Departamento de Ingenieria Electrónica y de Computadoreshttp://hdl.handle.net/10396/812024-03-19T11:03:16Z2024-03-19T11:03:16ZData mining in predictive maintenance systems: A taxonomy and systematic reviewEsteban, AuroraZafra, AmeliaVentura, Sebastiánhttp://hdl.handle.net/10396/276412024-03-08T03:00:47Z2022-01-01T00:00:00ZData mining in predictive maintenance systems: A taxonomy and systematic review
Esteban, Aurora; Zafra, Amelia; Ventura, Sebastián
Predictive maintenance is a field of study whose main objective is to optimize the timing and type of maintenance to perform on various industrial systems. This aim involves maximizing the availability time of the monitored system and minimizing the number of resources used in maintenance. Predictive maintenance is currently undergoing a revolution thanks to advances in industrial systems monitoring within the Industry 4.0 paradigm. Likewise, advances in artificial intelligence and data mining allow the processing of a great amount of data to provide more accurate and advanced predictive models. In this context, many actors have become interested in predictive maintenance research, becoming one of the most active areas of research in computing, where academia and industry converge. The objective of this paper is to conduct a systematic literature review that provides an overview of the current state of research concerning predictive maintenance from a data mining perspective. The review presents a first taxonomy that implies different phases considered in any data mining process to solve a predictive maintenance problem, relating the predictive maintenance tasks with the main data mining tasks to solve them. Finally, the paper presents significant challenges and future research directions in terms of the potential of data mining applied to predictive maintenance.
2022-01-01T00:00:00ZFast FPGA prototyping to explore and compare new SPWM strategiesGeninatti, Sergio R.Ortiz-López, ManuelQuiles-Latorre, Francisco JavierMorales-Leal, TomásGersnoviez, AndrésMoreno-Muñoz, A.http://hdl.handle.net/10396/272822024-02-19T11:26:02Z2024-01-01T00:00:00ZFast FPGA prototyping to explore and compare new SPWM strategies
Geninatti, Sergio R.; Ortiz-López, Manuel; Quiles-Latorre, Francisco Javier; Morales-Leal, Tomás; Gersnoviez, Andrés; Moreno-Muñoz, A.
This study presents a Flexible Test Bench (FTB) implemented with FPGA that synthesises of a large number of strategies that apply “Spread Spectrum” to reduce the energy of the fundamental harmonics present in a conventional Pulse Width Modulation (PWM). The FTB not only incorporates most of the known spread spectrum techniques but also allows to combine them and even to easily create new ones, thus providing a highly flexible test bench. The FTB has been described in standard VHDL, so it can be synthesised using any synthesis tool, and the number of logical resources used by each of them can be determined according to the spread spectrum strategy configured in its registers. Therefore, a tool is available to choose, according to the spectral response and the consumption of logic resources, the most suitable PWM spread spectrum strategy for each application. The particularity of the proposal is to have a unique hardware platform that allows the comparison of different techniques under the same physical implementation conditions since geometry and physical location are important when evaluating the conducted and radiated emission of the circuits. Another objective of our FTB is to solve in a unified way all the numerical aspects present in the FPGA-based implementation so that the numerical ranges and roundings used affect all the implemented techniques equally.
2024-01-01T00:00:00ZNeuro-fuzzy systems for daily solar irradiance classification and PV efficiency forecastingGersnoviez, AndrésGámez Granados, Juan CarlosCabrera-Fernández, MartaSantiago, IsabelCañete-Carmona, EduardoBrox-Jiménez, Maríahttp://hdl.handle.net/10396/272802024-02-19T11:28:47Z2023-01-01T00:00:00ZNeuro-fuzzy systems for daily solar irradiance classification and PV efficiency forecasting
Gersnoviez, Andrés; Gámez Granados, Juan Carlos; Cabrera-Fernández, Marta; Santiago, Isabel; Cañete-Carmona, Eduardo; Brox-Jiménez, María
Considering the impact of photovoltaic installations and the fact that their performance depends on the type of day, this paper presents a classifier that makes use of fuzzy logic to classify daily irradiance profiles as a human would do. To do this, the system must be linguistically interpretable, so the classifier must be simple enough, but without losing accuracy. This is why the article combines the use of data mining and supervised learning algorithms to obtain an initial system and then exploits simplification techniques such as the concept of fuzzy classifiers with incomplete rule bases, as well as fuzzy tabular simplification of rules to obtain a compact and simple final system. The classifier obtained handles the ambiguity presented by the daily irradiance profiles with precision. Once the system has been obtained, a large number of days in southern Spain are classified, analysing the performances of a photovoltaic plant obtained in each of the classes. Then, a neuro-fuzzy system is designed to predict the performance of the photovoltaic installation, considering the type of day, the maximum ambient temperature reached during the day, and the degradation of the installation over time, proving its usefulness in alerting about anomalous behaviour of the system.
2023-01-01T00:00:00ZAn IoT barrel bung to monitor evolution wine elaborated under biological agingCañete-Carmona, EduardoGallego-Martínez, Juan-JoséYousef-Jiménez, LailaRuiz Flores, AlbertoGersnoviez, AndrésMoreno, Juanhttp://hdl.handle.net/10396/272782024-02-19T11:15:51Z2022-01-01T00:00:00ZAn IoT barrel bung to monitor evolution wine elaborated under biological aging
Cañete-Carmona, Eduardo; Gallego-Martínez, Juan-José; Yousef-Jiménez, Laila; Ruiz Flores, Alberto; Gersnoviez, Andrés; Moreno, Juan
Wine aging is a crucial step in the elaboration of special and high quality wines as the sherry and
like-sherry type wines are. Some of these wines remain in oak barrels during a long time period,
subjected to the “biological aging” process, which is characterized by the maintenance of a yeast
biofilm over the wine surface. This yeast´s layer protects the wine from the oxidation and contribute
to its specific organoleptic characteristics. This work shows an instrumented bung for monitoring a set
of parameters to control this wine aging process. Tests carried out in a winery over 5 months, under
real conditions, prove that this device is capable of monitoring key parameters of wine subjected to
biological aging in a wireless way, working autonomously for more than a year.
2022-01-01T00:00:00Z