La boite de vitesses est un des principaux organes d’une automobile et son développement est complexe. De nombreuses contraintes doivent être prises en compte et notamment son comportement acoustique et vibratoire. Cet aspect de la conception est de nos jours assez mal maitrisé et les nuisances acoustiques des boites de vitesses, telle que le bruit de grenaille, sont bien souvent découvertes tardivement. L’objectif de ces travaux était le développement d’un modèle numérique de dynamique des engrenages applicable aux boites de vitesses et permettant de prédire les conditions d’apparition du bruit de grenaille. La modélisation proposée dans cette thèse repose sur une association originale de différentes modélisations et est applicable à la grande majorité des boites de vitesses. Les éléments flexibles tels que les arbres et les carters sont modélisés par la méthode des éléments-finis. Un modèle d’engrenage basé sur le modèle de contact de Kelvin-Voigt est développé. Ce dernier permet la prise en compte des pertes de contact et des chocs sur les flancs avants et arrières. Pour compléter la modélisation, des modèles de pertes mécaniques sont implémentés afin de prendre en compte l’influence des roulements, des paliers lisses, des synchroniseurs et du barbotage des pignons dans l’huile. Le modèle développé, couplé à un indicateur de bruit de grenaille, permet de réaliser des études de sensibilités afin d’identifier les paramètres influents sur le bruit de grenaille mais aussi de comparer les comportements vibratoires de différentes configurations. Pour finir, une campagne d’essais sur une boite de vitesse industrielle est réalisée et des résultats de simulations lui sont confrontés. / The gearbox is an important component of an automobile and its development is complex. Numerous constraints must be taken into account, particularly its noise and vibration behavior. This aspect of the conception is nowadays poorly mastered and the noise pollution of gearboxes, such as the rattle noise, are often discovered late. The aim of this work was the development of a numerical model of gear dynamics adapted to gearboxes’ modelling and allowing to predict the conditions of gear rattle noise appearance. The model proposed in this thesis is based on an original combination of different models and is applicable to the vast majority of gearboxes. Flexible components, such as shafts and housings are modeled by the finite element method. A gear model based on Kelvin-Voigt contact model is developed. It allows to take into account the contact losses and the back side contacts. To complete this model, mechanical loss models are implemented in order to take into account the influence of the bearings, plain bearings, synchronizers and gears’ immersion in oil. This model coupled with a noise indicator allows for sensitivity analyzes to identify influential parameters on the rattle noise but also to compare the dynamic behavior of different configurations. Finally, a test campaign on an industrial gerbox is conducted and simulation results are confronted to measurements.

Vibration monitoring is widely used to determine the condition of various mechanical systems. Traditionally a transducer is attached to the structure under investigation and the vibration signal recorded. This signal is then processed and the required information extracted from the signal. With epicyclic gearboxes this traditional approach is not advisable. This is in part due to the fact that the planet gears rotate internally on a planet carrier. Special techniques are therefore required to extract a viable data signal from the measured vibration signal. These techniques require an additional post-processing step in which a compiled data signal is extracted from the measured data signal. This work investigates the possibility of mounting transducers internally on the rotating planet carrier. Mounting transducers at this location removes the relative motion seen in traditional measurement techniques. An epicyclic gearbox is modified to facilitate the internal mounting of the accelerometers. A number of implementation problems are highlighted and solutions to these problems are discussed. A large portion of the work is dedicated to implementing and qualifying the epicyclic time synchronous averaging technique which is traditionally used to evaluate epicyclic gearboxes. As this technique forms the basis to evaluate the data obtained from internal measurements, it is of fundamental importance that the technique is implemented correctly. It is shown that vibration data can be reliably measured internally, by means of accelerometers mounted on the planet carrier. The internally measured data is compared to data obtained by traditional techniques and shown to be equally adept in detecting deterioration of a planet gear tooth. Simple condition indicators were used to compare the vibration data of the two techniques. It was seen that the data obtained from the internally mounted accelerometers was equally, and in certain cases, slightly more sensitive to planet gear damage. This implies that the technique can be used successfully to evaluate epicyclic gearbox damage. There are a number of practical implementation problems that will limit the use of this technique. As the technology becomes available to transmit measured vibration signals wirelessly, the application of the internal measurement technique will become more viable. A preliminary investigation was also launched into the relationship between a planetary gearbox with a single planet gear and one with multiple planet gears. It is illustrated that vibration data, measured from a gearbox containing a single planet gear, shows an increased sensitivity to planet gear damage. Although a special test rig might be required, the increased sensitivity to damage can provide a method to test planet gears in critical applications such as aircraft gearboxes. Copyright / Dissertation (MEng)--University of Pretoria, 2010. / Mechanical and Aeronautical Engineering / unrestricted

This master´s thesis deals with the acoustic emission of the gearbox housing. It contains a description of the procedure of solving individual numerical approaches and their results. Finally, it compares the influence of design modifications on acoustic emission.

The aim of the diploma thesis is the design of mechanical parts of the rear axle driveline suitable for rebuilding of a given sports car into an electric car. The introductory part briefly explains the physical principles of the drive and contains a brief summary of the current concepts of electric vehicle propulsion. Afterwards, there is a comparison and selection of a suitable concept for a given electric vehicle, determination of the basic vehicle parameters based on the calculation of the longitudinal vehicle dynamics and the gearbox calculation on the basis of which the design is solved. The next part is dedicated to the computational inspection of parts using the finite element method. The final part deals with the placement of the assembly inside the vehicle and the evaluation of the drive mechanism.

This thesis is devoted to the problem of the production of hulls of the gearboxes. The text of this final thesis shows the production technology for single and series production. At the same time, a critical amount of products for a different production options were established.

This diploma thesis concerns the design proposal for a bicycle gearbox powered by human force. The first part summarizes the existing solutions. The second part includes the proposal of the new design, together with the calculation of the strength for selected parts. Attached are the drawings documenting the findings.

This diploma thesis is about machining of exact hole specifications to fit the bearings from the the theoretical overviewof the fiiting. Another purpose is to describe; the overview of machines, the choices in bearings, and the types of gearboxes. Finally, it deals with the different methods of surface finishing, how to produce the holes for the bearings to fit in gearboxes.Finally, it deals with the different methods of surface finishing and how to produce the holes for the bearings to fit in the gearboxes

The aim of these theses was the creation of a single-stage gearbox by additive technology FDM / FFF. By chosen values was made dimension calculation for gears. The 3D model of the gearbox was designed in 3D software Autodesk Inventor. Single parts were produced on an FDM 3D printer by Prusa Research. Manufacturing programs for parts were prepared in PrusaSlicer. These programs were used for producing individuals parts on 3D Printer. Transparent material and printing parameters for the top of the gearbox were chosen by visual test and test of light intensity. The total cost of model production is calculated in the work. The result of these is a completely working model of a single-stage gearbox with a transparent top of the gearbox.

This diploma thesis deals with designing electric vehicle gearbox. Gearbox should serve as virtual replacement for actual transmission of VW ID.3 EV. Designed gearbox has two gears. In the first section there is an extensive search processed of drivetrain and transmission of battery electric vehicles. Next section contains choice of transmission concept and analyses solving of individual structural nodes – gear wheels, band breaks (components that engage individual gears), carriers, shaft, bearing. In the conclusion of diploma thesis, the two-gear planetary transmission is evaluated.

Background: The gearbox and machinery faults prediction are expensive both in terms of repair and loss output in production. These losses or faults may lead to complete machinery or plant breakdown.  Objective: The goal of this study was to apply advanced machine learning techniques to avoid these losses and faults and replace them with predictive maintenance. To identify and predict the faults in industrial machinery using Machine Learning (ML)  and Deep Learning (DL) approaches.  Methods: Our study was based on two types of datasets which includes gearbox and rotatory machinery dataset. These datasets were analyzed to predict the faults using machine learning and deep neural network models. The performance of the model was evaluated for both the datasets with binary and multi-classification problems using the different machine learning models and their statistics. Results: In the case of the gearbox fault dataset with a binary classification problem, we observed random forest and deep neural network models performed equally well, with the highest F1-score and AUC score of around 0.98 and with the least error rate of 7%.  In addition to this, in the case of the multi-classification rotatory machinery fault prediction dataset, the random forest model outperformed the deep neural network model with an AUC score of 0.98.  Conclusions: In conclusion classification efficiency of the Machine Learning (ML) and Deep Neural Network (DNN) model were tested and evaluated. Our results show Random Forest (RF) and Deep Neural Network (DNN) models have better fault prediction ability to identify the different types of rotatory machinery and gearbox faults as compared to the decision tree and AdaBoost.  Keywords: Machine Learning, Deep Learning, Big Data, Predictive Maintenance, Rotatory Machinery Fault Prediction, Gearbox Fault Prediction, Machinery Fault Database, Internet of Things (IoT), Spectra quest machinery fault simulator, Cloud Computing, Industry 4.0