Linear feature selection and classification using PNN and SFAM neural networks for a nearly online diagnosis of bearing naturally progressing degradations.

International audienceIn this work, an effort is made to characterize seven bearing states depending on the energy entropy of Intrinsic Mode Functions (IMFs) resulted from the Empirical Modes Decomposition (EMD).Three run-to-failure bearing vibration signals representing different defects either degraded or different failing components (roller, inner race and outer race) with healthy state lead to seven bearing states under study. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are used for feature reduction. Then, six classification scenarios are processed via a Probabilistic Neural Network (PNN) and a Simplified Fuzzy Adaptive resonance theory Map (SFAM) neural network. In other words, the three extracted feature data bases (EMD, PCA and LDA features) are processed firstly with SFAM and secondly with a combination of PNN-SFAM. The computation of classification accuracy and scattering criterion for each scenario shows that the EMD-LDA-PNN-SFAM combination is the suitable strategy for online bearing fault diagnosis. The proposed methodology reveals better generalization capability compared to previous works and it’s validated by an online bearing fault diagnosis. The proposed strategy can be applied for the decision making of several assets

A System to Search and Recommend Learning Courses Sequences

Traditional recommender systems provide the user with a list of items supposed to be of interest to the user. Each item is a single independent object and the entire result represents alternatives that match user’s preferences. Another category of recommender systems provides recommendations as collections of items. For this type of systems the recommended items are not alternatives but items to be taken in a “certain order”. In this work, we propose a system that recommends learning courses sequences. Another objective of our system is to enable efficient courses search by proposing an approach based on a multi-criteria weighting method. Our general purpose is to recommend sequences of learning courses using the user’s profile and also to search specific courses by keywords and to suggest related courses. Our goal is to facilitate the learning process and satisfy the user’s need

Highly sensitive protection scheme considering the PV operation control models

The integration of distributed generation (DG) based on inverters into power systems has increased significantly, necessitating a thorough understanding of its impact on fault analysis and the performance of distribution networks' protection mechanisms. This study addresses this issue by examining how various inverter management modes influence protective relay systems within IEEE 9-bus redial and mesh networks, CIGRE and IEEE 33-bus networks featuring Photovoltaic (PV) farms and Battery Energy Storage Systems (BESS), by IEEE1547–2018 and German grid code standards. By analyzing grid-connected scenarios with five distinct PV control modes, the research introduces a novel protection methodology termed the Photovoltaic Overcurrent Relay (PVOCR). This method introduces a current-voltage characteristic to optimally coordinate Overcurrent Relays (OCRs), aiming to reduce their operational time and eliminate mis-coordination events. The proposed PVOCR is evaluated against standard inverse time, SOCR, and modern adaptive voltage, VOCR, relay schemes across various fault scenarios differing in type and location. Furthermore, the PVOCR scheme effectively operates across all PV inverter modes without experiencing miscoordination events, whereas the SOCR and VOCR schemes encountered such issues during the operation of Control 4. These results underscore the potential utility of the PVOCR methodology in enhancing the reliability and efficiency of protection systems in inverter-based DG networks

An unusual Monteggia equivalent type 1 lesion: Diaphyseal ulna and radius fractures with a posterior elbow dislocation in a child

In this report, we describe an extremely unusual Monteggia equivalent type 1 lesion in a 10-year-old boy following a fall from a height of 1 m. On the plain radiographs, our patient had a particular Monteggia equivalent type 1 injury associating a posterior elbow dislocation with diaphyseal radius and ulna fractures. The patient was treated by closed reduction technique. At six months of follow-up, the fractures were consolidated and the elbow was stable. To our knowledge, only 8 adult cases and one paediatric observation with similar lesions had been reported through medical literature. Therefore, the aim of our case report is to remind this rare entity and also to provide a comprehensive review of the literature related to this uncommon lesion. Keywords: Monteggia equivalent, Children, Forearm fracture, Elbow dislocatio

Intra-articular knee arborescent lipoma: a case treated with arthroscopic synoviectomy

Arborescent lipoma is an unusual intra-articular lesion that typically develops in the knee and has to be evoked before chronic effusion. It corresponds to hyperplasia of mature fatty tissue and hypertrophy of synovial villi, developing within a joint. The reference treatment is synovectomy by arthrotomy. The rare forms localized to the anterior compartment of the knee can benefit from an arthroscopic synovectomy. Theauthors report a case of arborescent knee lipoma in a 47-year-old patient who received arthroscopic synoviectomy. To our knowledge, only a few cases of arborescent lipoma treated by arthroscopic synoviectomy have been reported in the literature.Key words: Arborescent lipoma, knee, synoviectomy, arthroscopi