Search

This paper proposes a new prognostic method capable of preventing catastrophic failures in Medium Voltage (MV) power cables. The main objective is the development of a monitoring system focused on the detection and localization of cable overtemperatures in underground distribution networks. The predictive analysis proposed here is based on a Multi-Layer neural network with Multi-Valued Neurons (MLMVN), which elaborates measurements of high frequency signals transmitted through Power Line Communication (PLC) devices. Therefore, the prognostic method does not require the introduction of additional components since the power line is already equipped with a communication system. This allows low intrusion and the possibility of monitoring power lines during their operation. Furthermore, the MLMVN-based classifier processes magnitude and phase of the received signals without preliminary coding steps and ensures a low computational cost. The main theoretical concept on which the predictive analysis is based is the detection of malfunctions starting from their effects on the cable parameters. For this reason, an RG7H1M1 cable has been experimentally characterized in the frequency range between 90 kHz and 1 MHz, both in nominal conditions and in overheating situations generated by means of a climatic chamber. The changes in the electrical parameters of the cable modify the transmitted signal and the monitoring system proposed here allows the identification and localization of the overheated section with high accuracy.

The recent development of highly automated machinery and intelligent industrial plants has increasingly enabled the continuous monitoring of their efficiency and condition, with the aim of maintaining high production efficiency and minimal malfunctions. Typical condition monitoring and fault detection applications are often achieved using acoustic and vibrational techniques, but the availability of distributed electrical measurements opens new opportunities for industrial fault detection with minimal impact on electrical systems. Even if artificial intelligence (AI)-based approaches can be used to model industrial equipment by means of measures made on electrical systems to which they are connected, machine learning algorithms have been demonstrated to be particularly adequate for this purpose due to the huge amount of data produced by interconnected sensors and devices. In this context, the aim of this work is to propose a new unsupervised analysis methodology for detecting anomalies in industrial machinery using electrical current values and other parameters measured on the power grid. The proposed framework is aimed at incorporating the advantages of machine learning algorithms and those of traditional analysis, optimizing their operation to improve performance and execution time; this also incorporates a methodology for analyzing the temporal dynamics of the anomaly based on short-time Fourier transform (STFT) to strengthen the performance of the detection. The results obtained showed excellent performance, both compared to the evaluations of a technical expert and to other methodologies used in the literature, with zero false positives (FPs) detected in all datasets tested and a negligible number of undetected outlier events, less than 4% of the total in the datasets.

Purpose: The design of a space launcher requires some considerations about the unsteady loads and heat transfer occurring at the base of the structure. In particular, these phenomena are predominant during the early stage of the flight. This paper aims to evaluate the ability of the unstructured, high order finite-volume CFD solver FLUSEPA, developed by Airbus Safran Launchers, to accurately describe these phenomena. Design/methodology/approach: This paper first performs a steady simulation on a base flow around a four-clustered rocket configuration. Results are compared with NASA experiments and Loci-CHEM simulations. Then, unsteady simulations of supersonic H2/air reacting mixing layer based on the experiment of Miller, Bowman and Mungal are performed. Three meshes with different cells number are used to study the impact of spatial resolution. Instantaneous and time-averaged concentrations are compared with the combined OH/acetone planar laser-induced fluorescence imaging from the experiment. Findings: FLUSEPA satisfactorily predicts the base heat flux at the base of a four-clustered rocket configuration. NASA Loci-CHEM reactive simulations indicate that afterburning plays an important role and should not be neglected. The unsteady reactive computation of a supersonic mixing layer shows that FLUSEPA is also able to accurately predict flow structures and interactions. However, the complexity of the experiment and the lack of details concerning the facility prevents from obtaining satisfactory converged results. Originality/value: This study is the first step on the development of a cost-effective method aiming at predicting unsteady loads and heat transfer on space launchers using an unsteady and reactive model for the CDF calculations. It uses original techniques such as conservative CHIMERA-like overset grids, local re-centering of fluxes and local adaptive time-stepping to reduce computational cost while being robust and accurate. [ABSTRACT FROM AUTHOR]

Underwater vehicle propulsion performed by exploiting electrical motor is in general the most flexible solution and it is growing in popularity because of its high efficiency both at high and at low advance speed, quick and simple deployment, low costs, and encumbrance. In the present work, permanent magnet synchronous motors for underwater propulsion are proposed. In particular, advanced sensorless control techniques of permanent magnet synchronous motors permit reduced costs, high reliability, and performances. When dealing with small autonomous underwater vehicle propulsion, such devices are hard to find in the market. Hence, the authors focused the research in the development of a system able to perform a reliable rotational speed and torque sensorless estimation. The design and implementation of a complete solution for underwater propulsion are presented as well as a novel rotor polarity identification technique exploiting a high-frequency injection control. Pool tests for the identification of the performances and of the dynamic parameters of the propulsion system are presented. Finally, the possibility of operating a sensorless estimation of the thrust and torque exerted by the propeller and pool test measurements are presented. These features could be exploited to improve navigation accuracy and involves obvious benefits in terms of cost reduction and reliability of the system.

Green shuttle vehicle (GSV) is a multi-purpose, four wheeled electric vehicle designed to operate in naturally protected areas where the conventional vehicles with internal combustion engines (ICEs) should be forbidden as a possible source of noise and pollution. The powertrain is based on a traction system with four in-wheel, permanent magnet motors that allow the vehicle to exhibit potentially interesting performances in terms of longitudinal dynamics, autonomy, and stability, even considering degraded adhesion conditions. In particular, this work also simulates the behaviour of the vehicle in degraded adhesion conditions, implementing a preliminary version of electric traction/braking fuzzy logic controller. The complete design and simulation of the system are an interesting example of how modern multi-disciplinary simulation tools can really accelerate the development of such a system with time and cost that are affordable also for small scale production series.

Le concept de retrait relationnel durable chez le jeune enfant est présenté dans son historique et ses liens avec la dépression du nourrisson. Le comportement de retrait relationnel durable du jeune enfant s’observe dans diverses situations comme les troubles de l’attachement, l’autisme, les troubles sensoriels, la douleur chronique, les troubles interactifs précoces, et aussi comme effet de la dépression maternelle. L’échelle «alarme détresse bébé » (ADBB) comprend 8items. Elle a été construite pour faciliter le dépistage précoce du retrait relationnel en utilisant, par exemple, la situation de l’examen de routine en centre de PMI. Les applications en clinique et en recherche, ainsi que les validations récentes de l’échelle sont présentées.

Sommario E' stato sviluppato un modello tridimensionale, per studiare la fluidodinamica con o senza combustione di una carica omogenea in un Motore ad Accensione Comandata. E' stata impiegata una tecnica esplicita del tipo predictor-corrector. Il modello è stato convalidato nella sua versïone bidimensionale confrontando la intensità della turbolenza calcolata al punto morto superiore con dati sperimentali e con risultati ottenuti con un diverso modello bidimensionale precedentemente convalidato. Il modello tridimensionale è stato quindi usato per simulare la fluidodinamica fredda di una carica omogenea in una camera di combustione di tipo pancake. Si è concluso che il modello può essere impiegato per la simulazione della fluidodinamica in un Motore ad Accencione Comandata.

In cases where the femur or tibial deformity is not correctly analysed, the corrective osteotomies may result in an oblique joint line. The aim of this study was to assess the preoperative deformity of patients due to undergo corrective osteotomy and the resulting abnormal tibial and femoral morphologies after the planned correction using 3D software.