Wear testing and finite element analysis of nitrile rubber (NBR) hand pump seals

The use of Nitrile Butadiene Rubber NBR as seal in machines has increased in recent years. NBR is considered as the standard material for sealing and NBR owes its many applications to a range of special mechanical properties. However, the non-linear mechanical properties and incompressible behaviour of NBR make the analysis of NBR very difficult. The literature review highlighted the fact that the most common technical cause of hand pump failures was the wear of the piston seals. The contact surface of the piston seals with the bore surface (Brass) of the cylinder and the piston seal contact area are the key to calculating and determining seal friction force and seal wear rate. Several researchers carried out modelling of friction and wear processes, though little of these focused on the wear of NBR seals, and very limited research has been conducted on the wear of piston seals in the presence of water, and a very few has been reported regarding how to determined and calculating the wear rate of removal material of piston seals used in water hand pump

Intelligent Condition Monitoring and Prognostic Methods with Applications to Dynamic Seals in the Oil & Gas Industry

The capital-intensive oil & gas industry invests billions of dollars in equipment annually and it is important to keep the equipment in top operating condition to help maintain efficient process operations and improve the rate of return by predicting failures before incidents. Digitalization has taken over the world with advances in sensor technology, wireless communication and computational capabilities, however oil & gas industry has not taken full advantage of this despite being technology centric. Dynamic seals are a vital part of reciprocating and rotary equipment such as compressor, pumps, engines, etc. and are considered most frequently failing component. Polymeric seals are increasingly complex and non-linear in behavior and have been the research of interest since 1950s. Most of the prognostic studies on seals are physics-based and requires direct estimation of different physical parameters to assess the degradation of seals, which are often difficult to obtain during operation. Another feasible approach to predict the failure is from performance related sensor data and is termed as data-driven prognostics. The offline phase of this approach is where the performance related data from the component of interest are acquired, pre-processed and artificial intelligence tools or statistical methods are used to model the degradation of a system. The developed models are then deployed online for a real-time condition monitoring. There is a lack of research on the data-driven based tools and methods for dynamic seal prognosis. The primary goal in this dissertation is to develop offline data-driven intelligent condition monitoring and prognostic methods for two types of dynamic seals used in the oil & gas industry, to avoid fatal breakdown of rotary and reciprocating equipment. Accordingly, the interest in this dissertation lies in developing models to effectively evaluate and classify the running condition of rotary seals; assess the progression of degradation from its incipient to failure and to estimate the remaining useful life (RUL) of reciprocating seals. First, a data-driven prognostic framework is developed to classify the running condition of rotary seals. An accelerated aging and testing procedure simulating rotary seal operation in oil field is developed to capture the behavior of seals through their cycle of operation until failure. The diagnostic capability of torque, leakage and vibration signal in differentiating the health states of rotary seals using experiments are compared. Since the key features that differentiate the health condition of rotary seals are unknown, an extensive feature extraction in time and frequency domain is carried out and a wrapper-based feature selection approach is used to select relevant features, with Multilayer Perceptron neural network utilized as classification technique. The proposed approach has shown that features extracted from torque and leakage lack a better discriminating power on its own, in classifying the running condition of seals throughout its service life. The classifier built using optimal set of features from torque and leakage collectively has resulted in a high classification accuracy when compared to random forest and logistic regression, even for the data collected at a different operating condition. Second, a data-driven approach to predict the degradation process of reciprocating seals based on friction force signal using a hybrid Particle Swarm Optimization - Support Vector Machine is presented. There is little to no knowledge on the feature that reflects the degradation of reciprocating seals and on the application of SVM in predicting the future running condition of polymeric components such as seals. Controlled run-to-failure experiments are designed and performed, and data collected from a dedicated experimental set-up is used to develop the proposed approach. A degradation feature with high monotonicity is used as an indicator of seal degradation. The pseudo nearest neighbor is used to determine the essential number of inputs for forecasting the future trend. The most challenging aspect of tuning parameters in SVM is framed in terms of an optimization problem aimed at minimizing the prediction error. The results indicate the effectiveness and better accuracy of the proposed approach when compared to GA-SVM and XGBoost. Finally, a deep neural network-based approach for estimating remaining useful life of reciprocating seals, using force and leakage signals is presented. Time domain and frequency domain statistical features are extracted from the measurements. An ideal prognostic feature should be well correlated with degradation time, monotonically increasing or decreasing and robust to outliers. The identified metrics namely: monotonicity, correlation and robustness are used to evaluate the goodness of extracted features. Each of the three metric carries a relative importance in the RUL estimation and a weighted linear combination of the metrics are used to rank and select the best set of prognostic features. The redundancy in the selected features is eliminated using Kelley-Gardner-Sutcliffe penalty function-based correlation-clustering algorithm to select a representative feature from each of the clusters. Finally, RUL estimation is modeled using a deep neural network model. Run-to-failure data collected from a reciprocating set-up was used to validate this approach and the findings show that the proposed approach can improve the accuracy of RUL prediction when compared to PSO-SVM and XGBoost regression. This research has important contribution and implications to rotary and reciprocating seal domain in utilizing sensors along with machine learning algorithms in assessing the health state and prognosis of seals without any direct measurements. This research has paved the way to move from a traditional fail-and-fix to predict-and-prevent approach in maintenance of seals. The findings of this research are foundational for developing an online degradation assessment platform which can remotely monitor the performance degradation of seals and provide action recommendations on maintenance decisions. This would be of great interest to customers and oil field operators to improve equipment utilization, control maintenance cost by enabling just-in-time maintenance and increase rate of return on equipment by predicting failures before incidents

The measurement of the film thickness and the roughness deformation of lubricated elastomers

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AN EXPERIMENTAL AND NUMERICAL INVESTIGATION OF THE COMBINATION OF DIFFERENT DAMPER TYPES FOR IMPROVED CONTROL OF VIBRATION

Eliminating and reducing unwanted vibrations required a good knowledge of the dynamic systems fundamental components; mass, spring, and damper. Meanwhile, dampers are responsible for reducing the vibrations amplitudes and the time needed by a structure to reach its steady state. This research is focused on studying a combination of different dampers through computational and experimental approaches. Furthermore, parametric studies are conducted to investigate the parameters that affect each damper's damping behavior. Two dampers were designed, manufactured, modeled, and tested through this study. Firstly, a hybrid damper was developed by integrating two damping technologies; Viscous Fluid Damper (VFD) and Particle Impact Damper (PID). The VFD used in this study was a Mono-tube commercial viscous damper used in the automobile suspension system. On the other hand, the PID part consisted of a circular plastic enclosure filled with Stainless Steel 15mm diameter bearing balls. The Fluid Impact Hybrid Damper (FIHD) was designed by attaching the PID part to the VFD piston rod. A shaker testing setup was developed to drive the hybrid dampers piston rod into a sinusoidal dynamic load with a 1-8 Hz frequency range. The number of balls was changed three times (5, 10, and 15) to examine this parameter effect on the FIHDs damping effect. In addition, a Finite Element Model (FEM) of the FIHD was developed using LS-Dyna explicit solver. The FEM of the FIHD simulated the elastoplastic collisions between the balls and the walls using a piecewise-linear plasticity material model. Results were presented using Frequency Response Function (FRF) to show the damping effect in a set of force-independent results. The evaluated FRF of the two approaches (Experiment and FEM model) showed a noticeable reduction in amplitude at the systems natural frequency (2 Hz). In addition to the hybrid damper, this study also investigated a damper that belongs to the semi-active countermeasures known as Magnetorheological fluid (MRF) damper. MRF dampers damping effect is controlled using a magnetic field produced by an excitation system. In an MRF damper, a smart fluid is used as the damper fluid instead of using the classic hydraulic oil. The excitation system components were designed and manufactured based on dimensions reported in a previous study. The excitation system's magnetic field (MF) density value was obtained both experimentally and numerically using Comsol FE software. The MF study aimed to address the parameters that affect the magnetic field density, and thus, the MRF damping effect. Eventually, a Computational Fluid Dynamic (CFD) Analysis is conducted on the MRF damper. The CFD analysis describes the fluid flow between the compression and rebound champers through the internal orifices. Averaged Navier-Stokes equations are solved by the SIMPLE method, and the RNG k-? is used to model turbulence when the fluid passes through the orifice. The viscosity of the MRF was evaluated experimentally using a viscosity meter when applying different values of magnetic flux. The magnetic flux values were changed along with changing the excitation current values from 0 A to 5 A with a 1 A increment. Rebound and compression forces were observed from the static pressure contour plot. Based on the damping coefficients obtained from different viscosities values, the results showed that the damping values are exponentially increasing when increasing viscosity

Tribometer set-up and friction coefficient in elastomers of sealing systems

El objetivo de esta tesis es, realizar la puesta a punto de un tribómetro disponible en el Departamento de Ingeniería Mecánica y Aeroespacial (DIMEAS), laboratorio del Politécnico de Torino. El tribómetro se encontró con un actuador neumático-hidráulico. Con esta configuración, con el fin de realizar la adquisición de datos, se buscaron los sensores compatibles para cada tarea, luego fueron reparados y cada uno se calibró. El tribómetro es capaz de adquirir la velocidad de deslizamiento (mm/s), la posición (mm), las fuerzas tangenciales y normal (N). Fue desarrollado un programa en Labview capaz de adquirir y guardar las respectivas señales de la forma adecuada. De la misma manera, un script en Matlab fue desarrollado para calcular el coeficiente de fricción. El modelo utilizado para calcular el coeficiente de fricción fue el más simple, pero fiable, desarrollado por Coulomb, en el que sólo toma en cuenta la fuerza normal y la fuerza tangencial. Por último, se realizaron algunas pruebas con el fin de verificar el comportamiento del tribómetro.The objective of this thesis is to, perform the setup of a tribometer available at the Department of Mechanical and Aerospace Engineering (DIMEAS), laboratory of the Polytechnic University of Turin. The tribometer was found with a pneumohydraulic actuator. With this configuration, in order to perform the data acquisition, the compatible sensors for each task were searched, then they were repaired and each one was calibrated. The tribometer is capable to acquire the sliding velocity (mm/s), position (mm), tangential and normal forces (N). A program in Labview capable to acquire and save the respective signals in the adequate way was developed. In the same way, a Matlab script was developed to calculate the friction coefficient. The model used to calculate friction coefficient was the simplest but reliable one, developed by Coulomb, in which only takes in to account the normal force and the tangential force. Finally, were done some tests in order to verify the behavior of the tribometer.Ingeniero (a) ElectrónicoPregrad

Developments for the calculation of heavily loaded journal bearings

This thesis describes the development of an ElastoHydroDynamic (EHD) bearing calculation. The effect of body forces is shown to be important for highly loaded bearings in reciprocating internal combustion engines. Extension of the program to rotating machinery includes an examination of instability in the shaft bearings of a turbocharger. The development of a parameter to predict cavitation damage in a bearing is promising. Several calculation results using the program are shown. These are engine main bearing and connecting rod big-end bearings and full floating bearings for a turbocharger. The calculations on the big-end bearing if a racing engine show why the designers were having difficulty understanding the correct location for the oil feed hole position. Effects of elastic deformation, thermal deformation and manufacturing/assembly deformation all have a significant effect on the extent of the oil film. A novel calculation for a cavitation damage parameter is demonstrated successfully for a heavily loaded diesel engine bearing. The importance of body forces on the oil film due to high accelerations on certain bearings is shown to be theoretically important but not yet demonstrated. The program was written with the intention to be incorporated into the sponsoring company’s range of engine design software. A part of that development process included carrying out calculations to demonstrate to customers and present papers at conferences. The results of some of these calculations have been included in this thesis. Results of a study on the effect of crankshaft geometry on racing engine viscous friction losses were reported in a paper presented at the IDETC conference in Long Beach, 2005. This study used the first version of the software which only included Rigid Hydro Dynamics (RHD) at the time but was usable. Results of a study on stability of shaft motion in high speed turbocharger bearings were reported in a paper at the 8th International Turbocharger conference in London, 2006. At this time the program was still only capable of RHD calculations but could now solve for multiple oil films simultaneously and sweep through the speed range. The studies on the effects of body forces and the development of a cavitation parameter will be presented in papers in the near future

Analysis and Experiment of an Ultra-light Flapping Wing Aircraft

II Inspired by flying animals in nature especially birds, human has designed and attempted to achieve man-powered flapping wing aircraft in very early aviation history. Limited by the understanding of the aerodynamic theory and materials in practise, the bird-like aircraft remains as a dream and ambition for over a contrary. As the relevant knowledge and technology are fast developing in the last decade, the research topic becomes attractive again with encouraging results from a few full scale aircraft flight tests. Although it is suspected that a manned scale flapping wing may not be as efficient as fixed wing, the unique advantages of high manoeuvrability and short take-off and landing capability will keep flapping wing as one of the most potential type of personal and aerobatic aircraft in the future market. The aim of this project is to investigate into the feasibility and development of a bio-inspired bird-like man-powered ultra-light flapping wing aircraft (ULFWA). The project is based on analytical and experimental study of a scaled model taking an existing hang glider as the baseline airframe. Based on the characteristics of flying animals in nature and manmade hang glider properties, this thesis focuses its study on evaluating the feasibility and analysis of primarily a human powered aircraft. For this purpose, there are four main features as guidance in the ULFWA design. Firstly the flapping frequency was limited to below 2Hz. Secondly the hang glider airframe was adapted with a simple flapping mechanism design. Thirdly the flapping wing stroke and kinematics has been kept with the simplest and resonant movement to achieve high mechanical efficiency. Finally the wing structure has flexible rib of chord wise unsymmetrical bending stiffness to offset the aerodynamic lift loss in upstroke. An engine powered mechanism design was also studied as additional option of the ULFWA. The initial design and aerodynamic calculation of the ULFWA was based on the hang glider data including dimensions, MTOW (226 kg) and cruising speed. The unsteady aerodynamic lift and thrust forces were calculated based on Theodorsen’s theory and unsteady panel method in 2D and extended to 3D using strip theory. A set of optimal flapping kinematic parameters such as amplitude and combination of the heaving and pitching motion of the 2D wing section were determined by calculation and comparison in the limited range. Considering the maximum power and lag motion that human could achieve, the flapping frequency in the ULFWA design is limited to 1Hz. This slow motion leads to a much lower propulsive efficiency in terms of the optimum Strouhal Number (St=0.2-0.4), which was used as the design reference. Mechanism and structure design with inertia force calculation was then completed based on the kinematics. This led to the evaluation of power requirement, which was divided into two components, drag and inertia forces. The results show that the ULFWA needs minimum 2452.25W (equals to 3.29Bhp) to maintain sustainable cruise flight. In order to demonstrate the ULFWA flapping mechanism and structure design, a 1:10 scaled model with two pairs of wings of different stiffness were built for testing and measurement. Two servomotors were used as to simulate human power actuation. With this model, simplified structure and one of mechanism designs was shown. Four experiments were carried out to measure the model’s lift and thrust force. Because of the limited response of the servo motors, the maximum flapping frequency achieved is only 0.75 Hz in the specified flapping amplitude which is close to reality and has improvement margin. By reducing the flapping amplitude, the frequency can be increased to gain higher thrust. Although it is fund that the result from scaled model test is a little lower than theoretical result, it has demonstrated the feasibility and potential of human powered flapping wings aircraft

Tribology of Machine Elements

Tribology is a branch of science that deals with machine elements and their friction, wear, and lubrication. Tribology of Machine Elements - Fundamentals and Applications presents the fundamentals of tribology, with chapters on its applications in engines, metal forming, seals, blasting, sintering, laser texture, biomaterials, and grinding