THE INVESTIGATION INTO THE CONDITION MONITORING OF TRIBOLOGICAL BEHAVIOUR BETWEEN PISTON RING AND CYLINDER LINER USING ACOUSTIC EMISSIONS

To improve engine operational performance and reliability, this study focuses on the investigation into the behaviour of tribological conjunction between the ring - liner based on a comprehensive analysis of non-intrusive acoustic emission (AE) measurement. Particularly, the study will provide more knowledge of using AE for online monitoring and diagnosing the performances of the conjunction. To fulfil this study, it integrates analytical predictions of the theoretical modelling for the AE generation mechanism with extensive experimental evaluations. Moreover, effective signal processing techniques are implemented with a combination of the model based AE predictions to extract the weak and nonstationary AE contents that correlate more with the tribological behaviour. Based on conventional tribological models, tribological AE is modelled to be due to two main dynamic effects: asperity-asperity collision (AAC) and fluid-asperity interaction (FAI), which allows measured AE signals from the tribological conjunction to be explained under different scenarios, especially under abnormal behaviours. FAI induced AE is more correlated with lubricants and velocity. It presents mainly in the middle of engine strokes but is much weaker and severely interfered with AEs from not only valve landings, combustion and fuel injection shocks but also the effect of considerable AACs due to direct contacts and solid particles in oils. To extract weak AEs for accurately diagnosing the tribological behaviours, wavelet transform analysis is applied to AE signals with three novel schemes: 1) hard threshold based wavelet coefficients selection in which the threshold value and wavelet analysis parameters are determined using a modified velocity of piston motion which has high dependence on the AE characteristics predicted by the two models; 2) Adaptive threshold wavelet coefficients selection in which the threshold is gradually updated to minimise the distance between the AE envelopes and the predicted dependence; and 3) wavelet packet transform (WPT) analysis is carried out by an optimised Daubechies wavelet through a novel approach based on minimising the time and frequency overlaps in WPT spectrum. Based on these optimal analyses, the local envelope amplitude (LEA) and the average residual wavelet coefficient (ARWC) are developed from AE signals as novel indicators to reflect the tribological behaviours.\ud Both the hard threshold based LEA and wavelet packet transform LEA values allow two different new lubricants to be diagnosed in accordance with model predictions whereas they produce less consistent results in differentiating the used oil under several operating conditions. Nevertheless, ARWC can separate the used oil successfully in that it can highlight the AAC effects of particle collisions in used oils. Similarly, LEA shows little impacts of two alternative fuels on the tribological behaviours. However, ARWC shows significantly higher amplitudes in several operating conditions when more particles can be produced due to unstable and incomplete combustions of both the biodiesel and FT diesel, compared with pure diesel, indicating they can cause light wear

Fault detection in rotating machinery using acoustic emission

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonRotating machinery is a critical asset of industrial plants worldwide. Bearings and gearboxes are two of the most common components found in rotating machinery of industrial plants. The malfunction of bearings and gearboxes lead the machine to fail and often these failures occur catastrophically leading to personnel injuries. Therefore it is of high importance to identify the deterioration at an early stage. Among the techniques applied to detect damage in rotating machinery, acoustic emission has been a prevalent field of research for its potential to detect defects at an earlier stage than other more established techniques such as vibration analysis and oil analysis. However, to reliably detect the fault at an early stage de-noising techniques often must be applied to reduce the AE noise generated by neighbouring components and normal component operation. For this purpose a novel signal processing algorithm has been developed combining Wavelet Packets as a pre-processor, Hilbert Transform, Autocorrelation function and Fast Fourier transform. The combination of these techniques allows identification of g repetitive patterns in the AE signal that are attributable to bearing and gear damage. The enhancement for early stage defect detection in bearings and gears provided by this method is beneficial in planning maintenance in advance, reducing machinery down-time and consequently reducing the costs associated with bearing breakdown. The effectiveness of the proposed method has been investigated experimentally using seeded and naturally developed defects in gears and bearings. In addition, research into the optimal Wavelet Packet node that offers the best de-noising results has been performed showing that the 250-750 kHz band gives the best SNR results. The detection of shaft angular misalignment using Acoustic Emission has been investigated and compared with acceleration spectra. The results obtained show enhancements of AE in detection shaft angular misalignment over vibration analysis in SNR and stability with varying operational conditions

Robotic surface exploration with vision and tactile sensing for cracks detection and characterisation

This thesis presents a novel algorithm for crack localisation and detection based on visual and tactile analysis via fibre-optics. A finger-shaped sensor based on fibre-optics is employed for the data acquisition to collect data for the analysis and the experiments. Three pairs of fibre optics are used to measure the sensor's soft part deformation via changes in the reflected light intensity. A fourth pair of optical fibre cables is positioned at the tip of the finger and it is used to sense the proximity to external objects. To detect the possible locations of cracks a camera is used to scan an environment while running an object detection algorithm. Once the crack is detected, a fully-connected graph is created from a skeletonised version of the crack. Minimum spanning tree is then employed for calculating the shortest path to explore the crack which is then used to develop the motion planner for the robotic manipulator. The motion planner divides the crack into multiple nodes which are then explored one by one. Then, the manipulator starts the exploration and performs the tactile data classification to confirm if there is indeed a crack in that location or just a false positive from the vision algorithm. This is repeated until all the nodes of the crack are explored. If a crack is not detected from vision, then it won't be further explored in the tactile step. Because of this, false negative have the biggest weight and recall is the most import metric in this study. I perform experiments to investigate the improvements for the time required during exploration when using visual and tactile modalities together. The experimental studies demonstrate that exploring a fractured surface with a combination of visual and tactile modalities is four times faster than using solely the tactile mode. The accuracy of detection is also improved when the two modalities were combined. Experiments are also performed in order to develop a robust machine learning model to analyse and classify the tactile data acquired during exploration via the fibre-optics sensor. Frequency domain features are explored to investigate the spectrum of the signal. Results show that when training machine learning models and deep learning networks using these features, the resulting models are more robust when tested across different databases, on which they are not trained. Thus, when computer vision techniques may fail because of light conditions or extreme environments, fibre-optics sensors can be employed to analyse the presence of cracks on explored surfaces via machine learning and deep neural network algorithms. Still, when introducing tactile in extreme environments, caution must be used when making contact with possible fragile surfaces which may break because of the friction produced by the tactile sensor. Proximity may be used in this case to calculate the distance between the sensor and the object and to reduce speed when getting closer to the object. In conclusion, the thesis has contributed to advances in crack detection by introducing a multi-modal algorithm that is used to detect cracks in the environment via computer vision and then confirming the presence of a crack via tactile exploration and machine learning classification of the data acquired from a fibre-optic-based sensor. Few methods currently use tactile sensing for crack characterisation and detection and this is the first study which shows the reliability of tactile-based methodologies for crack detection via machine learning analysis. Furthermore, this is the first method which combines both tactile and vision for crack analysis

Condition monitoring of belt based motion transmission systems

A key asset of Royal Mail Group consists of a nationwide network of sorting offices that forms a constituent component of the means through which the organisation provides an efficient nationwide postal service within the United Kingdom. It may be argued that the efficiency currently possessed by modem sorting offices is due to the utilisation of machines that automate the process of sorting items of mail. The modem letter-sorting machine possessed by Royal Mail can sort up to 30,000 letters per hour; such machines serve as an example of an achievement of the application of Mechatronics. The maintenance of letter sorting machines constitutes a large overhead for the organisation. In the face of competition from pervasive electronic media within the personal communications market and the prospect of deregulation, Royal Mail seeks to streamline its operation in part by the reduction of the overheads incurred through maintenance of letter sorting machinery. The adoption of condition based maintenance techniques and predictive maintenance, for letter sorting machine components such as belts and bearings, forms part of the strategy through which Royal Mail seeks to reduce this overhead. Utilisation of flat belts and timing belts for the implementation of key functions in letter sorting machinery, such as the transportation of items of mail within the mail sorting process, results in the use of many such components within letter sorting machinery. A direct link exists between the maintenance of peak performance of a sorting machine and the maintenance of belt drives; as such the maintenance of belt drives forms a substantial component of the maintenance overhead. The focus of this thesis consists of the condition monitoring of belt based motion transmission systems and in particular, flat belts. The research that forms the basis of this thesis consists of three elements. Firstly, consideration of current knowledge of belt based power transmission such as knowledge of the mechanics of the belt based power transmission process within the context of condition monitoring... [cont'd

30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017)

Proceedings of COMADEM 201

An innovative approach to dynamic driving simulations for vehicle thermal management processes

Extending from steady state simulation cases allows engineers to investigate the "real" on road conditions that are typically associated with transient characteristics. The ability to predict time dependent thermal behavior of vehicle environments leads to improved product development (with optimised modification potential) and an inherent reduction in experimental dependency and cost. Additionally many of the critical thermal cases experimentally validated are coupled to non-equilibrium boundary conditions, resulting either in an over-prediction through steady state 3-D CFD modeling or an inaccurate prediction through 1-D modeling. Today’s current industrial standard for virtual vehicle thermal management is mainly limited to steady-state conditions with some semi dynamic cases. Previous attempts have been proposed in the literature by industrial experts, to simulate unsteady thermal behavior of these time dependent vehicle conditions (e.g. thermal soak and hill climb). However, some of these proposals require a dependency on strong computing power, complete 3-D exhaust flow simulations, and complex multi-model coupling arrangements. Even though these methods incorporate realistic modeling approaches (due to the envisioned availability in computational resources), they lack the potential to accommodate complex boundary conditions, and to date no methodology has been able to simulate dynamic driving scenarios. Which brings up the question, why? The research proposes that the vehicle simulation field has overlooked the possibility to attempt highly transient cases, such as dynamic driving, due to the extreme volatility existing within vehicle boundary conditions, coupled to the traditional approaches which attempt to simulate these conditions. Therefore for numerical stability the simulation time scales have to be drastically reduced in order to resolve the high boundary condition fluctuations. This naturally exaggerates the calculation time for reasonable results and consequently compromises the application of the methodology for industry (considering the vehicle development time constraints). Therefore due to the simulation paradigm, “that original boundary conditions need to be modeled”, dynamic driving scenarios for full vehicle configurations is considered unfeasible. Simulation simplification is typically made on the geometrical modelling side, the implementation of physics or the assumptions of certain sub-system parameters, but significant alteration has never been made to the fundamental vehicle boundary conditions. However it is clear that the mass of the component can dampen the speed of its surface averaged thermal response to a given set of boundary conditions. Therefore the component essentially reacts at a different time scale to that of the exposed energy flux. Through this understanding it is evident that there is a potential to simplify the boundary conditions (therefore accelerating the calculation) based on the response nature of components. The following research aims at challenging the current simulation paradigm by introducing a methodology which simplifies the vehicle boundary conditions. The research goal is firstly the proof that dynamic driving profiles are possible to simulate with the current computational resources for full vehicle configurations. And secondly, the simplification of boundary conditions coupled to a new methodology to simulate these conditions, can replicate the time dependent component temperature behaviors, without significant depreciation in simulation accuracy. In the following research, a technique is presented which simplifies the high frequency changes within vehicle boundary conditions through the utilisation of wavelet transform based signal decomposition. Through identifying the thermally relevant frequency ranges (which correspond to component temperature change) a simplified boundary condition signal is derived. This simplified signal is then utilised in a quasi-transient approach to simulate the time dependent thermal behavior of the vehicle under highly dynamic loading conditions (e.g. Race-Track). A sensitivity study was also conducted to identify the propagation of error corresponding to the utilisation of simplified boundary conditions compared to the original input signals. Then a quasi-transient approach was compared to a fully transient approach in order to identify the error associated with the utilisation of multiple steady state CFD solutions. Additionally several investigation were conducted on the type of CFD solution necessary to achieve appropriate convection conditions for a quasi-transient approach. Ultimately the optimal parameters from these prior sensitivity studies corresponding to the least introduced error were implemented on a full vehicle configuration. Here profile independence was explored by transferring the proposed methodology to alternative dynamic driving profiles. Simulation results on multiple profiles were validated through experimental climatic wind tunnel tests, where a strong correlation was attained. These results were achieved with very little penalty on resources, whereby the methodology yielded a fraction of the calculation times (using 1/5th of the computing capacity) published in literature by alternative methods on simpler driving profiles. Additionally it was found that the simulation accuracy achieved was independent of driving profile, with discrepancies corresponding to modeling limitations on the vehicle. These results further confirmed the transferability capacity of the proposed methodology and the potential for wide scale application beyond the focus of this investigation

Investigation into the dynamic responses and tribological characteristics of cylinder liners in a IC engine with alternative fuels

Promoted by the realisation of dwindling fossil fuel supplies and their adverse environmental impacts, there more and more types of alternative fuels to fossil diesel have been used and investigated in compression ignition engines. However, the majority of researches on alternative fuels mainly focus on their power performance, efficiency and emission performance, without fully investigating the potential effects on the vibro-acoustic emissions and tribological characteristics of engines caused by their significant differences in physical and chemical properties. Consequently, the impacts of long-term use of alternative fuels on structural failure, lubrication degradation, friction aggravation, overall service life spans and associated maintenance activities of internal combustion (IC) engines have not yet been fully understood. To reduce this gap this thesis focuses on the investigation into the vibration responses of cylinder liners in a diesel engine to accurately characterises the tribological behaviour between the piston rings and cylinders which is one of the most decisive sub-processes that determine engine performance and yet is correlated with the combustion of different fuels. In particular, the investigation was carried out by coupling the hydrodynamic lubrication model with structural vibration effects through a series of extensive numerical simulations and systematic experimental evaluations in order to establish a vibration based technique to monitoring tribological behaviour and thereby accurately assess the influence. Based on the dynamic coupling mechanisms between the combustion characteristics of alternative fuels and the tribological behaviours of cylinder liners, the most significant influences from the fuel burning on tribological behaviour of cylinder liners concerned in this study is a direct and physical approach such as the effect of liner vibrations on cylinder friction process, even though an indirect and chemical but very slow approach such as the deterioration of oil properties by combustion products can happen. To characterise the direct influence a finite element dynamic model was developed and validated for predicting the dynamic responses of cylinder liners to respective excitation sources including the highly nonlinear combustion pressure shocks and subsequent piston slap impacts. The realistic consideration of both the characteristics of structural modes up to 15kHz and nonlinearities of elastic assembly constraints allows obtaining accurate prediction that the combustion shocks cause vibrations in a frequency range around 10kHz with an amplitude order of 0.01μm, whereas the piston slaps in frequency range from 1k to 5kHz with an amplitude order 0.2μm, which gives a clear and quantitative indication of the nonlinear phenomena of liner vibration due to combusting alternative fuels and varying lubrication conditions. In addition, a decomposition analysis of piston side-thrust forces provides more insight of the localized response characteristics corresponding to coupling interactions of combustion force with inertia force of piston assembly. To further investigate the potential influences of structural deformations to tribological behaviours of cylinder assemblies, a new dynamic deformation based lubrication model was developed based on an employment of improved shearing factors in which the effect of inevitable liner vibrations is included to obtain a more realistic lubricating film formation, distribution and tribological behaviours. The simulation studies show that this advancement in modelling oil films predicts that the biodiesel with more intense vibration emissions is able to reduce the friction loss between pistons and liners, whereas the methanol-diesel blend with weakened liner dynamic response may exacerbate the friction loss of IC engines. This finding confirms further that the vibration responses allow a straightforward and in-depth indication of the effect generated by using different fuels. In addition, a further experimental investigation was carried out based on a motoring engine test, in which high frequency sinusoidal vibrations at 25 kHz, 30 kHz and 40 kHz are added to the external surface of the linear. The observable changes in motoring torque verify that proper external vibrations can affect the tribological behaviours between the pistons and liners, including both asperity friction and viscous friction, and resulting in the friction reduction of IC engines. Particularly the 40 kHz vibration at the maximal driving power of the test device can achieve a reduction of 1.79% in the motoring torque. This has demonstrated more on the effectiveness of this vibration based diagnostic method in assessing the influences of alternative fuels upon tribological behaviours of piston ring and cylinder liners. Finally, further researches on the subjects is also proposed in order to complete the vibration based diagnostics in achieving more accurate assessment of engine lubrication conditions and effective friction reduction

Rolling contact fatigue failures in silicon nitride and their detection

The project investigates the feasibility of using sensor-based detection and processing systems to provide a reliable means of monitoring rolling contact fatigue (RCF) wear failures of silicon nitride in hybrid bearings. To fulfil this investigation, a decision was made early in the project to perform a series of hybrid rolling wear tests using a twin disc machine modified for use on hybrid bearing elements.The initial part of the thesis reviews the current understanding of the general wear mechanisms and RCF with a specific focus to determine the appropriate methods for their detection in hybrid bearings. The study focusses on vibration, electrostatic and acoustic emission (AE) techniques and reviews their associated sensing technologies currently deployed with a view of adapting them for use in hybrids. To provide a basis for the adaptation, an understanding of the current sensor data enhancement and feature extraction methods is presented based on a literature review.The second part describes the test equipment, its modifications and instrumentation required to capture and process the vibration, electrostatic and AE signals generated in hybrid elements. These were identified in an initial feasibility test performed on a standard twin disc machine. After a detailed description of the resulting equipment, the thesis describes the calibration tests aimed to provide base data for the development of the signal processing methods.The development of the signal processing techniques is described in detail for each of the sensor types. Time synchronous averaging (TSA) technique is used to identify the location of the signal sources along the surfaces of the specimens and the signals are enhanced by additional filtering techniques.The next part of the thesis describes the main hybrid rolling wear tests; it details the selection of the run parameters and the samples seeded with surface cracks to cover a variety of situations, the method of execution of each test run, and the techniques to analyse the results.The research establishes that two RCF fault types are produced in the silicon nitride rolling element reflecting essentially different mechanisms in their distinct and separate development; i) cracks, progressing into depth and denoted in this study as C-/Ring crack Complex (CRC) and ii) Flaking, progressing primarily on the surface by spalls. Additionally and not reported in the literature, an advanced stage of the CRC fault type composed of multiple and extensive c-cracks is interpreted as the result of induced sliding in these runs. In general, having reached an advanced stage, both CRC and Flaking faults produce significant wear in the steel counterface through abrasion, plastic deformation or 3-body abrasion in at least three possible ways, all of which are described in details

ReSCon '12, Research Student Conference: Book of Abstracts

The fifth SED Research Student Conference (ReSCon2012) was hosted over three days, 18-20 June 2012, in the Hamilton Centre at Brunel University. The conference consisted of 130 oral and 70 poster presentations, based on the high quality and diverse research being conducted within the School of Engineering and Design by postgraduate research students. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School