Particle Filter-Based Prognostics for an Electrolytic Capacitor Working in Variable Operating Conditions

International audiencePrognostic models should properly take into account the effects of operating conditions on the degradation process and on the signal measurements used for monitoring. In this work, we develop a Particle Filter-based (PF) prognostic model for the estimation of the Remaining Useful Life (RUL) of aluminum electrolytic capacitors used in electrical automotive drives, whose operation is characterized by continuously varying conditions. The capacitor degradation process, which remarkably depends from the temperature experienced by the component, is typically monitored by observing the capacitor Equivalent Series Resistance (ESR). However, the ESR measurement is influenced by the temperature at which the measurement is performed, which changes depending on the operating conditions. To address this problem, we introduce a novel degradation indicator independent from the measurement temperature. Such indicator can, then, be used for the prediction of the capacitor degradation and its RUL. For this, we develop a Particle Filter prognostic model, whose performance is verified on data collected in simulated and experimental degradation tests

Familia, envejecimiento y discapacidad en España

Durante el año 2003, en aquel momento como Centro de Estudios Demográficos, se nos encargó el informe general de la Encuesta sobre discapacidades, deficiencias y estado de salud, 1999. Dicho informe, elaborado con la experta colaboración del Grupo de Investigación sobre Envejecimiento (CSIC), se publicó en 2005. Aunque la discapacidad es lógicamente su objetivo principal, la fuente está claramente diseñada para sondear la relación existente entre quienes padecen estos problemas y su entorno familiar inmediato. Esta virtualidad es la que se ha pretendido explotar temáticamente aquí. En el presente artículo, se exponen algunos de los resultados obtenidos en el informe, articulados temáticamente en torno a estos dos terrenos, el de la edad y el del entorno convivencial inmediato

Very short-term load forecaster based on a neural network technique for smart grid control

Electrical load forecasting plays a crucial role in the proper scheduling and operation of power systems. To ensure the stability of the electrical network, it is necessary to balance energy generation and demand. Hence, different very short-term load forecast technologies are being designed to improve the efficiency of current control strategies. This paper proposes a new forecaster based on artificial intelligence, specifically on a recurrent neural network topology, trained with a Levenberg–Marquardt learning algorithm. Moreover, a sensitivity analysis was performed for determining the optimal input vector, structure and the optimal database length. In this case, the developed tool provides information about the energy demand for the next 15 min. The accuracy of the forecaster was validated by analysing the typical error metrics of sample days from the training and validation databases. The deviation between actual and predicted demand was lower than 0.5% in 97% of the days analysed during the validation phase. Moreover, while the root mean square error was 0.07 MW, the mean absolute error was 0.05 MW. The results suggest that the forecaster’s accuracy is considered sufficient for installation in smart grids or other power systems and for predicting future energy demand at the chosen sites

Using deep learning and meteorological parameters to forecast the photovoltaic generators intra-hour output power interval for smart grid control

In recent years, the photovoltaic generation installed capacity has been steadily growing thanks to its inexhaustible and non-polluting characteristics. However, solar generators are strongly dependent on intermittent weather parameters, increasing power systems' uncertainty level. Forecasting models have arisen as a feasible solution to decreasing photovoltaic generators' uncertainty level, as they can produce accurate predictions. Traditionally, the vast majority of research studies have focused on the develop- ment of accurate prediction point forecasters. However, in recent years some researchers have suggested the concept of prediction interval forecasting, where not only an accurate prediction point but also the confidence level of a given prediction are computed to provide further information. This paper develops a new model for predicting photovoltaic generators' output power confidence interval 10 min ahead, based on deep learning, mathematical probability density functions and meteorological parameters. The model's accuracy has been validated with a real data series collected from Spanish meteorological sta- tions. In addition, two error metrics, prediction interval coverage percentage and Skill score, are computed at a 95% confidence level to examine the model's accuracy. The prediction interval coverage percentage values are greater than the chosen confidence level, which means, as stated in the literature, the proposed model is well-founded

The short-term mortality fluctuation data series, monitoring mortality shocks across time and space.

The COVID-19 pandemic has revealed substantial coverage and quality gaps in existing international and national statistical monitoring systems. It is striking that obtaining timely, accurate, and comparable across countries data in order to adequately respond to unexpected epidemiological threats is very challenging. The most robust and reliable approach to quantify the mortality burden due to short-term risk factors is based on estimating weekly excess deaths. This approach is more reliable than monitoring deaths with COVID-19 diagnosis or calculating incidence or fatality rates affected by numerous problems such as testing coverage and comparability of diagnostic approaches. In response to the emerging data challenges, a new data resource on weekly mortality has been established. The Short-term Mortality Fluctuations (STMF, available at www.mortality.org ) data series is the first international database providing open-access harmonized, uniform, and fully documented data on weekly all-cause mortality. The STMF online vizualisation tool provides an opportunity to perform a quick assessment of the excess weekly mortality in one or several countries by means of an interactive graphical interface

Covid-19: la malinterpretación de los datos de la pandemia daña la confianza del público

Dos cartas publicadas en The Lancet y The Lancet Public Health en los últimos meses defienden la necesidad de evaluar de forma independiente la respuesta española ante la covid-19. Estamos de acuerdo, pero nos gustaría complementarlas con tres puntos que nos acercan a la ciencia abierta. Nos referimos a la confusión terminológica, la calidad de los datos y su disponibilidad

Early mobilisation in critically ill COVID-19 patients: a subanalysis of the ESICM-initiated UNITE-COVID observational study

Background Early mobilisation (EM) is an intervention that may improve the outcome of critically ill patients. There is limited data on EM in COVID-19 patients and its use during the first pandemic wave. Methods This is a pre-planned subanalysis of the ESICM UNITE-COVID, an international multicenter observational study involving critically ill COVID-19 patients in the ICU between February 15th and May 15th, 2020. We analysed variables associated with the initiation of EM (within 72 h of ICU admission) and explored the impact of EM on mortality, ICU and hospital length of stay, as well as discharge location. Statistical analyses were done using (generalised) linear mixed-effect models and ANOVAs. Results Mobilisation data from 4190 patients from 280 ICUs in 45 countries were analysed. 1114 (26.6%) of these patients received mobilisation within 72 h after ICU admission; 3076 (73.4%) did not. In our analysis of factors associated with EM, mechanical ventilation at admission (OR 0.29; 95% CI 0.25, 0.35; p = 0.001), higher age (OR 0.99; 95% CI 0.98, 1.00; p ≤ 0.001), pre-existing asthma (OR 0.84; 95% CI 0.73, 0.98; p = 0.028), and pre-existing kidney disease (OR 0.84; 95% CI 0.71, 0.99; p = 0.036) were negatively associated with the initiation of EM. EM was associated with a higher chance of being discharged home (OR 1.31; 95% CI 1.08, 1.58; p = 0.007) but was not associated with length of stay in ICU (adj. difference 0.91 days; 95% CI − 0.47, 1.37, p = 0.34) and hospital (adj. difference 1.4 days; 95% CI − 0.62, 2.35, p = 0.24) or mortality (OR 0.88; 95% CI 0.7, 1.09, p = 0.24) when adjusted for covariates. Conclusions Our findings demonstrate that a quarter of COVID-19 patients received EM. There was no association found between EM in COVID-19 patients' ICU and hospital length of stay or mortality. However, EM in COVID-19 patients was associated with increased odds of being discharged home rather than to a care facility. Trial registration ClinicalTrials.gov: NCT04836065 (retrospectively registered April 8th 2021)

Family, ageing and disability in Spain

Resumen: Durante el año 2003, en aquel momento como Centro de Estudios Demográficos, se nos encargó el informe general de la Encuesta sobre discapacidades, deficiencias y estado de salud, 1999. Dicho informe, elaborado con la experta colaboración del Grupo de Investigación sobre Envejecimiento (CSIC), se publicó en 2005. Aunque la discapacidad es lógicamente su objetivo principal, la fuente está claramente diseñada para sondear la relación existente entre quienes padecen estos problemas y su entorno familiar inmediato. Esta virtualidad es la que se ha pretendido explotar temáticamente aquí. En el presente artículo, se exponen algunos de los resultados obtenidos en el informe, articulados temáticamente en torno a estos dos terrenos, el de la edad y el del entorno convivencial inmediato. Resumen: During the year 2003, the Demographic Studies Center was in charge of the general report of the Survey about Discapacities, Deficiencies and the State of Health, 1999. This report, elaborated with the expert collaboration of the Research Group on Ageing (CSIC), was published in 2005. Although disability logically is its primary target, the source is clearly designed to sound out the existing relation between those who suffer these problems and their immediate family environment. This potential has been tried to exploit thematically here. In the present article some of the results obtained in the report are exposed, thematically formulated around these two areas: age and the immediate co-habitational environment.Peer reviewe