Identification de l'évolution de l'usure d'un outil de tournage basée sur l'analyse des efforts de coupe et des vibrations

L’influence de l’usure des outils coupants sur la qualité de l’état de surface demeure un problème principal dans un procédé d'usinage. La surveillance des processus d'usinage joue alors un rôle très important pour éviter l'apparition de certains phénomènes non désirés, tels que l'usure excessive et la rupture de l'outil. Dans ce travail, nous proposons une méthode de surveillance basée conjointement sur l'analyse temporelle et l'analyse fréquentielle des signaux mesurés en tournage pour identifier l’usure de l’outil. Les objectifs principaux de ce travail sont de montrer, d’une part, la sensibilité d'indicateurs scalaires à la variation de l'usure et d’autre part de déterminer plusieurs indicateurs de l’usure à l’image des fréquences caractéristiques, du niveau vibratoire et des changements brusques qui permettent de déceler l’endommagement de l’outil de coupe. Cette dernière étude fréquentielle est basée sur une analyse multirésolution en ondelettes. Les résultats obtenus et présentés dans cet article, montrent l'efficacité de ces approches en tournage.Mots-clés : Usure d’outil- Effort de coupe - Signatures vibratoires - Indicateurs scalaires - Analyse fréquentielle- Analyse multirésolution en ondelettes

Application of the Wavelet Multi-resolution Analysis and Hilbert transform for the prediction of gear tooth defects

In machine defect detection, namely those of gears, the major problem is isolating the defect signature from the measured signal, especially where there is significant background noise or multiple machine components. This article presents a method of gear defect detection based on the combination of Wavelet Multi-resolution Analysis and the Hilbert transform. The pairing of these techniques allows simultaneous filtering and denoising, along with the possibility of detecting transitory phenomena, as well as a demodulation. This paper presents a numerical simulation of the requisite mathematical model followed by its experimental application of acceleration signals measured on defective gears on a laboratory test rig. Signals were collected under various gear operating conditions, including defect size, rotational speed, and frequency bandwidth. The proposed method compares favourably to commonly used analysis tools, with the advantage of enabling defect frequency isolation, thereby allowing detection of even small or combined defects.Deposited by bulk importTS 11.02.1

Parietal fibrinous peritonitis in cattle: A literature review

peer reviewedBackground: Parietal fibrinous peritonitis (PFP) is a complication of laparotomy in cattle, consisting of fluid and fibrin accumulation within a fibrous capsule between the parietal peritoneum and the abdominal muscles. Since scientific information on PFP is scarce, we aim to collect available information to help practitioners in its diagnosis and treatment, and to formulate research perspectives. Methods: PubMed and GoogleScholar databases were scanned using “cattle” or “bovine”, and one of the following keywords: “seroma”, “parietal fibrinous peritonitis”, “retroperitoneal abscess”, or “wound infection”. Results: Although scientific information is often anecdotal, two recent larger studies shed more light on PFP symptoms, diagnosis and treatment. Symptoms vary according to the cavity’s localisation and size, and include anorexia, weight loss and an inflammatory status. Rectal palpation is strongly indicative, but the definitive diagnosis is made by ultrasound. Trueperella pyogenes and Escherichia coli are frequently isolated germs, although it remains unclear whether they are primary or secondary agents. Good survival rates were reported after surgical drainage. Conclusion: Although the diagnosis and treatment seem clear, the exact pathogenesis of PFP should be the focus of ongoing research. This can be achieved by epidemiological data analysis focusing on risk factors like surgery technique, housing and ration