEE), 2019)
Text en actes de congrés
Accés restringit per política de l'editorialThe awareness of the energy usage has become a recurrent topic during the last decades. Identifying the end-use energy of each individual device can lead to a substantial improvement in efficiency and fault detection. The ... -
Thermography-based methodology for multifault diagnosis on kinematic chain
(2018-12-01)
Article
Accés obertThe procedures for condition monitoring of electromechanical systems are undergoing a reformulation, mainly, due to the current thermographic affordability of infrared cameras to be incorporated in industrial applications. ... -
Vibration signal forecasting on rotating machinery by means of signal decomposition and neuro-fuzzy modeling
(2016-09-21)
Article
Accés obertVibration monitoring plays a key role in the industrial machinery reliability since it allows enhancing the performance of the machinery under supervision through the detection of failure modes. Thus, vibration monitoring ...
