Browsing by Subject "Fault Diagnosis"
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Item Advanced fault diagnosis techniques and their role in preventing cascading blackouts(Texas A&M University, 2007-04-25) Zhang, NanThis dissertation studied new transmission line fault diagnosis approaches using new technologies and proposed a scheme to apply those techniques in preventing and mitigating cascading blackouts. The new fault diagnosis approaches are based on two time-domain techniques: neural network based, and synchronized sampling based. For a neural network based fault diagnosis approach, a specially designed fuzzy Adaptive Resonance Theory (ART) neural network algorithm was used. Several ap- plication issues were solved by coordinating multiple neural networks and improving the feature extraction method. A new boundary protection scheme was designed by using a wavelet transform and fuzzy ART neural network. By extracting the fault gen- erated high frequency signal, the new scheme can solve the difficulty of the traditional method to differentiate the internal faults from the external using one end transmis- sion line data only. The fault diagnosis based on synchronized sampling utilizes the Global Positioning System of satellites to synchronize data samples from the two ends of the transmission line. The effort has been made to extend the fault location scheme to a complete fault detection, classification and location scheme. Without an extra data requirement, the new approach enhances the functions of fault diagnosis and improves the performance. Two fault diagnosis techniques using neural network and synchronized sampling are combined as an integrated real time fault analysis tool to be used as a reference of traditional protective relay. They work with an event analysis tool based on event tree analysis (ETA) in a proposed local relay monitoring tool. An interactive monitoring and control scheme for preventing and mitigating cascading blackouts is proposed. The local relay monitoring tool was coordinated with the system-wide monitoring and control tool to enable a better understanding of the system disturbances. Case studies were presented to demonstrate the proposed scheme. An improved simulation software using MATLAB and EMTP/ATP was devel- oped to study the proposed fault diagnosis techniques. Comprehensive performance studies were implemented and the test results validated the enhanced performance of the proposed approaches over the traditional fault diagnosis performed by the transmission line distance relay.Item Broken Bar Detection in Synchronous Machines Based Wind Energy Conversion System(2012-10-19) Rahimian, Mina MashhadiElectrical machines are subject to different types of failures. Early detection of the incipient faults and fast maintenance may prevent costly consequences. Fault diagnosis of wind turbine is especially important because they are situated at extremely high towers and therefore inaccessible. For offshore plants, bad weather can prevent any repair actions for several weeks. In some of the new wind turbines synchronous generators are used and directly connected to the grid without the need of power converters. Despite intensive research efforts directed at rotor fault diagnosis in induction machines, the research work pertinent to damper winding failure of synchronous machines is very limited. This dissertation is concerned with the in-depth study of damper winding failure and its traceable symptoms in different machine signals and parameters. First, a model of a synchronous machine with damper winding based on the winding function approach is presented. Next, simulation and experimental results are presented and discussed. A specially designed inside-out synchronous machine with a damper winding is employed for the experimental setup. Finally, a novel analytical method is developed to predict the behavior of the left sideband amplitude for different numbers and locations of the broken bars. This analysis is based on the magnetic field theory and the unbalanced multiphase circuits. It is found that due to the asymmetrical structure of damper winding, the left sideband component in the stator current spectrum of the synchronous machine during steady state asynchronous operation is not similar to that of the induction machine with broken bars. As a result, the motor current signature analysis (MCSA) for detection rotor failures in the induction machine is usable to detect broken damper bars in synchronous machines. However, a novel intelligent-systems based approach is developed that can identify the severity of the damper winding failure. This approach potentially can be used in a non-invasive condition monitoring system to monitor the deterioration of a synchronous motor damper winding as the number of broken bars increase over time. Some other informative features such as speed spectrum, transient time, torque-speed curve and rotor slip are also found for damper winding diagnosis.Item Development of New Whole Building Fault Detection and Diagnosis Techniques for Commissioning Persistence(2012-12-07) Lin, GuanjingCommercial building owners spent $167 billion for energy in 2006. Building commissioning services have proven to be successful in saving building energy consumption. However, the optimal energy performance obtained by commissioning may subsequently degrade. The persistence of savings is of significant interest. For commissioning persistence, two statistical approaches, Days Exceeding Threshold-Date (DET-Date) method and Days Exceeding Threshold-Outside Air Temperature (DET-Toa) method, are developed to detect abnormal whole building energy consumption, and two approaches called Cosine Similarity method and Euclidean Distance Similarity method are developed to isolate the possible fault reasons. The effectiveness of these approaches is demonstrated and compared through tests in simulation and real buildings. The impacts of the factors including calibrated simulation model accuracy, fault severity, the time of fault occurrence, reference control change magnitude setting, and fault period length are addressed in the sensitivity study. The study shows that the DET-Toa method and the Cosine Similarity method are superior and more useful for the whole building fault detection and diagnosis.Item Use of the continuous wavelet tranform to enhance early diagnosis of incipient faults in rotating element bearings(2009-05-15) Weatherwax, Scott EricThis thesis focused on developing a new wavelet for use with the continuous wavelet transform, a new detection method and two de-noising algorithms for rolling element bearing fault signals. The work is based on the continuous wavelet transform and implements a unique Fourier Series estimation algorithm that allows for least squares estimation of arbitrary frequency components of a signal. The final results of the research also included use of the developed detection algorithm for a novel method of estimating the center frequency and bandwidth for use with the industry standard detection algorithm, envelope demodulation, based on actual fault data. Finally, the algorithms and wavelets developed in this paper were tested against seven other wavelet based de-noising algorithms and shown to be superior for the de-noising and detection of inner and outer rolling element race faults.