Browsing by Subject "Wavelet transform"
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Item Applications of TAP-NDE technique to non-contact ultrasonic inspection in tubulars(Texas A&M University, 2005-02-17) Baltazar-Lopez, Martin EduardoThe possibility and feasibility of experimental detection of localized defects in tubes using laser-induced ultrasonic wave approach through Thermo Acousto Photonic Non Destructive Evaluation (TAP-NDE) and Signal processing through wavelet transform is examined in this research. Guided waves in cylindrical surfaces provide solutions for detection of different defects in the material. Several experiments were conducted to this respect. Wave propagation in both axial and circumferential directions was studied. The dispersive wave propagation of ultrasonic waves in hollow cylinders has been investigated experimentally, primarily for use in non-contact and nondestructive inspections of pipes and tubes. The laser ultrasonic waves propagated in cylindrical waveguides are particularly attractive because of their unique characteristics in the applications of nondestructive evaluation (NDE). Contrary to studies making use of only axially symmetric guided waves in hollow cylinders, here are analyzed also nonaxisymmetric waves. The analysis of data is made by using the Gabor wavelet transform. The capability of modeling the guided wave dispersion in hollow cylinders is used in developing guided wave experimental techniques for flaw detection. Good agreement was obtained when comparing the dispersion spectra between theory and experimentation. Measurement of group velocities of guided waves, which are obtained directly from the wavelet transform coefficients, can be used to determine allocation and sizing of flaws.Item Development of an algorithm for detection and classification of capacitor switching events(2015-12) Furlani Bastos, Alvaro; Santoso, Surya; Baldick, RossShunt capacitor banks are widely used to improve power system operation by injecting reactive power into predominantly inductive systems. These banks may be continuously energized or switched according to the load levels. The primary goal of this work is to develop an algorithm for detection of capacitor switching events, both energizing and de-energizing. This identification allow us to assess the capacitor performance and detection of an unsuccessful energization, restrikes during the de-energizing operation, blown fuses, or even failed capacitors in one of the phases. The identification algorithms are developed based on the unique features associated to capacitor switching events, such as wavelet transform coefficients, voltage gradient at the switching instant, inrush current, steady-state voltage rise, and reactive power support. Moreover, a library with common range of values for these parameters is used to improve the algorithm accuracy. For each identified capacitor switching event, the following parameters are computed: peak voltage and current, voltage phase angle at the switching instant, duration and frequency of the transient, reactive power support in each phase, steady-state voltage rise, relative location of the switched bank, variation of power factor, voltage total harmonic distortion, and RMS line current. This capacitor switching identification module is tested with data from a power quality monitor, including different types of events. The results show that both energizing and de-energizing algorithms provide high accuracy levels. Moreover, using the scores assignment improves the performance of the capacitor energizing identification algorithm. As an application, these algorithms are used to evaluate the power factor over compensation in a distribution utility.Item Extraction of blade-vortex interactions from helicopter transient maneuvering noise(2014-05) Stephenson, James Harold; Tinney, Charles Edmund, 1975-Time-frequency analysis techniques are proposed as a necessary tool for the analysis of acoustics generated by helicopter transient maneuvering flight. Such techniques are necessary as the acoustic signals related to transient maneuvers are inherently unsteady. The wavelet transform is proposed as an appropriate tool, and it is compared to the more standard short-time Fourier transform technique through an investigation using several appropriately sized interrogation windows. It is shown that the wavelet transform provides a consistent spectral representation, regardless of employed window size. The short-time Fourier transform, however, provides spectral amplitudes that are highly dependent on the size of the interrogation window, and so is not an appropriate tool for this situation. An extraction method is also proposed to investigate blade-vortex interaction noise emitted during helicopter transient maneuvering flight. The extraction method allows for the investigation of blade-vortex interactions independent of other sound sources. The method is based on filtering the spectral data calculated through the wavelet transform technique. The filter identifies blade-vortex interactions through their high amplitude, high frequency impulsive content. The filtered wavelet coefficients are then inverse transformed to create a pressure signature solely related to blade-vortex interactions. This extraction technique, along with a prescribed wake model, is applied to experimental data extracted from three separate flight maneuvers performed by a Bell 430 helicopter. The maneuvers investigated include a steady level flight, fast- and medium-speed advancing side roll maneuvers. A sensitivity analysis is performed in order to determine the optimal tuning parameters employed by the filtering technique. For the cases studied, the optimized tuning parameters were shown to be frequencies above 7 main rotor harmonics, and amplitudes stronger than 25% (−6 dB) of the energy in the main rotor harmonic. Further, it is shown that blade-vortex interactions can be accurately extracted so long as the blade-vortex interaction peak energy signal is greater or equal to the energy in the main rotor harmonic. An in-depth investigation of the changes in the blade-vortex interaction signal during transient advancing side roll maneuvers is then conducted. It is shown that the sound pressure level related to blade-vortex interactions, shifts from the advancing side, to the retreating side of the vehicle during roll entry. This shift is predicted adequately by the prescribed wake model. However, the prescribed wake model is shown to be inadequate for the prediction of blade-vortex interaction miss distance, as it does not respond to the roll rate of the vehicle. It is further shown that the sound pressure levels are positively linked to the roll rate of the vehicle. Similar sound pressure level directivities and amplitudes can be seen when vehicle roll rates are comparable. The extraction method is shown to perform admirably throughout each maneuver. One limitation with the technique is identified, and a proposal to mitigate its effects is made. The limitation occurs when the main rotor harmonic energy drops below an arbitrary threshold. When this happens, a decreased spectral amplitude is required for filtering; which leads to the extraction of high frequency noise unrelated to blade-vortex interactions. It is shown, however, that this occurs only when there are no blade-vortex interactions present. Further, the resulting sound pressure level is identifiable as it is significantly less than the peak blade-vortex interaction sound pressure level. Thus the effects of this limitation are shown to be negligible.Item Fabric wrinkle characterization and classification using modified wavelet coefficients and support-vector-machine classifiers(2012-05) Sun, Jingjing; Xu, Bugao; Reed, Julia A.Wrinkling caused in wearing and laundry procedures is one of the most important performance properties of a fabric. Visual examination performed by trained experts is a routine wrinkle evaluation method in textile industry, however, this subjective evaluation is time-consuming. The need for objective, automatic and efficient methods of wrinkle evaluation has been increasing remarkably in recent years. In the present thesis, a wavelet transform based imaging analysis method was developed to measure the 2D fabric surface data captured by an infrared imaging system. After decomposing the fabric image by the Haar wavelet transform algorithm, five parameters were defined based on modified wavelet coefficients to describe wrinkling features, such as orientation, hardness, density and contrast. The wrinkle parameters provide useful information for textile, appliance, and detergent manufactures who study wrinkling behaviors of fabrics. A Support-Vector-Machine based classification scheme was developed for automatic wrinkle rating. Both linear kernel and radial-basis-function (RBF) kernel functions were used to achieve a higher rating accuracy. The effectiveness of this evaluation method was tested by 300 images of five selected fabric types with different fiber contents, weave structures, colors and laundering cycles. The results show agreement between the proposed wavelet-based automatic assessment and experts’ visual ratings.Item Fast and low memory usage coding for image and video based on wavelet transform(Texas Tech University, 2007-05) Ye, Linning; Nutter, Brian; Mitra, Sunanda; Seshaiyer, Padmanabhan; Karp, TanjaA new video codec based on three-dimensional wavelet subband coding with 3-D BCWT is presented. This new video codec has almost identical PSNR performance to the well-known 3-D SPIHT video codec. However, it is much more computationally efficient and uses much less internal memory than 3-D SPIHT. Implementation results of 3-D BCWT show that it can achieve real time decoding with strictly software implementation on a PC. Application of the 3-D BCWT algorithm to volumetric medical images shows that it can also achieve good performance. Although the BCWT algorithm itself uses much less memory than the SPIHT algorithm, the total system memory usage in BCWT coding is still high due to the large memory consumption of the wavelet transform. In this dissertation, the line-based BCWT algorithm is also presented, which utilizes the line-based wavelet transform to achieve BCWT coding. Due to the backward coding feature of the BCWT algorithm, the line-based BCWT algorithm can significantly reduce the overall system memory usage. Depending upon the image size, the memory usage of the line-based BCWT algorithm can be less than 1% of the memory usage of the SPIHT algorithm. Compared with the original BCWT algorithm, the line-based BCWT algorithm can use less than 2% of the memory that the BCWT algorithm consumes, thus making this algorithm extremely suitable for implementation on resource-limited platforms.Item Seismic Analysis Using Wavelet Transform for Hydrocarbon Detection(2012-02-14) Cai, RuiMany hydrocarbon detection techniques have been developed for decades and one of the most efficient techniques for hydrocarbon exploration in recent years is well known as amplitude versus offset analysis (AVO). However, AVO analysis does not always result in successful hydrocarbon finds because abnormal seismic amplitude variations can sometimes be caused by other factors, such as alternative lithology and residual hydrocarbons in certain depositional environments. Furthermore, not all gas fields are associated with obvious AVO anomalies. Therefore, new techniques should be applied to combine with AVO for hydrocarbon detection. In my thesis, I, through case studies, intend to investigate and validate the wave decomposition technique as a new tool for hydrocarbon detection which decomposes seismic wave into different frequency contents and may help identify better the amplitude anomalies associated with hydrocarbon occurrence for each frequency due to seismic attenuation. The wavelet decomposition analysis technique has been applied in two geological settings in my study: clastic reservoir and carbonate reservoir. Results from both cases indicate that the wavelet decomposition analysis technique can be used for hydrocarbon detection effectively if the seismic data quality is good. This technique can be directly applied to the processed 2D and 3D pre-stack/post-stack data sets (1) to detect hydrocarbon zones in both clastic and carbonate reservoirs by analyzing the low frequency signals in the decomposed domain and (2) to identify thin beds by analyzing the high frequency signals in the decomposed domain. In favorable cases, the method may possibly help separate oil from water in high-porosity and high-permeability carbonate reservoirs deeply buried underground. Therefore, the wavelet analysis would be a powerful tool to assist geological interpretation and to reduce risk for hydrocarbon exploration.