Rolling element bearings are the one of the most widely used machine elements in the industry. The most important criterion in bearing selection is the endurance life. The first attempts on the prediction of the endurance life of rolling elements bearings are done by Lundberg and Palmgren in 1950s (Harris, 1999). Their work adopted as an ANSI, ABMA and ISO standard which is widely used in industry today. The basic assumption of Lundberg-Palmgren formulation is that no matter how small the load applied on rolling element bearing, all material in the stressed volume is subject to fatigue failure. In this study, four main life theories / Weibull, Lundberg-Palmgren, Ioannides-Harris, and Zaretsky on rolling element bearings have been investigated. Three-dimensional finite element models of a bearing&rsquo / s inner ring and rolling element have been prepared. The stress fields within the inner ring and the ball with respect to the applied load are obtained numerically. The fatigue life of the inner ring has been predicted by two methods that are widely used for fatigue analysis / Total Life Analysis (S-N method) and Crack Initiation Analysis (&amp / #56256 / &amp / #56624 / -N method). Obtained results are compared with ISO formulation. As a result of the investigation, S-N and &amp / #56256 / &amp / #56624 / -N methods are determined to give more conservative results than ISO method for higher loads that cause stresses above the fatigue limit of the material. The used methods for bearing life prediction recognize the existence of the fatigue limit stress. Hence as the stresses within an operating bearing do not exceed the limit stress, the bearing can achieve infinite life. It is also observed that load variation has a direct influence on the bearing life. When the load significantly changes from the levels which create stress above the fatigue limit to the levels that result stress is below the fatigue limit, the bearing would have higher endurance life than predicted by ISO method.

Robust fault analysis (FA) including the diagnosis of faults and predicting their level of severity is necessary to optimise maintenance and improve reliability of Aircraft. Early diagnosis of faults that might occur in the supervised process renders it possible to perform important preventative actions. The proposed diagnostic models were validated in two experimental tests. The first test concerned a single localised and generalised roller element bearing fault in a permanent magnet brushless DC (PMBLDC) motor. Rolling element bearing defect is one of the main reasons for breakdown in electrical machines. Vibration and current are analysed under stationary and non-stationary load and speed conditions, for a variety of bearing fault severities, and for both local and global bearing faults. The second test examined the case of an unbalance rotor due to blade faults in a thruster, motor based on a permanent magnet brushed DC (PMBDC) motor. A variety of blade fault conditions were investigated, over a wide range of rotation speeds. The test used both discrete wavelet transform (DWT) to extract the useful features, and then feature reduction techniques to avoid redundant features. This reduces computation requirements and the time taken for classification by the application of an orthogonal fuzzy neighbourhood discriminant analysis (OFNDA) approach. The real time monitoring of motor operating conditions is an advanced technique that presents the real performance of the motor, so that the dynamic recurrent neural network (DRNN) proposed predicts the conditions of components and classifies the different faults under different operating conditions. The results obtained from real time simulation demonstrate the effectiveness and reliability of the proposed methodology in accurately classifying faults and predicting levels of fault severity.

The main purpose of this diploma thesis is to design turbocharger rotor using rolling element bearings. The diploma thesis is compiled from two specialized search parts dealing with turbocharger rotor and rolling element bearing computation, respectively. The application of the particular rotor using the multi body system Adams – View is described in the following chapter. In the last chapter, one can find the comparison between rotor using bearing with steal and hybrid ceramic rolling element. Also, there is compariosn between rolling element bearing and journal bearing. In the maximum rotor speed, the decrease of more than 50 % in power loss, due to usage of rolling element bearing, resulted from this comparison.

Today's industry uses increasingly complex machines, some with extremely demanding performance criteria. Failed machines can lead to economic loss and safety problems due to unexpected production stoppages. Fault diagnosis in the condition monitoring of these machines is crucial for increasing machinery availability and reliability. Fault diagnosis of machinery is often a difficult and daunting task. To be truly effective, the process needs to be automated to reduce the reliance on manual data interpretation. It is the aim of this research to automate this process using data from machinery vibrations. This thesis focuses on the design, development, and application of an automatic diagnosis procedure for rolling element bearing faults. Rolling element bearings are representative elements in most industrial rotating machinery. Besides, these elements can also be tested economically in the laboratory using relatively simple test rigs. Novel modern signal processing methods were applied to vibration signals collected from rolling element tests to destruction. These included three advanced timefrequency signal processing techniques, best basis Discrete Wavelet Packet Analysis (DWPA), Matching Pursuit (MP), and Basis Pursuit (BP). This research presents the first application of the Basis Pursuit to successfully diagnosing rolling element faults. Meanwhile, Best basis DWPA and Matching Pursuit were also benchmarked with the Basis Pursuit, and further extended using some novel ideas particularly on the extraction of defect related features. The DWPA was researched in two aspects: i) selecting a suitable wavelet, and ii) choosing a best basis. To choose the most appropriate wavelet function and decomposition tree of best basis in bearing fault diagnostics, several different wavelets and decomposition trees for best basis determination were applied and comparisons made. The Matching Pursuit and Basis Pursuit techniques were effected by choosing a powerful wavelet packet dictionary. These algorithms were also studied in their ability to extract precise features as well as their speed in achieving a result. The advantage and disadvantage of these techniques for feature extraction of bearing faults were further evaluated. An additional contribution of this thesis is the automation of fault diagnosis by using Artificial Neural Networks (ANNs). Most of work presented in the current literature has been concerned with the use of a standard pre-processing technique - the spectrum. This research employed additional pre-processing techniques such as the spectrogram and DWPA based Kurtosis, as well as the MP and BP features that were subsequently incorporated into ANN classifiers. Discrete Wavelet Packets and Spectra, were derived to extract features by calculating RMS (root mean square), Crest Factor, Variance, Skewness, Kurtosis, and Matched Filter. Certain spikes in Matching Pursuit analysis and Basis Pursuit analysis were also used as features. These various alternative methods of pre-processing for feature extraction were tested, and evaluated with the criteria of the classification performance of Neural Networks. Numerous experimental tests were conducted to simulate the real world environment. The data were obtained from a variety of bearings with a series of fault severities. The mechanism of bearing fault development was analysed and further modelled to evaluate the performance of this research methodology. The results of the researched methodology are presented, discussed, and evaluated in the results and discussion chapter of this thesis. The Basis Pursuit technique proved to be effective in diagnostic tasks. The applied Neural Network classifiers were designed as multi layer Feed Forward Neural Networks. Using these Neural Networks, automatic diagnosis methods based on spectrum analysis, DWPA, Matching Pursuit, and Basis Pursuit proved to be effective in diagnosing different conditions such as normal bearings, bearings with inner race and outer race faults, and rolling element faults, with high accuracy. Future research topics are proposed in the final chapter of the thesis to provide perspectives and suggestions for advancing research into fault diagnosis and condition monitoring.

The presented diploma thesis deals with the design of a test system for rolling bearings, which allows the change of the lubrication parameters (e.g. changing of the relubrica-tion interval). In the document, the reader first learns about the meaning of lubrication of rolling bearings, the possibilities of lubricant supply to the bearing (specifically for the supply of grease) and the possibilities of dosing control. Subsequently in the document is described the present state of experimental stations for testing rolling bearings, which is available at the Institute of Machine and Industrial Design. The end of the part about current state of knowledge is also mentioned the possibility of speeding up fatigue tests. In the next part, the author describes his own solution. The result is the design of an experimental station (for option to relubricate with grease), the creation of a lubrication control platform and the creation of a basic program. Part of the work is also verification experiments and drawing documentation.

The demand for reliable condition monitoring systems on rotating machinery for power generation is continuously increasing due to a wider use of wind power as an energy source, which requires expertise in the diagnostics of these systems. An alternative to the limited availability of diagnostics and maintenance experts in the wind energy sector is to use unsupervised machine learning algorithms as a support tool for condition monitoring. The way condition monitoring systems can employ unsupervised machine learning algorithms consists on prioritizing the assets to monitor via the number of anomalies detected in the vibration signals of the rolling element bearings. Previous work has focused on the detection of anomalies using features taken directly from the time or frequency domain of the vibration signals to determine if a machine has a fault. In this work, I detect outliers using features derived from encoded vibration signals via sparse coding with dictionary learning. I investigate multiple outlier detection algorithms and evaluate their performance using different features taken from the sparse representation. I show that it is possible to detect an abnormal behavior on a bearing earlier than reported fault dates using typical condition monitoring systems.

Avec l’apparition de moteur électrique dans le secteur automobile, les réducteurs mécaniques fonctionnent à des vitesses de rotation de plus en plus élevées. Pour ce type de réducteur, les pertes de puissance au niveau des paliers à roulements peuvent être prédominantes pour des vitesses de rotation élevées. Ces pertes sont fortement dépendantes du comportement thermique du palier à roulement. D’où l’intérêt de développer des outils numériques permettant d’estimer les puissances générées au sein d’un palier à roulement. Cette estimation permettra en phase de pré-étude de développer un dispositif de refroidissement adapté afin d’éviter tout risque de dégradation du palier à roulement. Cette thèse présente une nouvelle approche permettant d’étudier le comportement thermomécanique de palier à roulement. Cette approche intermédiaire requiert un minimum de paramètres d’entrée (géométrie externe du palier à roulement et condition de fonctionnement). Elle utilise la méthode dite « des réseaux thermiques » pour obtenir une interconnexion entre les pertes de puissance et le comportement thermique du palier à roulement. Enfin cette approche permet de calculer la puissance dissipée au sein d’un roulement et les températures des bagues et du lubrifiant principalement pour une application hautes vitesses. Cette approche est développée pour des roulements à billes à gorge profonde et contact oblique. Des valeurs expérimentales sont nécessaires pour valider cette nouvelle approche. C’est pourquoi, un nouveau banc d’essai modulaire dédié à l’étude du comportement thermomécanique de palier à roulement a été développé. Sur ce nouveau moyen d’essai, une grande variété de paliers à roulements peut être testée pour différentes conditions de fonctionnement. Pour les premiers essais, un roulement à billes à gorge profonde lubrifié par injection est testé pour un fonctionnement hautes vitesses (produit (n×D_m) supérieur au million). / Rolling Element Bearing (REB) is an essential component in mechanical transmission to reduce friction between rotating parts. Now, with the development of electrical motor in mechanical industry, REBs may work at very high rotation speed. It leads to an increase of REB power losses and temperatures. Theses power losses are strongly coupled with the REB thermal behaviour. The oil temperature has a significant impact on the kinematic viscosity which in turn affects the REB power losses. Based on thermal network approach, an intermediate model is developed in this study. This new model allows obtaining lumped information (temperature of rings) with a minimum of input data (REB external geometry and operating condition only) and by using global power loss models. This intermediate model is developed for angular contact ball bearing and deep groove ball bearing under oil jet lubrication for high speed application. Experimental data are required to validate this new approach. That why, a modular test rig is designed to obtain information on the REB thermomechanical behaviour. The new test rig developed in this study is dedicated to a wide range of REB dimensions and for different operating conditions. For the first test, a deep groove ball bearing under oil jet lubrication is studied for high speed application ((N.dm) product is higher than one million.)

Malgré les innovations technologiques, les éoliennes restent sujettes à des défaillances prématurées de composants mécaniques imposants, ayant des conséquences considérables sur le coût de l’énergie. Parmi les défaillances majeures au sein des roulements d’éoliennes, un mode de fatigue de contact atypique se caractérise par de vastes réseaux de fissures ramifiées avec des phases microstructurales adjacentes d’apparence blanche à l’origine de la dénomination White Etching Cracks (WEC). Contrairement à la fatigue de contact classique, les WEC apparaissent pour un nombre de cycles et des charges relativement faibles, menant à une défaillance du composant imprévisible selon les modèles de durée de vie actuels. Les WEC ont été observés chez tous les roulementiers, dans diverses applications industrielles et pour différents types de roulements, éléments, lubrifiants, aciers et traitements thermiques. Ce manque de dénominateur commun rend les WEC difficilement reproductibles sur bancs d’essai sans chargement artificiel en hydrogène de l’acier. Ainsi, pour le moment, la formation des WEC ne fait pas l’objet d’un consensus. Une analyse des reproductions de WEC a été menée afin d’en comprendre les mécanismes tribologiques. Des protocoles expérimentaux ont été établis pour révéler les WEC, souvent situés à des positions inhabituelles par rapport au contact. Leur reproduction sur des roulements standards, chargés ou non en hydrogène, a permis de démontrer que le chargement artificiel en hydrogène, jusque-là couramment employé pour étudier la défaillance, reproduit des faciès identiques mais semble modifier l’initiation des WEC. Ainsi, des reproductions de WEC sans chargement en hydrogène et dans des configurations différentes ont été comparées afin d’appréhender les phénomènes tribologiques à l’origine des WEC. Les résultats suggèrent que l’initiation est principalement déclenchée par des phénomènes de surfaces avec l’absorption tribochimique d’hydrogène au niveau des surfaces métalliques fraîches sur la piste de roulement ou au niveau des flancs de microfissures superficielles. La propagation est ensuite assistée chimiquement par l’hydrogène concentré en pointe de fissure. Un arbre des causes étendu révèle que les WEC peuvent être associées à de multiples combinaisons de conditions opératoires qui semblent cependant conduire à des paramètres tribologiques similaires à l’échelle du contact avec, notamment, des cinématiques de glissement, des formulations de lubrifiants spécifiques et des paramètres tribochimiques catalyseurs comme la présence d’eau et/ou d’électricité. Une vaste campagne d’essai a alors été conduite sur un tribomètre bi-disques afin de simuler la fatigue de contact. Les résultats confirment que les facteurs influents identifiés ne sont pas pour autant auto-suffisants. La formation des WEC repose sur un équilibre instable entre aspects matériaux, mécaniques et tribochimiques, à maîtriser pour concevoir des solutions industrielles. / Despite constant expansion and engineering progress, wind turbines still present unexpected failures of heavy duty mechanical components drastically affecting the cost of energy. Among the most prevalent tribological failures in wind turbine rolling element bearings, a peculiar rolling contact fatigue mode has been associated to broad subsurface three-dimensional branching crack networks bordered by white etching microstructure, and thus named White Etching Cracks (WEC). Compared to conventional microstructural alterations, WECs tend to develop at moderate loads and cycles eventually leading to premature failures that remain unpredictable using fatigue life estimations. Far from being generic to specific manufacturers, WECs occur in various industrial applications, for various bearing types, components, lubricants, steels grades and heat treatments. As WEC occurrences present no common evident denominator, they remain delicate to reproduce on laboratory test rigs without prior artificial hydrogen charging, so that no consensus on WEC formation mechanisms have been confirmed yet. In this study, a thorough tribological analysis of WEC formation mechanisms has been led. Expertise protocols have been established to best reveal and observe WECs that commonly develop at unconventional locations versus the contact area. First analysis of WEC reproductions on standard rolling element bearings either hydrogen precharged or kept neutral have signified that artificial hydrogen charging, commonly employed to apprehend the failure mode, results in similar WEC morphologies but tends to alter WEC tribological initiation. In consequence, WEC reproductions in remarkably different configurations but without hydrogen charging have been compared in order to propose a better understanding of WEC surface-affected formation mechanisms: first, initiation via tribochemical hydrogen permeation at nascent steel surfaces formed either directly at the raceway or at surface microcracks flanks and second, propagation by local hydrogen embrittlement at crack tips function of the stress state. An extensive root cause analysis have then been led suggesting that WEC may be associated to various combinations of macroscopic operating conditions that often interact and come down to similar tribological parameters including high sliding energy thresholds, specific lubricant formulations and tribochemical drivers such as water contamination and/or electrical potentials. Further investigations on a minimalist twin-disc fatigue tribometer have provided additional evidence that WEC influent drivers are non-self-sufficient, supporting that WEC formation mechanisms rely on a subtle equilibrium between tribo-material, tribo-mechanical and tribo-chemical drivers that all should be mastered to design efficient and durable countermeasures.

No description available.

This Master's thesis is part of the Hydrogen Embrittlement in Rolling element bearings project (HERo) initiated at Luleå University of Technology (LTU), with the primary objective of determining critical hydrogen concentrations in bearing steel for rolling element bearings. The specific aim of this Master's thesis is to design a test rig that enables the investigation of the effects of hydrogen embrittlement on rolling element bearings under load. The design process focused on ease of manufacture and assembly. The developed test rig includes an electric motor, a pneumatic load application mechanism, and an electrochemical cell. Using the leverage principle, a thrust roller bearing is loaded vertically, while it is driven by an electric motor that is connected to the bearing with a tyre coupling. The electrochemical cell, which consists of a reference electrode, counter electrode, and the test bearing as the working electrode, is used to charge the test bearing with hydrogen. The cell was designed to be easily accessible between tests to facilitate the change of thrust roller bearings. The test bench enables the analysis of rolling element bearings that are exposed to simultaneous hydrogen embrittlement and realistic operating conditions. / Detta examensarbete är en del av Hydrogen Embrittlement in Rolling element bearings-projektet (HERo) som pågår vid Luleå tekniska universitet (LTU), med huvudmålet att bestämma de kritiska vätekoncentrationerna i lagerstål för rullningslager. Det specifika målet med detta examensarbete är att konstruera en testrigg för att direkt undersöka effekten av väteförsprödning av lager i en simulerad verklig tillämpning. Designprocessen fokuserade på enkel tillverkning och montering.  Den utvecklade testriggen inkluderar en elmotor, en pneumatisk lastpåläggnings-mekanism och en elektrokemisk cell. Med hjälp av hävstångsprincipen belastas ett axiellt rullager vertikalt, medan det drivs av en elmotor via en däckkoppling. Den elektrokemiska cellen, som består av en referenselektrod, motelektrod och testlagret som arbetselektrod, används för att införa väte i lagret. Cellen har konstruerats på ett sätt som underlättar byte av testlager mellan testerna.  Testriggen skapar därmed möjligheten att analysera rullningslager som utsätts för väteförsprödning under realistiska driftförhållanden. / Diese Masterarbeit ist Teil des Hydrogen Embrittlement in Rolling element bearings-Projekts (HERo), das an der Technischen Universität Luleå (LTU) initiiert wurde, mit dem primären Ziel, kritische Wasserstoffkonzentrationen für Lageranwendungen zu bestimmen. Das spezifische Ziel dieser Masterarbeit ist es, einen Prüfstand zu konstruieren, um die Auswirkungen von Wasserstoffversprödung auf Rollenlager im Belastungszustand zu untersuchen. Der Schwerpunkt des Designprozesses lag darauf, eine einfache Fertigung und Montage des Prüfstandes zu gewährleisten.  Der entwickelte Prüfstand umfasst einen Motor, einen Mechanismus zur Lastaufbringung und eine elektrochemische Zelle. Mithilfe des Hebelgesetzes wird das Testlager vertikal belastet, während es mithilfe eines Elektromotors und einer Reifenkupplung angetrieben wird. Die elektrochemische Zelle, bestehend aus Referenzelektrode, Gegenelektrode, und dem Testlager als Arbeitselektrode, dient dazu, Wasserstoff in das Testlager einzubringen. In ihrem Design wurde darauf geachtet, dass sie zwischen den Tests leicht zugänglich ist, um den Austausch der Testproben zu erleichtern. Der Prüfstand ermöglicht somit die Analyse von Rollenlagern, die sowohl Wasserstoffversprödung als auch realistischen Betriebsbedingungen ausgesetzt sind.