PhD and Masters by research theses (SoE)

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Browsing PhD and Masters by research theses (SoE) by Subject "Acoustic Emission"

Now showing 1 - 4 of 4
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    Condition Monitoring of Slow Speed Rotating Machinery Using Acoustic Emission Technology
    (Cranfield University, 2010-06) Elforjani, Mohamed Ali; Mba, David
    Slow speed rotating machines are the mainstay of several industrial applications worldwide. They can be found in paper and steel mills, rotating biological contractors, wind turbines etc. Operational experience of such machinery has not only revealed the early design problems but has also presented opportunities for further significant improvements in the technology and economics of the machines. Slow speed rotating machinery maintenance, mostly related to bearings, shafts and gearbox problems, represents the cause of extended outages. Rotating machinery components such as gearboxes, shafts and bearings degrade slowly with operating time. Such a slow degradation process can be identified if a robust on-line monitoring and predictive maintenance technology is used to detect impending problems and allow repairs to be scheduled. To keep machines functioning at optimal levels, failure detection of such vital components is important as any mechanical degradation or wear, if is not impeded in time, will often progress to more serious damage affecting the operational performance of the machine. This requires far more costly repairs than simply replacing a part. Over the last few years there have been many developments in the use of Acoustic Emission (AE) technology and its analysis for monitoring the condition of rotating machinery whilst in operation, particularly on slow speed rotating machinery. Unlike conventional technologies such as thermography, oil analysis, strain measurements and vibration, AE has been introduced due to its increased sensitivity in detecting the earliest stages of loss of mechanical integrity. This programme of research involves laboratory tests for monitoring slow speed rotating machinery components (shafts and bearings) using AE technology. To implement this objective, two test rigs have been designed to assess the capability of AE as an effective tool for detection of incipient defects within low speed machine components (e.g. shafts and bearings). The focus of the experimental work will be on the initiation and growth of natural defects. Further, this research work investigates the source characterizations of AE signals associated with such bearings whilst in operation. It is also hoped that at the end of this research program, a reliable on-line monitoring scheme used for slow speed rotating machinery components can be developed.
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    An experimental investigation into the correlation between Acoustic Emission (AE) and bubble dynamics
    (Cranfield University, 2011-08) Husin, Shuib; Mba, David; Addali, Abdulmajid
    Bubble and cavitation effects phenomena can be encountered in two-phase gas-liquid systems in industry. In certain industries, particularly high-risk systems such as a nuclear reactor/plant, the detection of bubble dynamics, and the monitoring and measurement of their characteristics are necessary in controlling temperature. While in the petro-chemical engineering industry, such as oil transportation pipelines, the detection and monitoring of bubbles/cavitation phenomena are necessary to minimise surface erosion in fluid carrying components or downstream facilities. The high sensitivity of Acoustic Emission (AE) technology is feasible for the detection and monitoring of bubble phenomena in a two phase gas-liquid system and is practical for application within the industry. Underwater measurement of bubble oscillations has been widely studied using hydrophones and employing acoustic techniques in the audible range. However, the application of Acoustic Emission (AE) technology to monitor bubble size has hitherto not been attempted. This thesis presents an experimental investigation aimed at exploring AEs from gas bubble formation, motion and destruction. AE in this particular investigation covers the frequency range of between 100 kHz to 1000 kHz. The AE waveform analysis showed that the AE parameter from single bubble inception and burst events, i.e. AE amplitude, AE duration and AE energy, increased with the increase of bubble size and liquid viscosity. This finding significantly extends the potential use of AE technology for detecting the presence of bubbles in two-phase flow. It is concluded that bubble activity can be detected and monitored by AE technology both intrusively and non-intrusively. Furthermore, the bubble size can be determined by measurement of the AE and this forms the significant contribution of this thesis.
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    Monitoring hydrodynamic bearings with acoustic emission and vibration analysis
    (Cranfield University, 2012-06) Mirhadizadeh, S. A.; Mba, David
    Acoustic emission (AE) is one of many available technologies for condition health monitoring and diagnosis of rotating machines such as bearings. In recent years there have been many developments in the use of Acoustic Emission technology (AET) and its analysis for monitoring the condition of rotating machinery whilst in operation, particularly on high speed machinery. Unlike conventional technologies such as oil analysis, motor current signature analysis (MCSA) and vibration analysis, AET has been introduced due to its increased sensitivity in detecting the earliest stages of loss of mechanical integrity. This research presents an experimental investigation that is aimed at developing a mathematical model and experimentally validating the influence of operational variables such as film thickness, rotational speed, load, power loss, and shear stress for variations of load and speed conditions, on generation of acoustic emission in a hydrodynamic bearing. It is concluded that the power losses of the bearing are directly correlated with acoustic emission levels. With exponential law, an equation is proposed to predict power losses with reasonable accuracy from an AE signal. This experimental investigation conducted a comparative study between AE and Vibration to diagnose the rubbing at high rotational speeds in the hydrodynamic bearing. As it is the first known attempt in rotating machines. It has been concluded, that AE parameters such as amplitude, can perform as a reliable and sensitive tool for the early detection of rubbing between surfaces of a hydrodynamic bearing and high speed shaft. The application of vibration (PeakVue) analysis was introduced and compared with demodulation. The results observed from the demodulation and PeakVue techniques were similar in the rubbing simulation test. In fact, some defects on hydrodynamic bearings would not have been seen in a timely manner without the PeakVue analysis.In addition, the application of advanced signal processing and statistical methods was established to extract useful diagnostic features from the acquired AE signals in both time and frequency domain. It was also concluded that the use of different signal processing methods is often necessary to achieve meaningful diagnostic information from the signals. The outcome would largely contribute to the development of effective intelligent condition monitoring systems which can significantly reduce the cost of plant maintenance. To implement these main objectives, the Sutton test rig was modified to assess the capability of AET and vibration analysis as an effective tool for the detection of incipient defects within high speed machine components (e.g. shafts and hydrodynamic bearings). The first chapter of this thesis is an introduction to this research and briefly explains motivation and the theoretical background supporting this research. The second and third chapters, summarise the relevant literature to establish the current level of knowledge of hydrodynamic bearings and acoustic emission, respectively. Chapter 4 describes methodologies and the experimental arrangements utilized for this investigation. Chapter 5 discusses different NDT diagnosis. Chapter 6 reports on an experimental investigation applied to validate the relationship between AET on operational rotating machines, such as film thickness, speed, load, power loss, and shear stress. Chapter 7 details an investigation which compares the applicability of AE and vibration technologies in monitoring a rubbing simulation on a hydrodynamic bearing.
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    Slug Velocity Measurement and Flow Regime Recognition Using Acoustic Emission Technology
    (Cranfield University, 2013-07) Alssayh, Muammer Ali Ahmed; Mba, David; Addali, Abdulmajid
    Slug velocity measurement and flow regime recognition using acoustic emission technology are presented. Two non-intrusive and three intrusive methods were employed to detect the slug regime and measure its velocity using AE sensors. For the non-intrusive methods, AE sensors were placed directly on the exterior of the steel pipe section of the test rig with and without clamps. The intrusive method involved using different waveguide configurations with the AE sensors flush with the inner wall of the pipe. The experimental study presented investigated the application of Acoustic Emission (AE) technology for detecting slug velocity in addition to differentiating flow regime in two-phase (gas/liquid) flow in horizontal pipes. It is concluded that the slug velocity can be determined with acoustic emission (AE) sensors. The results were compared to slug velocities measured using high speed camera (HSC) and Ultrasound Transit Time (UST) techniques with good agreement between the three techniques at low gas void fraction (GVF). However, at high GVF (up to 95%) where the UST technique has limitations in application, the AE and HSC offered a good agreement. Flow regimes were also differentiated by using a combination of AE technology and Kolmogorov–Smirnov test technique. Stratified, slug and bubble regimes were recognised differentiated.
**Copy of record** Please note that the electronic theses currently available on this server have been originally submitted in a paper format. In all cases the bound paper thesis is the copy of record.