Iacopo Marri, Emil Petkovski,Loredana Cristaldi, Marco Faifer
Lithium-ion batteries soh estimation, based on support-vector regression and a feature-based approach

Lithium-Ion batteries, have become enormously used in many systems and applications, and are the most widespread energy storage system. Optimizing the usage of batterie is therefore very important to increase the safety of systems like electric vehicles or portable devices, to reduce economic loss in industrial environments, and to increase their availability. An accurate State of Health (SoH) estimation is important since it allows us to know battery conditions and make an appropriate use of it, and it improves the accuracy of other diagnostic measures, like State of Charge (SoC). In this paper, an approach for SoH estimation is proposed, based on Support Vector Regression machine learning algorithm and a smart feature extraction process, finding a good trade-off between applicability, light computation effort, and accuracy of results. Features selection and parameters tuning are discussed, and performances are measured on a dataset from the Prognostics Center of Excellence at NASA, considering 3 batteries of the dataset.

Yu Jun, Olena Hordiichuk-Bublivska, Yan Lingyu, Marian Kyryk, Mykola Beshley, Hu Jiwei
Big Data Аnalysis in Smart Grid Systems

The problem of Big Data processing in large industrial systems requires the use of machine learning methods. A smart grid system is an example of improving the efficiency of traditional data processing systems, which allows much more efficient and flexible distribution of electricity to end-users. However, for a smart grid to work properly, it needs to constantly monitor data from sensors and meters. The Singular Value Decomposition (SVD) algorithm is used to improve the efficiency of Big Data processing and reduce its dimensionality. The paper proposes the use of advanced SVD, which can work in distributed industrial systems and ensure the reliability and speed of data processing.

Krzysztof Dowalla, Piotr Bilski, Ryszard Kowalik
Series arc fault detection and line selection based on Non-Intrusive Load Monitoring Method

The series arc faults are a common cause of household fires. Low fault current amplitude is the reason for the difficulties in implementing effective arc detection systems. The paper presents a novel arc detection and line selection method. It can be easily used in the low-voltage Alternate Current (AC) network to enhance the functionality of the Non-Intrusive Load Monitoring (NILM) system with arc detection for the whole household. Unlike existing methods, the proposed approach exploits not only current signal but also voltage signal time domain analysis. In the case of arc fault detection, line selection is based on the mean values of changes in the consecutive current signal periods during the arc and comparing them with current waveforms for each appliance in non-arc conditions. Tests have been conducted with up to 6 devices operating simultaneously in the same circuit. Single period arc detection accuracy was 98.47%, with recall at 97.5% and F-score of 0.983. The arc detection accuracy in terms of the IEC 62606:2013 standard was 99.33%, F-score of 99.33. Line selection accuracy was 91.57%.

Gianluca Albanese, Antonio Delle Femine, Daniele Gallo, Claudio Iodice, Massimo Iorizzo, Carmine Landi, Francesco Letizia, Mario Luiso, Bruno Testa
Measurement of the Effect of Pulsed Electric Fields on the Inactivation of Wine Yeasts

Traditional sterilization techniques for wine (more in general liquid food) often compromise the organoleptic properties of the food itself. Research is underway to find alternative solutions. The pulsed electric field has proved to be an alternative technique for food sterilization. However, scientific papers on this topic report conflicting results regarding treatment details such as the duration, amplitude, frequency and number of required field pulses. In this article, some preliminary experiments will be presented in the application of pulsed electric fields in winemaking, taking care of the aspects related to the measurement of the electrical quantities involved. The experiment was carried out in the first place to evaluate the selectivity of the treatment with respect to the different yeast species naturally present in grape juice. The measurement of the electrical quantities involved is not trivial, the article represents a first effort to develop a correct measurement setup, aimed at providing the scientific community with the first experimental measurement results during the treatment with the pulsed electric field.

E. Natale, G. D’Emilia, L. Chiominto, A. Gaspari, S. Marsella, M. Marzoli
Metrological comparison between instruments for status monitoring of buildings after earthquake

This paper aims to investigate the possibility of using measuring instruments to obtain objective indications of the state of a building following an earthquake, to facilitate the planning of interventions in safe conditions and to design provisional structures. The use of such tools would also be useful for monitoring both buildings and provisional structures over time. In particular, a Laser Scanner and a Total Station are examined and compared from a metrological point of view, to evaluate the possibility of using them in emergency situations, which present particular criticalities for measurements, if the reliability of the results has to be guaranteed. The façade of a historical building is used as a test case, and is subjected to measurement campaigns, distributed over time, with the aim of evaluating repeatability and reproducibility of results. Furthermore, applying known thicknesses to the monitoring points, the systems measuring thresholds are evaluated. This work would like to represent a first step towards the standardization of procedures for the adoption of Laser Scanner and Total Stations by rescuers in emergency situations.