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Partager le résultat de cette recherche Interroger des sources externesContribution à l'optimisation de la maintenance conditionnelle par l'analyse vibratoire / Rachid Chaib
Titre : Contribution à l'optimisation de la maintenance conditionnelle par l'analyse vibratoire Type de document : texte imprimé Auteurs : Rachid Chaib ; Univ. de Constantine, Éditeur scientifique ; I. Verzea, Directeur de thèse Année de publication : 2006 Importance : 111 f. Note générale : 01 Disponible à la salle de recherche 02 Disponibles au magazin de la B.U.C. 01 CD Langues : Français (fre) Catégories : Français - Anglais
Génie MécaniqueTags : Analyse vibratoire Maitenance conditionnelle Index. décimale : 620 Génie Mécanique En ligne : ../theses/gmecanique/CHA4521.pdf Permalink : index.php?lvl=notice_display&id=889 Contribution à l'optimisation de la maintenance conditionnelle par l'analyse vibratoire [texte imprimé] / Rachid Chaib ; Univ. de Constantine, Éditeur scientifique ; I. Verzea, Directeur de thèse . - 2006 . - 111 f.
01 Disponible à la salle de recherche 02 Disponibles au magazin de la B.U.C. 01 CD
Langues : Français (fre)
Catégories : Français - Anglais
Génie MécaniqueTags : Analyse vibratoire Maitenance conditionnelle Index. décimale : 620 Génie Mécanique En ligne : ../theses/gmecanique/CHA4521.pdf Permalink : index.php?lvl=notice_display&id=889 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité CHA/4521 CHA/4521 Thèse Bibliothèque principale Thèses Disponible
Titre : Diagnostic de l'état des machines tournantes par l'analyse vibratoire Type de document : texte imprimé Auteurs : Soumia Teyar ; Univ. de Constantine, Éditeur scientifique ; S. Meziani, Directeur de thèse Année de publication : 2003 Importance : 95 f. Note générale : 1 Disponible à la salle de recherche
2 Disponibles au magasin de la bibliothèque centraleLangues : Français (fre) Catégories : Français - Anglais
Génie MécaniqueTags : Diagnostic Analyse spectrale Maintenance conditionnelle Analyse vibratoire Machine tournante Index. décimale : 620 Génie Mécanique Permalink : index.php?lvl=notice_display&id=741 Diagnostic de l'état des machines tournantes par l'analyse vibratoire [texte imprimé] / Soumia Teyar ; Univ. de Constantine, Éditeur scientifique ; S. Meziani, Directeur de thèse . - 2003 . - 95 f.
1 Disponible à la salle de recherche
2 Disponibles au magasin de la bibliothèque centrale
Langues : Français (fre)
Catégories : Français - Anglais
Génie MécaniqueTags : Diagnostic Analyse spectrale Maintenance conditionnelle Analyse vibratoire Machine tournante Index. décimale : 620 Génie Mécanique Permalink : index.php?lvl=notice_display&id=741 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité TEY/3866 TEY/3866 Thèse Bibliothèque principale Thèses Disponible 
Titre : Contribution a l'etude des processus d'usure developpes a l'interface des contacts glissants sans passage du courant electrique des machines tournantes Type de document : texte imprimé Auteurs : Noureddine Menasri, Auteur ; Ali Bouchoucha, Directeur de thèse Editeur : constantine [Algérie] : Université Constantine 1 Année de publication : 2014 Importance : 177 f. Format : 30 cm. Note générale : 2 copies imprimées disponibles Langues : Français (fre) Catégories : Français - Anglais
Génie MécaniqueTags : wear the third body bearing gear diagnosis vibration analysis neural networks artificial multilayer usure troisième corps roulement engrenage diagnostic analyse vibratoire réseaux de neurones artificiels multicouches الارتداء الجسم الثالث دحرجة تعشیق التشخیص التحلیل الاھتزازي والشبكات العصبیة اصطناعیة متعددة الطبقات Index. décimale : 620 Génie Mécanique Résumé : Rotating machines play a strategic role in a manufacturing process; it is the case of a cement mill. These machines are made of fragile organs (bearings and gears, etc.) subjected to mechanical stress and harsh industrial environments. There are multiple causes of deterioration of a machine element: normal wear and tear, overload (or under load), poor lubrication, mounting problems, etc… Depending on the extent of degradation, the surfaces in contact present spalling a more or less important.
In general, the wear can be seen as associating failure mechanisms (shear joints, fatigue ...) to interactive phenomena such as thermal effects, volume phenomena (plastic deformation, phase change, diffusion) and naturally surface effects (reaction, adsorption, segregation ...).
In this work the one hand, a study of the characterization of the bearing wear (QJ1244N2MA and SKF 22248 CC / N1W33C3) of the gear unit DMGH 25.4 of a horizontal cement mill was made.
On the other hand, the wear can be seen as a loss of functionality of a system, which affects the image of the components of the vibratory system. Indeed, this change of image vibration will be used as an indicator of defects that will make a diagnosis of an industrial system.
However, many currently available techniques require considerable expertise for successful implementation: it requires new techniques that allow relatively unskilled operators to make reliable decisions without knowing the mechanism of the system and analyze the data. The artificial neural networks (ANN) are suitable for this kind of problem.
It is within this context that our investigations. On the one hand a first study is dedicated to an overview of more detailed knowledge about the wear and tools to understand this phenomenon,especially the concept of third body as the medium at the interface between two bodies in contact, in which wear can be considered as a complex competition between the phenomena of detachment of particles of the contact surfaces and final ejection of these particles out of contact.
On the other hand, a diagnostic approach to implementing multilayer artificial neural networks from measurements performed on a horizontal gear DMGH 25.4.
To study the performance of neural networks vis-a-vis the problems of system diagnostic gear and bearings, cases of failures have been minimized, two types of defects are considered: wear the ring and outside QJ1244 breaking of a tooth of the intermediate gear.Diplôme : Doctorat en sciences En ligne : ../theses/gmecanique/MEN6454.pdf Format de la ressource électronique : Permalink : index.php?lvl=notice_display&id=9490 Contribution a l'etude des processus d'usure developpes a l'interface des contacts glissants sans passage du courant electrique des machines tournantes [texte imprimé] / Noureddine Menasri, Auteur ; Ali Bouchoucha, Directeur de thèse . - constantine [Algérie] : Université Constantine 1, 2014 . - 177 f. ; 30 cm.
2 copies imprimées disponibles
Langues : Français (fre)
Catégories : Français - Anglais
Génie MécaniqueTags : wear the third body bearing gear diagnosis vibration analysis neural networks artificial multilayer usure troisième corps roulement engrenage diagnostic analyse vibratoire réseaux de neurones artificiels multicouches الارتداء الجسم الثالث دحرجة تعشیق التشخیص التحلیل الاھتزازي والشبكات العصبیة اصطناعیة متعددة الطبقات Index. décimale : 620 Génie Mécanique Résumé : Rotating machines play a strategic role in a manufacturing process; it is the case of a cement mill. These machines are made of fragile organs (bearings and gears, etc.) subjected to mechanical stress and harsh industrial environments. There are multiple causes of deterioration of a machine element: normal wear and tear, overload (or under load), poor lubrication, mounting problems, etc… Depending on the extent of degradation, the surfaces in contact present spalling a more or less important.
In general, the wear can be seen as associating failure mechanisms (shear joints, fatigue ...) to interactive phenomena such as thermal effects, volume phenomena (plastic deformation, phase change, diffusion) and naturally surface effects (reaction, adsorption, segregation ...).
In this work the one hand, a study of the characterization of the bearing wear (QJ1244N2MA and SKF 22248 CC / N1W33C3) of the gear unit DMGH 25.4 of a horizontal cement mill was made.
On the other hand, the wear can be seen as a loss of functionality of a system, which affects the image of the components of the vibratory system. Indeed, this change of image vibration will be used as an indicator of defects that will make a diagnosis of an industrial system.
However, many currently available techniques require considerable expertise for successful implementation: it requires new techniques that allow relatively unskilled operators to make reliable decisions without knowing the mechanism of the system and analyze the data. The artificial neural networks (ANN) are suitable for this kind of problem.
It is within this context that our investigations. On the one hand a first study is dedicated to an overview of more detailed knowledge about the wear and tools to understand this phenomenon,especially the concept of third body as the medium at the interface between two bodies in contact, in which wear can be considered as a complex competition between the phenomena of detachment of particles of the contact surfaces and final ejection of these particles out of contact.
On the other hand, a diagnostic approach to implementing multilayer artificial neural networks from measurements performed on a horizontal gear DMGH 25.4.
To study the performance of neural networks vis-a-vis the problems of system diagnostic gear and bearings, cases of failures have been minimized, two types of defects are considered: wear the ring and outside QJ1244 breaking of a tooth of the intermediate gear.Diplôme : Doctorat en sciences En ligne : ../theses/gmecanique/MEN6454.pdf Format de la ressource électronique : Permalink : index.php?lvl=notice_display&id=9490 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MEN/6454 MEN/6454 Thèse Bibliothèque principale Thèses Disponible Documents numériques
texte intégraleAdobe Acrobat PDF
Titre : Développement d’un outil de pronostic pour la maintenance des systèmes mécaniques. Type de document : texte imprimé Auteurs : Younes Debbah, Auteur ; Abdelhakim Cherfia, Directeur de thèse Editeur : جامعة الإخوة منتوري قسنطينة Année de publication : 2018 Importance : 134 f. Format : 30 cm. Note générale : 2 copies imprimées disponibles
Langues : Français (fre) Catégories : Français - Anglais
Génie MécaniqueTags : Pronostic diagnostic prédiction intelligence artificielle analyse vibratoire systèmes
experts réseaux de neurones Prognosis diagnosis prediction artificial intelligence vibration analysis expert
systems neural networks التنبؤ التشخيص الذكاء الاصطناعي تحليل الاهتزاز النظم الخبيرة الشبكات العصبيةIndex. décimale : 620 Génie Mécanique Résumé : Maintenance is becoming increasingly important in companies and tends to evolve for reactivity and cost needs. A particular evolution concerns the way to apprehend the phenomena of failure: little by little the industrialists tend, not only to anticipate them by the recourse to preventive actions, but in addition to do it in the most just possible way with a goal reducing costs and risks. This evolution has given a growing share to the prognosis process.
The activity of fault prognosis is today considered as a key process in industrial maintenance strategies. However, in practice, prognostic tools are still rare. Today's stabilized approaches rely on a history of significant incidents to be representative of potentially predictable events The purpose of this thesis is to propose a tool to predict the degradation of equipment without prior knowledge of its behavior, and to generate prognostic indicators to optimize maintenance strategies. Various techniques, of vibratory signal processing, have been explored
and tested, on a test bench designed and realized as part of the research axes of this work. Two techniques of artificial intelligence have been exploited in the diagnosis and prognosis of defects in rotating machines, where indicator selection techniques have been explored.
The combination of vibration signal processing techniques and artificial intelligence by neural networks has made it possible to provide an efficient prognostic tool and to quantify the relevance of the sources of information used and proposed.
Diplôme : Doctorat En ligne : ../theses/gmecanique/DEB7262.pdf Format de la ressource électronique : Permalink : index.php?lvl=notice_display&id=10859 Développement d’un outil de pronostic pour la maintenance des systèmes mécaniques. [texte imprimé] / Younes Debbah, Auteur ; Abdelhakim Cherfia, Directeur de thèse . - جامعة الإخوة منتوري قسنطينة, 2018 . - 134 f. ; 30 cm.
2 copies imprimées disponibles
Langues : Français (fre)
Catégories : Français - Anglais
Génie MécaniqueTags : Pronostic diagnostic prédiction intelligence artificielle analyse vibratoire systèmes
experts réseaux de neurones Prognosis diagnosis prediction artificial intelligence vibration analysis expert
systems neural networks التنبؤ التشخيص الذكاء الاصطناعي تحليل الاهتزاز النظم الخبيرة الشبكات العصبيةIndex. décimale : 620 Génie Mécanique Résumé : Maintenance is becoming increasingly important in companies and tends to evolve for reactivity and cost needs. A particular evolution concerns the way to apprehend the phenomena of failure: little by little the industrialists tend, not only to anticipate them by the recourse to preventive actions, but in addition to do it in the most just possible way with a goal reducing costs and risks. This evolution has given a growing share to the prognosis process.
The activity of fault prognosis is today considered as a key process in industrial maintenance strategies. However, in practice, prognostic tools are still rare. Today's stabilized approaches rely on a history of significant incidents to be representative of potentially predictable events The purpose of this thesis is to propose a tool to predict the degradation of equipment without prior knowledge of its behavior, and to generate prognostic indicators to optimize maintenance strategies. Various techniques, of vibratory signal processing, have been explored
and tested, on a test bench designed and realized as part of the research axes of this work. Two techniques of artificial intelligence have been exploited in the diagnosis and prognosis of defects in rotating machines, where indicator selection techniques have been explored.
The combination of vibration signal processing techniques and artificial intelligence by neural networks has made it possible to provide an efficient prognostic tool and to quantify the relevance of the sources of information used and proposed.
Diplôme : Doctorat En ligne : ../theses/gmecanique/DEB7262.pdf Format de la ressource électronique : Permalink : index.php?lvl=notice_display&id=10859 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité DEB/7262 DEB/7262 Thèse Bibliothèque principale Thèses Disponible
