Browsing by Author "Osornio Rios, Roque A."
Now showing items 1-20 of 24
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A novel deep learning-based diagnosis method applied to power quality disturbances
(2021-05-02)
Article
Open AccessMonitoring 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 ... -
Advances in power quality analysis techniques for electrical machines and drives: a review
(2022-03-01)
Article
Open AccessThe 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 ... -
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 ... -
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
Open AccessThe 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)
Conference report
Open AccessCondition-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 ... -
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-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 ... -
Diagnosis Methodology Based on Statistical-time Features and Linear Discriminant Analysis Applied to Induction Motors
(2017)
Conference report
Restricted access - publisher's policyThe development of condition monitoring strategies is necessary to ensure the efficiency and reliability of the operation on electric machines. The feature calculation is an important signal processing step used to obtain ... -
Diagnosis methodology for identifying gearbox wear based on statistical time feature reduction
(2017-01-01)
Article
Open AccessStrategies for condition monitoring are relevant to improve the operation safety and to ensure the efficiency of all the equipment used in industrial applications. The feature selection and feature extraction are suitable ... -
Incremental learning framework-based condition monitoring for novelty fault identification applied to electromechanical systems
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Conference report
Open AccessA 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 ... -
Industrial data-driven monitoring based on incremental learning applied to the detection of novel faults
(2020-09-01)
Article
Open AccessThe detection of uncharacterized events during electromechanical systems operation represents one of the most critical data challenges dealing with condition-based monitoring under the Industry 4.0 framework. Thus, the ... -
Industrial process condition forecasting methodology based on neo-fuzzy neuron and self-organizing maps
(2019-08-01)
Article
Open AccessThe 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 ... -
Multifault diagnosis method applied to an electric machine based on high-dimensional feature reduction
(2016-12-07)
Article
Open AccessCondition monitoring schemes are essential for increasing the reliability and ensuring the equipment efficiency in industrial processes. The feature extraction and dimensionality reduction are useful preprocessing steps ... -
Multiple-fault detection and identification scheme based on hierarchical self-organizing maps applied to an electric machine
(2019-08-01)
Article
Open AccessStrategies of condition monitoring applied to electric motors play an important role in the competitiveness of multiple industrial sectors. However, the risk of faults coexistence in an electric motor and the overlapping ... -
Novel condition monitoring approach based on hybrid feature extraction and neural network for assessing multiple faults in electromechanical systems
(Institute of Electrical and Electronics Engineers (IEEE), 2019)
Conference report
Restricted access - publisher's policyNew challenges involve the development of new condition monitoring approaches to avoid unexpected downtimes and to ensure the availability of machines during operating working conditions. The feature calculation from ... -
Novelty detection based condition monitoring scheme applied to electromechanical systems
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Conference report
Open AccessThis 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 ...
