Rolling element bearings are one of the most significant elements and frequently-used components in mechanical systems. Bearing fault detection and diagnosis is important for preventing productivity loss and averting catastrophic failures of mechanical systems. In industrial applications, bearing life is often difficult to predict due to different application conditions, load and speed variations, as well as maintenance practices. Therefore, reliable fault detection is necessary to ensure productive and safe operations. Vibration analysis is the most widely used method for detection and diagnosis of bearing malfunctions. A measured vibration signal from a sensor is often contaminated by noise and vibration interference components. Over the years, many methods have been developed to reveal fault signatures, and remove noise and vibration interference components. Though many vibration based methods have been proposed in the literature, the high frequency resonance (HFR) technique is one of a very few methods have received certain industrial acceptance. However, the effectiveness of the HFR methods depends, to a great extent, on some parameters such as bandwidth and centre frequency of the fault excited resonance, and window length. Proper selection these parameters is often a knowledge-demanding and time-consuming process. In particular, the filter designed based on the improperly selected bandwidth and center frequency of the fault excited resonance can filter out the true fault information and mislead the detection/diagnosis decisions. In addition, even if these parameters can be selected properly at beginning of each process, they may become invalid in a time-varying environment after a certain period of time. Hence, they may have to be re-calculated and updated, which is again a time-consuming and error-prone process. This undermines the practical significance of the above methods for online monitoring of bearing conditions. To overcome the shortcomings of existing methods, the following four non-parametric and non-filtering methods are proposed: 1. An amplitude demodulation differentiation (ADD) method, 2. A calculus enhanced energy operator (CEEO) method, 3. A higher order analytic energy operator (HO_AEO) approach, and 4. A higher order energy operator fusion (HOEO_F) technique. The proposed methods have been evaluated using both simulated and experimental data.

Rolling element bearings are one of the most significant elements and frequently-used components in mechanical systems. Bearing fault detection and diagnosis is important for preventing productivity loss and averting catastrophic failures of mechanical systems. In industrial applications, bearing life is often difficult to predict due to different application conditions, load and speed variations, as well as maintenance practices. Therefore, reliable fault detection is necessary to ensure productive and safe operations. Vibration analysis is the most widely used method for detection and diagnosis of bearing malfunctions. A measured vibration signal from a sensor is often contaminated by noise and vibration interference components. Over the years, many methods have been developed to reveal fault signatures, and remove noise and vibration interference components. Though many vibration based methods have been proposed in the literature, the high frequency resonance (HFR) technique is one of a very few methods have received certain industrial acceptance. However, the effectiveness of the HFR methods depends, to a great extent, on some parameters such as bandwidth and centre frequency of the fault excited resonance, and window length. Proper selection these parameters is often a knowledge-demanding and time-consuming process. In particular, the filter designed based on the improperly selected bandwidth and center frequency of the fault excited resonance can filter out the true fault information and mislead the detection/diagnosis decisions. In addition, even if these parameters can be selected properly at beginning of each process, they may become invalid in a time-varying environment after a certain period of time. Hence, they may have to be re-calculated and updated, which is again a time-consuming and error-prone process. This undermines the practical significance of the above methods for online monitoring of bearing conditions. To overcome the shortcomings of existing methods, the following four non-parametric and non-filtering methods are proposed: 1. An amplitude demodulation differentiation (ADD) method, 2. A calculus enhanced energy operator (CEEO) method, 3. A higher order analytic energy operator (HO_AEO) approach, and 4. A higher order energy operator fusion (HOEO_F) technique. The proposed methods have been evaluated using both simulated and experimental data.

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.

Solar energy harvesting using photovoltaic (PV) systems has gained popularity in recent years due to its relative ease of use and its cost efficiency compared to the rest of the clean energy sources. However, to further expand the application of PV systems requires making them more desirable than the other competitive energy sources. The improvement of safety and cost efficiency are requisites for further popularization of PV system application. To satisfy these requisites it is necessary to optimally design the system against the environmental conditions. Wind action is one of the main ambient loads affecting the performance of PV systems. This dissertation aims to investigate the effects of wind load on residential scale roof mounted PV panels and their supporting structures as well as evaluating the structural response of the system to the wind-induced vibration. To achieve these goals, several full- and large-scale experimental tests were performed at the Wall of Wind Experimental Facility at Florida International University (FIU). The wind effects on different PV system and roof configurations were investigated in these tests. The results shed light on the most influential parameters affecting the wind pressures acting on the PV panel surface. In addition, the findings are presented in the form of design pressure coefficients for adoption to future building codes and wind standards. The second phase of the physical testing included the investigation of the actual response of the PV system to the wind action. Because of the dynamic properties of the PV panel, it was expected that the wind induced vibration can affect the dynamic response of the system including the acceleration at the panel surface and support reactions at the racking system to roof interface. To test this theory, two different models of the system were developed, one with the real PV panels and the other one with wooden rigid panels. Comparing the results, it was concluded that the dynamic response of the system was not considerably affected by wind-induced fluctuations. Finally, and to better understand the dynamic response of the system, an analytical model was developed using ANSYS and dynamic analysis was carried out using as input the wind induced pressure data acquired from the physical testing. At the first step, the analytical model was verified by comparing the analytical modal frequencies to the experimental natural frequencies obtained from the hammer test. It was shown that the analytical model can well represent the dynamic properties of the actual model. However, once the reaction output was compared to the loadcell data recorded during the wind tunnel test, there was a considerable discrepancy between the results. It was assumed that the deflection of the supporting structure caused this discrepancy. This assumption was verified and it was concluded that the supporting structure can significantly influence the dynamic response of the system.

Increased demand for smaller electronics is driving the electronic packaging industry to develop smaller, more efficient component level packages. Surface mounted components, such as flip chips, ball grid arrays (BGAs), and chip-scale packages (CSPs), are being developed for use in high-volume production. All of these technologies use solder bumps to attach the active silicon to the substrate, and traditional nondestructive methods such as machine vision, acoustic microscopy or x-ray inspection cannot easily find solder bump defects. Therefore, a system, consisting of an Nd:YAG laser that delivers pulses of infrared energy to the surface of the chip, a laser interferometer to record surface vibrations, and a high-speed data acquisition system to record the signals, was developed. The pulsed laser generates ultrasound on the chips surface, exciting the whole chip into a vibration motion, and the interferometer measures the vibration displacement of the chips surface at several points. Changes in the quality of the device or its attachment to the board produce changes in the free vibration response. Characterization of the differences between good devices and devices with defects, both in time domain and frequency domain, is performed using signal analysis. The system has inspected flip chips and chip scale packages for missing and misaligned solder balls, but to characterize the resolution of the system for open solder joints, a study of the vibration modes excited by the laser source in a flip chip was performed on specimens with intentionally created defects. Experimental measurements of excited modes were compared with a modal analysis model created in ANSYS, and defects were detected as small changes in the mode shape on the surface of the chips. Current inspection methods have also been inadequate for inspecting multi-layer ceramic capacitors (MLCCs). Flex cracks, caused by manufacturing processes, often cause the capacitors to fail in-service. Samples that have been cracked intentionally were compared with reference samples to determine the feasibility of using this technique to monitor the condition of MLCCs on an assembly line. Currently, there is no on-line inspection method for controlling this problem, but this technique was able to differentiate between good and damaged capacitors.

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.

Abstract Despite the large amount of research work in condition based maintenance and condition monitoring methods, there is still a need for more reliable and accurate methods. The clear evidence of that need is the continued dependence on time based maintenance, especially for critical applications such as turbomachinery and airplane engines. The lack of accurate condition monitoring systems could lead to not only the unexpected failures as well as the resulting hazards and repair costs, but also a huge waste of material and time because of unnecessary replacement due to false alarms and unnecessary repair and maintenance. Temperature change is a phenomenon that accompanies every dynamic activity in the universe. However, it has not been adequately exploited for mechanical system condition monitoring. The reason is the slow response of current temperature monitoring systems compared to other condition monitoring methods such as vibration analysis. Many references inferred that the change in temperature is not sensible until approaching the end of the monitored component life and even the whole system life (Kurfess, et al., 2006; Randall, 2011; Patrick, et al., March 7-14, 2009). On the other hand, the most commonly used condition monitoring method, i.e., vibration analysis, is not free from pitfalls. Although vibration analysis has shown success in detecting some bearing faults, for other faults like lubrication problems and gradual wear it is much less effective. Also, it does not give a reliable indication of fault severity for many types of bearing faults. The advancement of thermography as a temperature monitoring tool encourages the reconsideration of temperature monitoring for mechanical system fault detection. In addition to the improved accuracy and responsiveness, it has the advantage of non-contact monitoring which eliminates the need for complex sensor mounting and wiring especially for rotating components. Therefore, in current studies the thermography-based monitoring method is often used either as a distinct method or as a complementary tool to vibration analysis in an integrated condition monitoring system. The main objectives of this study are hence to: 1. Define heat sources in the rolling element bearings and overview two of the most famous bearing temperature calculation methods. 2. Setup a bearing test rig that is equipped with both vibration and temperature monitoring systems. 3. Develop a temperature calculation analytical model for rolling element bearing that include both friction calculation and heat transfer models. The friction calculated by the model will be compared to that calculated using the pre-defined empirical methods. The heat transfer model is used for bearing temperature calculation that will be compared to the experimental measurement using different temperature monitoring devices. 4. Propose a new in-band signal enhancement technique, based on the synchronous averaging technique, Autonomous Time Synchronous Averaging (ATSA) that does not need an angular position measuring device. The proposed method, in addition to the Spectral Kurtosis based band selection, will be used to enhance the bearing envelope analysis. 5. Propose a new method for classification of the bearing faults based on the fault severity and the strength of impulsiveness in vibration signals. It will be used for planning different types of tests using both temperature and vibration methods. 6. Develop and experimentally test a new technique to stimulate the bearing temperature transient condition. The technique is supported by the results of finite element modeling and is used for bearing temperature condition monitoring when the bearing is already running at thermal equilibrium condition.

Present-day builders of harpsichords disagree as to the use of iron or carbon-steel wire in their attempt to duplicate the tonal qualities of the early 16th century instruments. The variations in tone produced by vibrating iron and steel wires may be due, at least in part, to differences in their decay characteristics. A wire was set into vibration by placing a section in a magnetic field and passing a variable-frequency alternating current through it. A condition of resonance was established by appropriately selecting frequencies, lengths, and tensions that would simultaneously satisfy the relationship: fr = n/2L(T/p)1/2. Then measurements of decay time as a function of frequency were made for a variety of typical harpsichord strings: iron, steel, brass, bronze, etc. Samples varied in diameter from 170 mm to 600 mm and the resonant frequencies ranged from 20 Hz to 12,000 Hz. Changes in energy loss through the supports were measured by varying the size and mass of the supports and by modifying the method of attachment of the wire. Differences in loss of energy due to internal friction were noted in the comparison of decay times for different wire materials and diameters. The energy losses due to sound radiation and viscous damping were examined by placing the vibrating wire in a vacuum. Two significant conclusions, among others gathered from the data, indicate that: 1. For similar samples of iron and steel wire vibrating under like conditions, the steel wire will vibrate for a longer period of time than the iron wire. 2. Energy losses to sound radiation and viscous damping greatly exceed all other modes of energy loss from the wire. Suggestions for additional investigations based On the results of this paper are presented in the concluding pages.

Internal convective cooling is a method by which components, such as gas turbine blades, are protected from damage caused by elevated temperatures. Heat pipes are structures that transport and dissipate large quantities of pressurized thermal energy. The thermal energy is transported from a heat source to a thermal sink via evaporative cooling. A radially rotating high temperature heat pipe employs centrifugal force to return or drive the working saturated-vapor mixture from the condenser section to the evaporator section. A rotating heat rig is being developed at the University of Central Florida (UCF) in order to gain a better understanding of the interaction between thermal Conductivity, rotational speed, operating temperatures and thermal loads. As a part of its development, this study will focus on identifying key factors that maximize the first critical speeds on rotating heat pipe assemblies having non-uniform temperature distributions. It was found that in order to avoid reaching the first critical speed the use of double bearings should be implemented. Since the temperature of the heat pipe will be non-uniform, this will have a minimal effect on the critical speed of the rotating rig. The first phase of the construction of the rotating rig will be stable and will provide valuable test data without reaching any critical speeds.

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