Now showing items 1-20 of 21

    • A data-driven-based industrial refrigeration optimization method considering demand forecasting 

      Cirera Balcells, Josep; Cariño Corrales, Jesús Adolfo; Zurita Millán, Daniel; Ortega Redondo, Juan Antonio (2020-05-21)
      Article
      Open Access
      One 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 ...
    • Chromatic monitoring of gear mechanical degradation based on acoustic emission 

      Delgado Prieto, Miquel; Zurita Millán, Daniel (Institute of Electrical and Electronics Engineers (IEEE), 2017-11-01)
      Article
      Open Access
      This 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 ...
    • Contributions to industrial process condition forecasting applied to copper rod manufacturing process 

      Zurita Millán, Daniel (Universitat Politècnica de Catalunya, 2017-09-08)
      Doctoral thesis
      Open Access
      Ensuring reliability and robustness of operation is one of the main concerns in industrial anufacturing processes , dueto the ever-increasing demand for improvements over the cost and quality ofthe processes outcome. In ...
    • Data analytics for performance evaluation under uncertainties applied to an industrial refrigeration plant 

      Cirera Balcells, Josep; Cariño Corrales, Jesús Adolfo; Zurita Millán, Daniel; Ortega Redondo, Juan Antonio (Institute of Electrical and Electronics Engineers (IEEE), 2019-01-01)
      Article
      Open Access
      Artificial 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 

      Cirera Balcells, Josep; Quiles Zaguirre, Maria; Cariño Corrales, Jesús Adolfo; Zurita Millán, Daniel; Ortega Redondo, Juan Antonio (Institute of Electrical and Electronics Engineers (IEEE), 2018)
      Conference report
      Restricted access - publisher's policy
      Industrial 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 

      Zurita Millán, Daniel; Cariño Corrales, Jesús Adolfo; Delgado Prieto, Miquel; Ortega Redondo, Juan Antonio (Institute of Electrical and Electronics Engineers (IEEE), 2014)
      Conference report
      Restricted access - publisher's policy
      The 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 

      Cariño Corrales, Jesús Adolfo; Delgado Prieto, Miquel; Zurita Millán, Daniel; Millan, Marta; Ortega Redondo, Juan Antonio; Romero Troncoso, Rene De Jesus (Institute of Electrical and Electronics Engineers (IEEE), 2016-10-19)
      Article
      Open Access
      This 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 

      Delgado Prieto, Miquel; Cariño Corrales, Jesús Adolfo; Zurita Millán, Daniel; Millán Gonzálvez, Marta; Ortega Redondo, Juan Antonio; Romero Troncoso, René de Jesús (InTech, 2017-05-31)
      Part of book or chapter of book
      Open Access
      Dealing 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 machinery 

      Cariño Corrales, Jesús Adolfo; Delgado Prieto, Miquel; Iglesias Martínez, José Antonio; Sanchís, Araceli; Zurita Millán, Daniel; Millan, Marta; Ortega Redondo, Juan Antonio; Romero Troncoso, René (Institute of Electrical and Electronics Engineers (IEEE), 2018-09-03)
      Article
      Open Access
      An 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 

      Cariño Corrales, Jesús Adolfo; Zurita Millán, Daniel; Delgado Prieto, Miquel; Ortega Redondo, Juan Antonio; Romero Troncoso, Rene De Jesus (Institute of Electrical and Electronics Engineers (IEEE), 2014)
      Conference report
      Restricted access - publisher's policy
      Abstract: 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 ...
    • Incremental novelty detection and fault identification scheme applied to a kinematic chain under non-stationary operation 

      Cariño Corrales, Jesús Adolfo; Delgado Prieto, Miquel; Zurita Millán, Daniel; Picot, Antoine; Ortega Redondo, Juan Antonio; Romero Troncoso, René (2019-01-01)
      Article
      Restricted access - publisher's policy
      Classical 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 

      Zurita Millán, Daniel; Delgado Prieto, Miquel; Cariño Corrales, Jesús Adolfo; Clerc, Guy; Ortega Redondo, Juan Antonio; Razik, Hubert; Osornio Rios, Roque A. (2019-08-01)
      Article
      Open Access
      The 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 

      Zurita Millán, Daniel; Sala Cardoso, Enric; Cariño Corrales, Jesús Adolfo; Delgado Prieto, Miquel; Ortega Redondo, Juan Antonio (IEEE Press, 2016)
      Conference report
      Open Access
      Industrial 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 

      Zurita Millán, Daniel; Delgado Prieto, Miquel; Cariño Corrales, Jesús Adolfo; Ortega Redondo, Juan Antonio; Clerc, Guy (Institute of Electrical and Electronics Engineers (IEEE), 2016-09-20)
      Article
      Open Access
      Abstract—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 ...
    • Intelligent sensor based on acoustic emission analysis applied to gear fault diagnosis 

      Zurita Millán, Daniel; Delgado Prieto, Miquel; Ortega Redondo, Juan Antonio; Romeral Martínez, José Luis (Institute of Electrical and Electronics Engineers (IEEE), 2013)
      Conference report
      Restricted access - publisher's policy
      The development of intelligent and autonomous monitoring systems applied to rotating machinery, represents the evolution towards the automatic industrial plants supervision. In this regard, an acoustic emission based ...
    • Mechanical fault detection by means of AE analysis 

      Zurita Millán, Daniel (Universitat Politècnica de Catalunya, 2013-02)
      Master thesis (pre-Bologna period)
      Open Access
      Rotating machinery is widely used in all of the industrials fields. In this sense, mechanical components are common elements in these systems. Therefore a periodic revision of the mechanical components of the system is ...
    • Multimodal forecasting methodology applied to industrial process monitoring 

      Zurita Millán, Daniel; Delgado Prieto, Miquel; Cariño Corrales, Jesús Adolfo; Ortega Redondo, Juan Antonio (2017-09-20)
      Article
      Open Access
      IEEE 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 ...
    • Self-powered wireless sensor applied to gear diagnosis based on acoustic emission 

      Delgado Prieto, Miquel; Zurita Millán, Daniel; Wang, Wensi; Machado Ortiz, Anderson; Ortega Redondo, Juan Antonio; Romeral Martínez, José Luis (2016-01-01)
      Article
      Open Access
      Advanced sensing strategies in the industrial sector are becoming a valued technological answer to increase the performance and competitiveness. The development of enhanced sensing solutions considering both technology and ...
    • Semisupervised refrigeration plant cooling disaggregation by means of deep neural network ensemble 

      Cirera Balcells, Josep; Cariño Corrales, Jesús Adolfo; Zurita Millán, Daniel; Ortega Redondo, Juan Antonio (Institute of Electrical and Electronics Engineers (IEEE), 2019)
      Conference report
      Restricted access - publisher's policy
      The 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 ...
    • Vibration signal forecasting on rotating machinery by means of signal decomposition and neuro-fuzzy modeling 

      Zurita Millán, Daniel; Delgado Prieto, Miquel; Saucedo Dorantes, Juan Jose; Cariño Corrales, Jesús Adolfo; Osornio Rios, Roque A.; Ortega Redondo, Juan Antonio; Romero Troncoso, Rene de J. (2016-09-21)
      Article
      Open Access
      Vibration 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 ...