Simulation of vibrations produced by localized faults in rolling elements of bearings in gearboxes

A combined gear/bearing model has been made to study the interaction between gears and bearings in the presence of faults. The thirty-four degree-of-freedom model of the University of New South Wales (UNSW) gearbox test rig is a lumped mass parameter model, which has the capacity to model different fault types (localized inner/outer race faults and extended faults). This is in addition to its original capacity for modelling spalls and cracks in the gears. The gear/bearing model takes into consideration the slippage in the bearings, the Hertzian contact and the nonlinearity of the bearing stiffness (time variant). Results have earlier been published for simulated local faults in the inner and outer races of the bearings as well as for an extended inner race fault. For a complete modelling of localized faults, the simulation model has now been updated to enable simulating faults in the rolling elements. The modeling of the faults in the rolling elements takes into consideration the difference in race curvature and represents a new contribution to the development of the model. The agreement between the processed simulated and measured signals shows the robustness of the developed model and its suitability for testing new diagnostic and prognostic algorithms

Establishing relative weights for contractor prequalification criteria in a pre-qualification evaluation model

Pre-qualification criteria is a screening methodology to select contractors. Each contractor attribute has its own importance in relation to the others. It is an essential process that the relative importance'weights' of each selection criteria be identified. Several methodologies are used to identify such weights. A Delphic technique together with Analytical Hierarchy Process (AHP) utilizing pair-wise analysis was used to establish such weights through a structured questionnaire. The established weights will then be used to develop a contractor's pre-qualification model using a hybrid technique by combining a Neural Network and a Genetic Algorithm

Computational Fluid Dynamic Analysis of a Vibrating Turbine Blade

This study presents the numerical fluid-structure interaction (FSI) modelling of a vibrating turbine blade using the commercial software ANSYS-12.1. The study has two major aims: (i) discussion of the current state of the art of modelling FSI in gas turbine engines and (ii) development of a “tuned” one-way FSI model of a vibrating turbine blade to investigate the correlation between the pressure at the turbine casing surface and the vibrating blade motion. Firstly, the feasibility of the complete FSI coupled two-way, three-dimensional modelling of a turbine blade undergoing vibration using current commercial software is discussed. Various modelling simplifications, which reduce the full coupling between the fluid and structural domains, are then presented. The one-way FSI model of the vibrating turbine blade is introduced, which has the computational efficiency of a moving boundary CFD model. This one-way FSI model includes the corrected motion of the vibrating turbine blade under given engine flow conditions. This one-way FSI model is used to interrogate the pressure around a vibrating gas turbine blade. The results obtained show that the pressure distribution at the casing surface does not differ significantly, in its general form, from the pressure at the vibrating rotor blade tip

Planetary bearing defect detection in a commercial helicopter main gearbox with vibration and acoustic emission

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Helicopter gearboxes significantly differ from other transmission types and exhibit unique behaviors that reduce the effectiveness of traditional fault diagnostics methods. In addition, due to lack of redundancy, helicopter transmission failure can lead to catastrophic accidents. Bearing faults in helicopter gearboxes are difficult to discriminate due to the low signal to noise ratio (SNR) in the presence of gear vibration. In addition, the vibration response from the planet gear bearings must be transmitted via a time-varying path through the ring gear to externally mounted accelerometers, which cause yet further bearing vibration signal suppression. This research programme has resulted in the successful proof of concept of a broadband wireless transmission sensor that incorporates power scavenging whilst operating within a helicopter gearbox. In addition, this paper investigates the application of signal separation techniques in detection of bearing faults within the epicyclic module of a large helicopter (CS-29) main gearbox using vibration and Acoustic Emissions (AE). It compares their effectiveness for various operating conditions. Three signal processing techniques including an adaptive filter, spectral kurtosis and envelope analysis, were combined for this investigation. In addition, this research discusses the feasibility of using AE for helicopter gearbox monitoring

Bearing signal separation enhancement with application to helicopter transmission system

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Bearing vibration signal separation is essential for fault detection of gearboxes, especially where the vibration is nonstationary, susceptible to background noise, and subjected to an arduous transmission path from the source to the receiver. This paper presents a methodology for improving fault detection via a series of vibration signal processing techniques, including signal separation, synchronous averaging (SA), spectral kurtosis (SK), and envelope analysis. These techniques have been tested on experimentally obtained vibration data acquired from the transmission system of a CS-29 Category A helicopter gearbox operating under different bearing damage conditions. Results showed successful enhancement of bearing fault detection on the second planetary stage of the gearbo

Fault Detection Enhancement in Rolling Element Bearings Using the Minimum Entropy Deconvolution

Minimum Entropy Deconvolution (MED) has been recently introduced to the machine condition mon- itoring field to enhance fault detection in rolling element bearings and gears. MED proved to be an excellent aid to the extraction of these impulses and diagnosing their origin, i.e. the defective component of the bearing. In this paper, MED is revisited and re-introduced with further insights into its application to fault detection and diagnosis in rolling element bearings. The MED parameter selection as well as its combination with pre-whitening is discussed. Two main cases are presented to illustrate the benefits of the MED technique. The first one was taken from a fan bladed test rig. The second case was taken from a wind turbine with an inner race fault. The usage of the MED technique has shown a strong enhancement for both fault detection and diagnosis. The paper contributes to the knowledge of fault detection of rolling element bearings through providing an insight into the usage of MED in rolling element bearings diag- nostic. This provides a guide for the user to select optimum parameters for the MED filter and illustrates these on new interesting cases both from a lab environment and an actual case

Poprawa wykrywania uszkodzeń łożysk tocznych w turbinach wiatrowych przy użyciu metody minimum entropy deconvolution

Minimum Entropy Deconvolution (MED) has been recently introduced to the machine condition monitoring field to enhance fault detection in rolling element bearings and gears. MED proved to be an excellent aid to the extraction of these impulses and diagnosing their origin, i.e. the defective component of the bearing. In this paper, MED was applied for fault detection and diagnosis in rolling element bearings in wind turbines. MED parameter selection as well as its combination with pre-whitening is discussed. Two main cases are presented to illustrate the benefits of the MED technique. The first was taken from a fan bladed test rig. The second case was taken from a wind turbine with an inner race fault. The usage of the MED technique has shown a strong enhancement for both fault detection and diagnosis. The paper contributes to the knowledge of fault detection of rolling elements bearings through providing an insight into the usage of MED in rolling element bearings diagnostic by providing a guide for the user to select optimum parameters for the MED filter and illustrating these on new interesting cases both from a lab environment and an actual case.Metoda Minimum Etropy Deconvolution (MED) została niedawno wprowadzona do diagnostyki w celu poprawy wykrywania uszkodzeń łożysk tocznych i przekładni. MED okazała się bardzo pomocna w ekstrakcji impulsów pochodzących od tych uszkodzeń i określania miejsca ich pochodzenia (np. uszkodzonego elementu łożyska). W niniejszym artykule MED zastosowano do wykrywania uszkodzeń łożysk tocznych w turbinach wiatrowych. W artykule opisano zagadnienie selekcji parametrów metody MED oraz metody "wybielania sygnału" (ang. pre-whitening). Korzyści płynące z zastosowania metody przedstawiono na dwóch przypadkach. Pierwszym jest stanowisko laboratoryjne, a drugim - turbina wiatrowa z uszkodzoną bieżnią wewnętrzną łożyska generatora. Zastosowanie metody MED pozwoliło na znaczącą poprawę zarówno wykrycia, jak i lokalizacji uszkodzenia. Najistotniejszymi częściami niniejszego artykułu są: opis metody MED, wskazówki dotyczące optymalnego dostrojenia metody oraz interesujące przypadki zarówno laboratoryjne, jak i rzeczywiste