In this paper, a monitoring method for DC-DC converters in photovoltaic applications is presented. The primary goal to prevent catastrophic failures by detecting malfunctioning conditions during the operation of electrical system. proposed prognostic procedure based on machine learning techniques and focuses variations passive components with respect their nominal range. A theoretical study choose best measurements analysis adapt order facilitate study, graphical assessment testability...

In this article, we propose a monitoring procedure based on multilayer neural network with multivalued neurons (MLMVN) capable of preventing catastrophic failures dc–dc converters. The classifier allows both the detection any malfunction and its localization. Thanks to low computational complexity, proposed method operates online, estimating deviations passive components from their nominal values: control strategies be promptly adopted operation converter kept in high efficiency reliability...

In this paper, we present a new method designed to recognize single parametric faults in analog circuits. The technique follows rigorous approach constituted by three sequential steps: calculating the testability and extracting ambiguity groups of circuit under test (CUT); localizing failure putting it correct fault class (FC) via multi-frequency measurements or simulations; (optional) estimating value faulty component. fabrication tolerances healthy components are taken into account every...

Integrating a grid-connected battery into renewable energy community amplifies the collective self-consumption of photovoltaic and facilitates arbitrage in electricity markets. However, how much can independence really increase? Is it cost-effective investment? The answer to these questions represents novelty literature due innovative nature asset under consideration market regulatory framework which is evaluated. Employing net present value assessment, our analysis incorporated aging...

Abstract Laparoscopic transabdominal preperitoneal inguinal hernia repair is a safe and effective technique. In this study we tested the hypothesis that self-gripping mesh used with laparoscopic approach comparable to polypropylene in terms of perioperative complications, against lower overall cost procedure. We carried out prospective randomized trial comparing group 30 patients who underwent versus received fibrin glue fixation. There were no statistically significant differences between...

The main objective of this paper is to propose two innovative monitoring methods for electrical disturbances in low-voltage networks. approaches present a focus on the classification voltage signals frequency domain using machine learning techniques. first technique proposed here uses Fourier transform (FT) waveform and classifies corresponding complex coefficients through multilayered neural network with multivalued neurons (MLMVN). In case, classifier structure has three layers small...

This paper proposes a new prognostic method capable of preventing catastrophic failures in Medium Voltage (MV) power cables. The main objective is the development monitoring system focused on detection and localization cable overtemperatures underground distribution networks. predictive analysis proposed here based Multi-Layer neural network with Multi-Valued Neurons (MLMVN), which elaborates measurements high frequency signals transmitted through Power Line Communication (PLC) devices....

This paper presents a rule-based control strategy for the Battery Management System (BMS) of prosumer connected to low-voltage distribution network. The main objective this work is propose computationally efficient algorithm capable managing energy flows between network and equipped with photovoltaic (PV) production system. goal BMS maximize prosumer’s economic revenue by optimizing use, storage, sale, purchase PV based on electricity market information daily production/consumption curves....

A smart monitoring system capable of detecting and classifying the health conditions MV (Medium Voltage) underground cables is presented in this work. Using analysis technique proposed here, it possible to prevent occurrence catastrophic failures medium voltage lines, for which generally difficult realize maintenance operations carry out punctual inspections. This prognostic method based on Frequency Response Analysis (FRA) can be used online during normal network operation, resulting a...

In this paper a comparison is presented between two strategies for the control of Dual Active Bridge (DAB) converter regulated through Single Phase Shift (SPS) modulation. The purpose controller to regulate phase-shift voltage impressed inductor from primary and secondary obtain desired output current. To achieve goal, based on different approaches are proposed. first one performs regulation using Proportional-Integral (PI) controller, while second one, called Model Reference Control (MRC),...

The importance of testability analysis in neural network based fault diagnosis DC-DC converters is discussed this paper. Theoretical fundamentals and an applicative example are presented, by taking into account the single-fault hypothesis. A program for switched used example. It relies on symbolic techniques, which may be to simulate circuits a very easy fast way.

This paper proposes a design optimization method for passive shielding in Wireless Power Transfer (WPT) systems. Starting from charging device developed electric vehicles, the main objective of this work is to study effects different solutions on energy transmission efficiency and electromagnetic emissions. A Finite Element Method (FEM) used evaluate ohmic losses related geometric configurations both plate ferrite bars, as well use materials shielding. As result procedure, mutual inductance...

DC–DC converter fault diagnosis, executed via neural networks built by exploiting the information deriving from testability analysis, is subject of this paper. The under consideration are complex valued (CVNNs), whose fundamental feature proper treatment phase and contained in it. In particular, a multilayer network based on multi-valued neurons (MLMVN) considered. order to effectively design network, analysis exploited. Two possible ways for executing converters proposed, taking into...

The a-priori economic and energetic design of a Renewable Energy Community (REC) requires hourly electric generation load profiles for the community members. are easily inferable, especially in case photovoltaics. consumption trends, on other hand, more unpredictable. For this reason, reconstruction simulated becomes relevant area study. In paper, we propose novel strategy to generate sensible from information commonly found energy bills, adopting machine learning approach based...

Abstract In this paper a new method is developed and described, aimed at the modeling diagnosis of joints connecting ends two cables on high voltage electricity pylon. Identifying anomalous joint behaviour through line frequency response analysis first objective work. For reason, it necessary to model whole overhead with lumped circuit studying electrical parameter variation. The problem approached in multiple steps: modelling, testability model, optimal selection, identification possible...

Allograft artery mycotic aneurysm (MA) represents a rare but life-threatening complication of kidney transplantation. Graftectomy is widely considered the safest option. Due to rarity disease and substantial risk fatal consequences, experience with conservative strategies limited. To date, only few reports on surgical repair have been published. We describe case true MA successfully managed by resection arterial re-anastomosis.An 18-year-old gentleman, post-operative day 70 after deceased...

In this paper a classification system based on complex-valued neural network is used to evaluate the health state of joints in high voltage overhead transmission lines.The aim method prevent breakages through frequency response measurements obtained at initial point network.The specific advantage kind measure be non-intrusive and therefore safer than other approaches, also considering nature lines.A feedforward multi-layer with multi-valued neurons achieve goal.The results for power lines...

Abstract The technique proposed in this work is finalized to the non-intrusive monitoring of high voltage electrical networks. In order develop a prognostic method capable avoiding failures on overhead transmission grids, connection joints between two sections line are considered. based use Frequency Response Analysis (FRA) and machine learning, represented by neural classifier Multi-Valued Neuron (MVN) network. procedure can be considered as smart measurement block, where single measure...

An intact hepatic artery is the gateway to successful hepato-biliary surgery. Introduction of laproscopic cholecystectomy (LC) has stimulated a renewed interest in anatomy artery. In this case report we have highlighted importance variations right terms origin and course We present rare asymptomatic liver atrophy due an intraoperative lesion also performed literature review about surgical vascular lesions tried confirm concept behind "non trivial procedure" LC.

In this paper an original approach and a theoretical method, based on techniques of Frequency Response Analysis (FRA), soft computing machine learning, are described for the continuous monitoring, prognosis fault diagnosis various joint regions overhead lines power transmission. The proposed procedure can be considered intelligent measurement module, where single used by neural processor to extract important information complex electrical system.