Rolling-element bearings are widely used in various mechanical and electrical applications. Accordingly, a reliable bearing health condition monitoring system is very useful in industries to detect incipient defects in bearings, so as to prevent machinery performance degradation and malfunction. Although several techniques have been reported in the literature for bearing fault detection and diagnosis, it is still challenging to implement a bearing condition monitoring system for real-world industrial applications because of the complexity of bearing structures and noisy operating conditions. The objective of this thesis is to develop a novel intelligent system for more reliable bearing fault diagnostics. This system involves two sequential processes: feature extraction and decision-making. The proposed strategy is to develop advanced and robust techniques at each processing stage so as to improve the reliability of bearing condition monitoring. First, a novel wavelet spectrum analysis technique is proposed for the representative feature extraction. This technique applies the wavelet transform to demodulate the resonance signatures that are related to bearing health conditions. A weighted Shannon function is proposed to synthesize the wavelet coefficient functions to enhance feature characteristics. The viability of this technique is verified by experimental tests corresponding to various bearing health conditions. Secondly, an enhanced diagnostic scheme is developed for automatic decision-making. This scheme consists of modules of classification and prediction: a novel neuro-fuzzy classifier is developed to effectively integrate the strengths of the selected fault detection techniques (i.e., the resulting representative features) for a more accurate assessment of bearing health conditions; a novel multi-step predictor is proposed to forecast the future states of bearing conditions, which will be used to further enhance the diagnostic reliability. The investigation results have demonstrated that the developed intelligent diagnostic system outperforms other related bearing fault diagnostic schemes.

Software systems are growing rapidly in size and complexity, and becoming more and more difficult and expensive to maintain exclusively by human operators. These systems are expected to be highly available, and failure in these systems is expensive. To meet availability and performance requirements within budget, automated and efficient approaches for systems monitoring are highly desirable. Autonomic computing is an effort in this direction, which promises systems that self-monitor, thus alleviating the burden of detailed operation oversight from human administrators. In particular, a solution is to develop automated monitoring systems that continuously collect monitoring data from target systems, analyze the data, detect errors and diagnose faults automatically. In this dissertation, we survey work based on management metrics and describe the common features of these current solutions. Based on observations of the advantages and drawbacks of these solutions, we present a general solution framework in four separate steps: metric modeling, system-health signature generation, system-state checking, and fault localization. Within our framework, we present two specific solutions for error detection and fault diagnosis in the system, one based on improved linear-regression modeling and the second based on summarizing the system state by an informationtheoretic measurement. We evaluate our monitoring solutions with fault-injection experiments in a J2EE benchmark and show the effectiveness and efficiency of our solutions.

Democracy development techniques such as international election monitoring have increasingly become commonplace. Monitors are sent to far off locations to scrutinize the electoral processes and determine whether or not they have met the free and fair standards as established by their mandates. The term free and fair however, has become a catchphrase amongst many of those involved in the election monitoring and democracy development fields. The phrase is often interpreted loosely and is rarely clearly defined. Despite the recognition of the terms often differing interpretations, it remains a commonly used standard. The 2005 Ethiopian Elections demonstrate that free and fair, when interpreted differently by international electoral observers, can have consequential results. <p>The thesis provides a political analysis of the Carter Centers and European Unions international election monitoring final reports of the 2005 Ethiopian elections. Following the 2005 Ethiopian elections the Carter Centers and the European Unions electoral observation reports became highly politicized. In the post election period, the two organizations came to different conclusions in regards to the validity of the electoral process. At the core of these differences were the organizations differing conceptions of what constitutes free and fair electoral practices. In the post election period the European Unions and Carter Centers reports have been pitted against one and other as those concerned with the election results seek to make sense of the reports. <p>This thesis is significant because it asks relevant questions about the consequences of differing understandings of free and fair. The thesis seeks to provide insight into international election monitoring and provide recommendations to improve the process.

My study examines the relationship between principal and agent in a moral hazard setting where the principal has the ability to monitor the actions of the agent at an interim stage of the project. I show that monitoring can induce the agent to exert higher levels of effort and can result in a reallocation of project payoffs between the two parties. This reallocation is not a one-way street: Situations exist where monitoring encourages greater effort from the agent, resulting in greater project payoffs for both principal and agent. For projects that are characterized as high-risk, high-reward projects where agent involvement is costly, monitoring is often the optimal strategy; this is an explanation for why venture capital type investments are the subject of intense monitoring. When the principal can share monitoring results at an interim stage with the agent, the agent is able to modify his effort levels in certain situations for the benefit of both parties.

Engineering industries usually require nondestructive evaluation (NDE) methods to ensure quality control, safety, and optimized use of resources. Among potential NDE techniques, ultrasonic wave methods are widely used because of their versatility and affordability. For applications to layered structures, ultrasonic guided waves are naturally excited and detected, so these guided waves are the preferred choice when compared to conventional bulk waves. The main advantage of guided waves over bulk waves for layered structures is that these guided waves can propagate a much farther distance, and thus they enable long range inspection. It is important to note that guided waves are multi-mode, so a preferred mode can be selectively used, although it is sometimes more efficient to use multiple wave modes. The characteristics of guided waves, namely dispersive propagation and attenuation, are directly related to the properties of the system in which they are propagating, so the measurement of these wave characteristics can be used for material characterization and condition monitoring. Despite a number of successful techniques to experimentally measure propagation characteristics of guided waves, there is a lack of a standard procedure to obtain attenuation characteristics. This research develops such a quantitative and systematic procedure to extract attenuation characteristics from real guided wave time-domain signals. This research considers multiple wave-modes, and focuses on broadband attenuation measurements with laser ultrasonic techniques. The analytical model of guided waves with attenuation is studied in general cases, and a numerical simulation is developed to model the point source/receiver laser measurement system. The attenuation extraction technique is developed using synthetic signals generated by the simulation. Finally, this research demonstrates the use of experimentally-measured attenuation data for material characterization and condition monitoring by developing an inversion scheme to back-calculate material properties for a number of practical cases.

The motivation of this paper is to propose a simple and reliable method to identify on-road vehicle events, particularly in the driving situations. A content rhythm is extracted by applying a virtual line lies on the same position of each frame. Thereupon a simplified representation of a continuous video is to record the temporal information of vehicle status. Thus, vehicle situations such as changing lane, safe distance and speed display can be detected instantly by analyzing the statistical characteristics of content rhythm. The proposed method can not only prevent accidents but also improve the traffic safety by monitoring the on-road vehicle status. Experimental results show the proposed method is reliable for vehicle event detection.

The use of a wireless sensor network (WSN) to monitor an historic structure under rehabilitation is the focus of this research. To thoroughly investigate the issue, two main objectives are addressed: the development of a reliable WSN tailored for use in historic structures, and the implementation of the monitoring system in the field to test the feasibility of the WSN and its applicability for structural health monitoring (SHM). Three field studies are undertaken in this research. The Frankford Church, an historic wooden church which required foundation replacement, is the first field study. Sensors monitor tilt of the church’s walls throughout construction. During the construction process, the entire floor of the church is removed and the tree stump foundations are replaced by concrete masonry unit (CMU) blocks and steel pedestals. The tilt in the walls is correlated to the construction process. St. Paul Lutheran, an historic masonry church with timber-framed roof, constitutes the second field study. In this structure, the foundations along the exterior walls are underpinned and the floors are removed and replaced with a floating concrete slab. Detected movements are also correlated to the construction efforts. The Johanniskirche, an historic masonry church with moisture problems, is the final field study case. Real-time and past measured WSN climate data is used to determine the most appropriate solution for the humid climate and resulting condensation problems in this structure. From these results, a moisture migration risk analysis protocol is created for use with a WSN to address condensation issues. The results of the tilt monitoring indicate that the approach is realistic to monitor tilt in the walls of historic structures. For future research, it is recommended to implement motes with higher tilt sensitivity. Also, further development of energy saving algorithms and energy harvesting methods will improve the WSN’s performance. Climate monitoring results show it is feasible to monitor climate conditions of historic structures. The moisture migration protocol provides a basis for further improvement. Implementation of this tool will help predict condensation events and prevent future damage to the historic structure.

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In recent years, sustainable development has become one of the most important issues internationally. Many indicators related to sustainable development have been proposed and implemented, such as Island Taiwan and Urban Taiwan. However the missing values come along with environmental monitoring data pose serious problems when we conducted the study on building a sustainable development indicator for marine environment. Since data is the origin of the summarized information, such as indicators. Given the poor data quality caused by the missing values, there will be some doubts about the result accuracy when using such data set for estimation. It is therefore important to apply suitable data pre-processing, such that reliable information can be acquired by advanced data analysis. Several reasons cause the problem of missing value in environmental monitoring data, for example: breakdown of machines, ruin of samples, forgot recording, mismatch of records when merging data, and lost of records when processing data. The situations of missing data are also diverse, for example: in the same time of sampling, some data records at several sampling sites are partially or completely disappeared. On the contrary, partial or complete time series data are missing at the same sampling site. It is therefore obvious to see that the missing values of environmental monitoring data are both related to spatial and temporal dimensions. Currently the techniques of data imputation have been developed for certain types of data or the interpolation of missing values based on either geographic data distributions or time-series functions. To accommodate both spatial and temporal information in an analysis is rarely seen. The current study has been tried to integrate the related analysis procedures and develop a computing process using both spatial and temporal dimensions inherent in the environmental monitoring data. Such data imputation process can enhance the accuracy of estimated missing values.

Dense wavelength-division multiplexing (DWDM) technology are the provide solutions to increase the capacity of network. With the growth of using the OADM in DWDM system, it is more and more important to research the fault-locating fiber-link in-service supervisory technique for enhance the system reliability. Optical Time Domain Reflectometer (OTDR) is a popular tool to offer an in-service fault-locating of fiber link in fiber-optic transmission systems. But in the DWDM network, this technique is never be used for in-service supervisory application on the system. Are different OADM structures will affect the in-service OTDR monitoring? Since OTDR operates with high peak powers, the stimulated Raman scattering (SRS) effect in the conventional transmission fiber gives rise to power depletion of the data signal, and may degrade the bit-error-rate (BER) performance. In this work, we investigate the in-service 1.65-£gm OTDR monitoring supported FBG-based OADM structures. We improved FBG sandwiched between a pair of three-port optical circulator and multi-port optical circulator (MOC) FBG-based OADM to support OTDR monitoring, and research the technique of in-service OTDR monitoring for FBG-based, MZ-FBG based OADM system. The system bit-error-rate due to the OTDR monitoring a 10-Gb/s long (> 80 km) distance fiber link is examined. Negligible system power penalty, due to the OTDR monitoring, of both structures in 10 Gb/s dense wavelength division multiplexing (DWDM) link is achieved. That is mean the system with OTDR monitoring should have the in-service fault-location monitoring capability to enhance network reliability. We also investigate the in-service OTDR 1.65-£gm OTDR monitoring on the distributed Raman application system.