Rolling element bearings are a vital part in many rotating machinery, including vehicles. A defective bearing can be a symptom of other problems in the machinery and is due to a high failure rate. Early detection of bearing defects can therefore help to prevent malfunction which ultimately could lead to a total collapse. The thesis is done in collaboration with Scania that wants a better understanding of how external sensors such as accelerometers, can be used for condition monitoring in their gearboxes. Defective bearings creates vibrations with specific frequencies, known as Bearing Characteristic Frequencies, BCF [23]. A key component in the proposed method is based on identification and extraction of these frequencies from vibration signals from accelerometers mounted near the monitored bearing. Three solutions are proposed for automatic bearing fault detection. Two are based on data-driven classification using a set of machine learning methods called Support Vector Machines and one method using only the computed characteristic frequencies from the considered bearing faults. Two types of features are developed as inputs to the data-driven classifiers. One is based on the extracted amplitudes of the BCF and the other on statistical properties from Intrinsic Mode Functions generated by an improved Empirical Mode Decomposition algorithm. In order to enhance the diagnostic information in the vibration signals two pre-processing steps are proposed. Separation of the bearing signal from masking noise are done with the Cepstral Editing Procedure, which removes discrete frequencies from the raw vibration signal. Enhancement of the bearing signal is achieved by band pass filtering and amplitude demodulation. The frequency band is produced by the band selection algorithms Kurtogram and Autogram. The proposed methods are evaluated on two large public data sets considering bearing fault classification using accelerometer data, and a smaller data set collected from a Scania gearbox. The produced features achieved significant separation on the public and collected data. Manual detection of the induced defect on the outer race on the bearing from the gearbox was achieved. Due to the small amount of training data the automatic solutions were only tested on the public data sets. Isolation performance of correct bearing and fault mode among multiplebearings were investigated. One of the best trade offs achieved was 76.39 % fault detection rate with 8.33 % false alarm rate. Another was 54.86 % fault detection rate with 0 % false alarm rate.

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Wave ocean energy is a source of renewable energy which is gaining interest in the modern world. In contrast to other well-researched renewable energy sources such as wind energy, wave ocean energy is under the development phase. Governments around the world are encouraging the research of harnessing wave energy. As of now, there are different concepts to harness energy from waves. Tribological components are one of the main aspects that need attention in these wave energy converters. The moving components such as bearings can be the life-determining component of the entire device. This thesis provides conceptual solutions to adapt an existing start-stop bearing test rig to the conditions of wave energy converters. The test rig can test different bearing sused in the wave energy converters. The new design intends to provide scaled wave energy conditions. These conditions are mainly influenced by the oscillating movement of the bearings, the complex load condition and the salty environment. Since the testing of bearings in wave energy converters is in the initial stage, modular designs are implemented to test different types of bearings. / Se filen

<p dir="ltr">Rolling element bearings (REBs) are common components in rotating equipment. They are used to carry loads and allow for rotation and misalignments with minimal friction. There exists a wide variety of ball and roller bearings that are suited for a wide variety of applications. All varieties of REBs operate with the same fundamental principles: force transferred from the shaft is applied to the inner race of a bearing, distributed among the rolling elements, and passed on through the outer race to the bearing housing. Load distribution among the rolling elements and the dynamic performance of the bearing is dependent on the bearing’s specifications and operating conditions. Bearing-housing and inner race-shaft fit classifications also control the bearing radial internal clearance (RIC), which eventually affects the bearing performance and load transferred to the housing.</p><p dir="ltr">This thesis experimentally and analytically investigates the load distribution and dynamic performance of rolling elements and investigates roller slip, tilt, and skew in a spherical roller bearing (SRB) under various combinations of loads and speeds. In order to have better insight into the effect of flexible housing and shaft on load distribution and dynamics of REBs, it was experimentally investigated the variation of inner race-shaft and outer race-housing interfaces on load and pressure maps at the bearing-housing interface for four different varieties of rolling element bearing: deep groove ball bearings, angular contact ball bearings, cylindrical roller bearings, and spherical roller bearings. Moreover, an integrated rotor-bearing housing system model developed to examine the behaviors of the rotor, bearing, and housing operating under various conditions.</p><p dir="ltr">In order to gain a deeper understanding of the dynamic behavior of REBs, a full six degree of freedom SRB dynamic model was developed in MSC ADAMS software. C++ based ADAMS/Solver subroutines, called dynamic bearing model (DBM), were developed and incorporated in ADAMS to compute reaction forces and moments in a rolling element bearing. DBM is based on the discrete element method (DEM), which assumes each of the bearing elements (i.e., rolling elements, cage, inner race, and outer race) to be a rigid body with six degrees-of freedom (DOF) in a three-dimensional space. A novel test rig (spherical roller bearing test rig, SRBTR) was also designed and developed to investigate load distribution and roller slip, tilt, and skew in an SRB. The test rig utilized a double-row SRB and was designed to allow for direct visual access to each row using a high-speed camera. The dynamic behavior of the rollers was corroborated with the developed analytical model. The experimental and analytical results indicate that the roller tilt angle increases with axial load, remains constant with speed, and decreases with increasing radial load when the roller is located in the load zone. Furthermore, roller skew in the load zone increases with axial load and shaft speed; however, it decreases with the radial load. The results indicate that when the radial-to-axial load ratio is greater than 4, roller tilt and skew are minimized. Due to roller intermittent slip and roller cage pocket collision in the unload zone, tilt and skew become unpredictable. The magnitude of the tilt and skew in the unload zone is directly related to the roller-race and roller-cage pocket clearances, respectively. Another test rig (pressure mapping test rig, PMTR) was designed to solely investigate how bearing-housing and inner race-shaft interfaces affect the load distribution in REBs. Thin film pressure sensors were utilized and placed around the perimeter of the test bearings inside of a housing to experimentally evaluate the pressure distribution between REBs and a housing under different loads and bearing-shaft and bearing-housing interfaces. Pressure map results were used to evaluate the effect of radial internal clearance on the load distribution of different bearing types. Pressure map results confirmed that the amplitude of load variation reduces with the bearing internal clearance. The thin film sensor system was also used to investigate the circumferential load distribution on the housing.</p><p dir="ltr">Previous ADAMS bearing models have assumed the bearing outer race to be fixed to the ground and the bearing inner race to be attached to a rigid shaft. In order to develop a more realistic and versatile bearing simulation tool, ADAMS bearing models were combined with flexible housings and rotor. To achieve an integrated rotor-bearing housing system model, the ADAMS bearing model was coupled through a set of interface points using component-mode-synthesis (CMS) for the rotor and housing model. The bearing outer races were discretized into multiple nodes to compute the force and deformation at the bearing housing conformal contact as well as to minimize the computational requirements associated with the conformal contact problems. The integrated model was then utilized to investigate the effects of rotor flexibility in the bearing rotor system and the effect of bearing clearance and housing clearance on bearing dynamics. It was demonstrated that the flexibility of the rotor has a significant effect on bearing element motion and dynamics. The results also indicated that depending on the bearing type, the shaft deflection can induce a moment within the bearing that is not readily identifiable from elementary theory. The results showed that the flexible housing undergoes deformations that create ovality in the bearing housing, thus affecting bearing dynamics. The model was also used to investigate bearing performance in a miniature wind turbine main shaft, utilizing a combination of SRB and cylindrical roller bearing (CRB) ADAMS models. Results suggest that the axial-to-radial load ratio should be less than the tangent of the SRB contact angle to avoid premature failure due to rollers sliding in the SRB as well as detrimental parallel misalignment in the CRB.</p>