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Full-Text Articles in Engineering

Automatic Multi-Frequency Rotating-Probe Eddy-Current Data Analysis , Ping Xiang Jan 2005

Automatic Multi-Frequency Rotating-Probe Eddy-Current Data Analysis , Ping Xiang

Retrospective Theses and Dissertations

An automatic scheme for analyzing multi-frequency rotating-probe eddy-current data is proposed herein. This system integrates signal/image-processing algorithm with pattern recognition methods for accomplishing the objectives. The eddy current signals are acquired from several kinds of frequency multiplexed eddy-current rotating-probes. The problem involves the detection of the flaw signals, classifying the defect format and sizing/characterizing the defect profile. The preprocessing steps include conversion of one-dimensional data to obtain a two-dimensional image, removing background noise, suppressing structure-masking signals, and calibration. Optimal thresholding of calibrated signal based on probability of detection (POD) concepts are discussed in detail. Feature extraction and signal ...


Applications Of Pod Studies And Robust Design To Electromagnetic Nde , Zhiwei Zeng Jan 2003

Applications Of Pod Studies And Robust Design To Electromagnetic Nde , Zhiwei Zeng

Retrospective Theses and Dissertations

Numerical techniques, such as finite element methods (FEM), have been widely used in predicting defect signatures in nondestructive evaluation (NDE). The test conditions in the numerical models are deterministic in nature. However, signals generated by identical flaws are usually different under practical testing conditions. This affects the reliability of NDE methods. A considerable amount of attention has been focused towards quantifying the reliability of a variety of NDE methods, which has led to development of models for evaluating probability of detection (POD). Sources of variabilities that influence POD in NDE systems vary due to different testing modalities. POD models not ...


Neural Network Based Iterative Algorithms For Solving Electromagnetic Nde Inverse Problems , Pradeep Ramuhalli Jan 2002

Neural Network Based Iterative Algorithms For Solving Electromagnetic Nde Inverse Problems , Pradeep Ramuhalli

Retrospective Theses and Dissertations

The solution of inverse problems is of interest in a variety of applications ranging from geophysical exploration to medical diagnosis and non-destructive evaluation (NDE). Electromagnetic methods are often used in the nondestructive inspection of conducting and ferromagnetic materials. A crucial problem in electromagnetic NDE is signal inversion wherein the defect parameters must be recovered from the measured signals. Iterative algorithms are commonly used to solve this inverse problem. Typical iterative inversion approaches use a numerical forward model to predict the measurement signal for a given defect profile. The desired defect profile can then be found by iteratively minimizing a cost ...


Finite Element And Meshless Methods In Ndt Applications , Liang Xuan Jan 2002

Finite Element And Meshless Methods In Ndt Applications , Liang Xuan

Retrospective Theses and Dissertations

Eddy current nondestructive testing (NDT) methods are extensively used in the inspection of aging aircrafts. Thousands of fasteners and bonded joints on each aircraft should be inspected and in order to handle the huge task, fast, accurate and cost effective inspection methods are clearly needed. Some of the challenges encountered in eddy current testing are (1) detection of corrosions or cracks in the multi-layer structures, (2) detection of cracks under the fastener (CUF), (3) detection of surface and subsurface defects close to edges.;Conventional eddy current inspection method is time consuming due to the small probe size and large inspection ...


A Novel Approach To The Classification Of Ultrasonic Nde Signals , Daewon Kim Jan 2002

A Novel Approach To The Classification Of Ultrasonic Nde Signals , Daewon Kim

Retrospective Theses and Dissertations

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature space. This thesis describes an alternative approach which uses the least mean square (LMS) method to determine the coordinates of the ultrasonic probe followed by the use of a synthetic ...


Remote Field Eddy Current Probes For The Detection Of Stress Corrosion Cracks In Transmission Pipelines , Plamen Alexandrov Ivanov Jan 2002

Remote Field Eddy Current Probes For The Detection Of Stress Corrosion Cracks In Transmission Pipelines , Plamen Alexandrov Ivanov

Retrospective Theses and Dissertations

Magnetic flux leakage (MFL) is a technique used widely in non-destructive testing (NDT) of natural gas and petroleum transmission pipelines. This inspection method relies on magnetizing the pipe-wall in axial direction. The MFL inspection tool is equipped with an array of Hall sensors located around the circumference of the pipe, which registers the flux leakage caused by any defects present in the pipe-wall. In general, the tool is constructed such that the magnetization occurs in axial direction as a result of which this method is not sensitive to axially oriented defects.;One type of defect, which is of a growing ...


Adaptive Multicoding And Robust Linear-Quadratic Receivers For Uncertain Cdma Frequency-Selective Fading Channels , Jianjun Ni Jan 2002

Adaptive Multicoding And Robust Linear-Quadratic Receivers For Uncertain Cdma Frequency-Selective Fading Channels , Jianjun Ni

Retrospective Theses and Dissertations

Wideband Code Division Multiple Access (WCDMA) communications in the presence of channel uncertainty poses a challenging problem with many practical applications in the wireless communications filed. In this dissertation, robust linear-quadratic (LQ) receivers for time-varying, frequency-selective CDMA channels in the presence of uncertainty regarding instantaneous channel state information are proposed and studied. In order to enhance the performance of the LQ receivers, a novel modulation technique adaptive multicoding is employed. We proposed a simple, intuitively appealing cost function the modified deflection ratio that can be maximized to find signal constellations and associated LQ receivers that are optimal in a certain ...


Data Fusion For Nde Signal Characterization , Jaein Lim Jan 2001

Data Fusion For Nde Signal Characterization , Jaein Lim

Retrospective Theses and Dissertations

The primary objective of multi-sensor data fusion, which offers both quantitative and qualitative benefits, is to be able to draw inferences that may not be feasible with data from a single sensor alone. In this study, data from two sets of sensors are fused to estimate the defect profile from magnetic flux leakage (MFL) inspection data. The two sensors measure the axial and circumferential components of the MFL field. Data is fused at the signal level. The two signals are combined as the real and imaginary components of a complex valued signal. Signals from an array of sensors are arranged ...


3-D Defect Profile Reconstruction From Magnetic Flux Leakage Signatures Using Wavelet Basis Function Neural Networks , Kyungtae Hwang Jan 2000

3-D Defect Profile Reconstruction From Magnetic Flux Leakage Signatures Using Wavelet Basis Function Neural Networks , Kyungtae Hwang

Retrospective Theses and Dissertations

The most popular technique for inspecting natural gas pipelines involves the use of magnetic flux leakage (MFL) methods. The measured MFL signal is interpreted to obtain information concerning the structural integrity of the pipe. Defect characterization involves the task of calculating the shape and size of defects based on the information contained in the signal. An accurate estimate of the defect profile allows assessment of the safe operating pressure of the pipe. Artificial neural networks (ANNs) have been employed for characterizing defects in the past. However, conventional neural networks such as radial basis function neural networks are not always suitable ...


Multistage Adaptive Noise Cancellation And Multi-Dimensional Signal Processing For Ultrasonic Nondestructive Evaluation , Jae-Joon Kim Jan 2000

Multistage Adaptive Noise Cancellation And Multi-Dimensional Signal Processing For Ultrasonic Nondestructive Evaluation , Jae-Joon Kim

Retrospective Theses and Dissertations

Ultrasonic signal processing presents several challenges with respect to both noise removal and interpretation. The interference of unwanted reflections from material grain structure can render the data extremely noisy and mask the detection of small flaws. It is therefore imperative to separate the flaw reflections from grain noise. The interpretation or classification of ultrasonic signals in general is relatively difficult due to the complexity of the physical process and similarity of signals from various classes of reflectors;Adaptive noise cancellation techniques are ideally suited for reducing spatially varying noise due to the grain structure of material in ultrasonic nondestructive evaluation ...


Image Analysis Using Multiscale Boundary Extraction Algorithm , Nawapak Eua-Anant Jan 2000

Image Analysis Using Multiscale Boundary Extraction Algorithm , Nawapak Eua-Anant

Retrospective Theses and Dissertations

The complete analysis and interpretation of the information in image data is a complex process. This dissertation presents 3 major contributions to image analysis, namely, global multiscale detection, local scale analysis, and boundary extraction. Global scale analysis is related to identification of the various scales presented in the image. A new approach for global scale analysis is developed based on the differential power spectrum normalized variance ratio (DPSNVR). The DPSNVR is the ratio of the second order normalized central moment of the power spectrum of the image to that of the multiscale differential mask. Local maxima in DPSNVR graph directly ...


Texture Representation Using Wavelet Filterbanks , Nam-Deuk Kim Jan 2000

Texture Representation Using Wavelet Filterbanks , Nam-Deuk Kim

Retrospective Theses and Dissertations

Texture analysis is a fundamental issue in image analysis and computer vision. While considerable research has been carried out in the texture analysis domain, problems relating to texture representation have been addressed only partially and active research is continuing. The vast majority of algorithms for texture analysis make either an explicit or implicit assumption that all images are captured under the same measurement conditions, such as orientation and illumination. These assumptions are often unrealistic in many practical applications;This dissertation addresses the viewpoint-invariance problem in texture classification by introducing a rotated wavelet filterbank. The proposed filterbank, in conjunction with a ...


Wavelet Based Multiresolution Zero-Crossing Representations , Muhammad Akbar Khan Afzal Jan 2000

Wavelet Based Multiresolution Zero-Crossing Representations , Muhammad Akbar Khan Afzal

Retrospective Theses and Dissertations

This research proposes a new signal representation based an multiscale zero-crossings of the signal. It is shown that the original signal is uniquely characterized by its zero-crossing representation. The representation is insensitive to translation of the input signal. In this approach, the zero-crossing information is supplemented with the first moment of the signal to stabilize the representation. This technique, initially suggested by others for wavelet transform zero-crossings, results in a method for reconstructing the original signal from its multiscale zero-crossings. The signal recovery algorithm is fast and efficient, and suggests completeness of the representation. The representation has been successfully applied ...


The Separation Of Multiple Mutually Interfering Fm Signals And The Use Of Predistortion To Compensate For Nonlinear Rf Amplifiers , Sven Anders Mattsson Jan 1999

The Separation Of Multiple Mutually Interfering Fm Signals And The Use Of Predistortion To Compensate For Nonlinear Rf Amplifiers , Sven Anders Mattsson

Retrospective Theses and Dissertations

This thesis covers two fairly different topics, separation of multiple FM signals, emphasizing on the case of three FM signals, and pre-distortion for compensation of non-linear amplifiers. The thesis shows that given a received signals that is the sum of three or more interfering FM signals whose phases are bandlimited, there is strong reasons to believe that there is unique solution. I.e., it is probably not possible for any other FM signals that are bandlimited to add to the same received signal. The research also shows that the solution is stable, a small error will not cause a divergence ...


Interference Suppression For Ds/Cdma Systems In Non-Gaussian Impulsive Channels , Seoyoung Lee Jan 1998

Interference Suppression For Ds/Cdma Systems In Non-Gaussian Impulsive Channels , Seoyoung Lee

Retrospective Theses and Dissertations

Multiple-access interference (MAI) suppression techniques in DS/CDMA systems usually assume additive Gaussian noise. Minimum mean squared error (MMSE) detectors are near-far resistant in additive Gaussian noise channels. But the additive channel noise in many communication channels is often non-Gaussian and impulsive. Signal detection in non-Gaussian impulsive noise is traditionally focused on single-user channels. Symmetric alpha-stable (S[alpha] S) probability density functions can accurately model large classes of impulsive noise. The MMSE performance criterion cannot be used for S[alpha] S processes with 0<[alpha]<2 since they have infinite variance. This dissertation considers the problems of MAI suppression for DS/CDMA systems in the presence of additive non-Gaussian impulsive channel noise modeled as a S[alpha] S process with 1<[alpha]<2. These MAI suppression techniques help combat the near-far problem. First, the minimum dispersion (MD) criterion is introduced to suppress MAI. Linear MD detection can be viewed as expansion of the concept of the MMSE detection for Gaussian multiple-access channels to S[alpha] S non-Gaussian impulsive multiple-access channels. The linear MD detector is implemented adaptively using least mean p-norm (LMP) algorithm. The performance of the linear MD detector is analyzed in the context of a S[alpha] S process. Simulation results indicate that the adaptive MD detector shows good near-far resistance. Next, this dissertation presents a MRI suppression method using the least Lp-norm criterion. The iteratively reweighted least squares (IRLS) algorithm recursively approximates the least Lp-norm solution from weighted normal equations. Simulation results show that the proposed detector provides remarkable performance improvements over the adaptive MD detector in a wide range of near-far situations. The proposed detector has much better near-far resistance than the adaptive MD detector. Finally, fuzzy hybrid detector combines the adaptive MD detector and the hard-limiting matched filter (HLMF) detector. The HLMF detector performs well when the additive impulsive noise significantly dominates over MAI. Simulation results indicate significant performance improvements over the adaptive MD detector alone in impulsive noise-limited environments. When MAI dominates, the fuzzy hybrid detector nearly has the same performance as the adaptive MD detector.


Eddy Current Automatic Flaw Detection System For Heat Exchanger Tubes In Steam Generators , Sheng-Fa Chuang Jan 1997

Eddy Current Automatic Flaw Detection System For Heat Exchanger Tubes In Steam Generators , Sheng-Fa Chuang

Retrospective Theses and Dissertations

In this dissertation we present an automatic flaw detection system for heat exchanger tubes in steam generators. The system utilizes two well-known techniques, wavelets and fuzzy logic, to automatically detect the flaws in tubing data. The analysis of eddy current inspection data is a difficult task which requires intensive labor by experienced human analysts. To aid the analysts, an accurate and consistent automatic data analysis package was developed. The software development is divided into three parts: data preprocessing, wavelet analysis, and a fuzzy inference system. The data preprocessing procedure is used to set up a signal analysis standard for different ...


Adaptive Iir Filtering Using The Homotopy Continuation Method , Sangmin Bae Jan 1997

Adaptive Iir Filtering Using The Homotopy Continuation Method , Sangmin Bae

Retrospective Theses and Dissertations

The objective of this study is to develop an algorithmic approach for solving problems associated with the convergence to the local minima in adaptive IIR filtering. The approach is based on a numerical method called the homotopy continuation method;The homotopy continuation method is a "solution exhaustive method" for calculating all solutions of a set of nonlinear equations. The globally optimum filter coefficients correspond to the solutions with minimum mean square error. In order to apply the technique to the adaptive IIR filtering problem, the homotopy continuation method is modified to handle a set of nonlinear polynomials with time-varying coefficients ...


Nde Data Fusion Using Morphological Approaches , Young-Won Song Jan 1997

Nde Data Fusion Using Morphological Approaches , Young-Won Song

Retrospective Theses and Dissertations

The objective of most data fusion algorithms is to combine information made available by various sensors synergistically in order to enhance the overall level of information. Since information obtained from data sources such as sensors is often incomplete or imprecise in nature, the application of data fusion techniques has evoked interest in a number of fields ranging from robotics to nondestructive evaluation (NDE). In NDE applications, such techniques can be used to integrate and fuse data obtained using multiple inspection modalities to produce a more comprehensive picture of the condition of the test specimen. As an example, ultrasonic and eddy ...


Advanced Eddy-Current Methods For Quantitative Nde , Cheng-Chi Tai Jan 1997

Advanced Eddy-Current Methods For Quantitative Nde , Cheng-Chi Tai

Retrospective Theses and Dissertations

The objectives of this dissertation were to devise and develop advanced eddy-current methods for quantitative NDE. The techniques used include time-domain methods (pulsed eddy current), frequency-domain methods (swept-frequency eddy current), and the photoinductive imaging method that combines eddy-current and laser-based thermal-wave techniques. We first developed theoretical models to predict the pulsed eddy current signal and showed this technique can be used to characterize metallic coatings on metal substrates. A feature-based rapid inversion method was developed to determine the conductivity and thickness of the coating simultaneously. In the second work, we studied the fundamentals of eddy current interactions with magnetic metals ...


Signal Processing And Image Restoration Techniques For Two-Dimensional Eddy Current Nondestructive Evaluation , Bing Wang Jan 1997

Signal Processing And Image Restoration Techniques For Two-Dimensional Eddy Current Nondestructive Evaluation , Bing Wang

Retrospective Theses and Dissertations

This dissertation presents a comprehensive study on the forward modeling methods, signal processing techniques, and image restoration techniques for two-dimensional eddy current nondestructive evaluation. The basic physical forward method adopted in this study is the volume integral method. We have applied this model to the eddy current modeling problem for half space geometry and thin plate geometry. To reduce the computational complexity of the volume integral method, we have developed a wavelet expansion method which utilizes the multiresolution compression capability of the wavelet basis to greatly reduce the amount of computation with small loss in accuracy. To further improve the ...


Diffraction-Corrected Synthetic Aperture Focusing For Spherical Ultrasonic Radiators , Wassef Munther Masri Jan 1997

Diffraction-Corrected Synthetic Aperture Focusing For Spherical Ultrasonic Radiators , Wassef Munther Masri

Retrospective Theses and Dissertations

Synthetic Aperture Focusing Techniques (SAFT) represent a special class of beam-steering algorithms. They are employed to improve the signal-to-noise ratio (SNR) and resolution of ultrasonic images. Such techniques have traditionally been implemented assuming a geometrical model that neglects the effects of diffraction. This dissertation accounts for diffraction effects by using an analytical model based on the Rayleigh-Sommerfeld formula. The model has been extended to characterize the acoustic fields in an immersed solid; a case frequently encountered in scanning acoustic microscopy applications. The results are then verified by comparing them with results obtained using a finite element model;The analytical model ...


Development And Application Of Spread-Spectrum Ultrasonic Evaluation Technique , Jahangir Khan Kayani Jan 1996

Development And Application Of Spread-Spectrum Ultrasonic Evaluation Technique , Jahangir Khan Kayani

Retrospective Theses and Dissertations

A new approach to ultrasonic NDE called spread-spectrum ultrasonic evaluation (SSUE) is investigated. It regards the ultrasonic nondestructive evaluation as an acoustic-impulse-response estimation and characterization problem. This problem has been compared with the analogous problems of radio-detection-and-ranging from communications field and the seismic exploration problem of geophysics. Out of the various options for the impulse response estimation, the continuous pseudorandom signal correlation method has been shown to be the optimum for peak-power limited systems such as the ultrasonic NDE systems. The problem of self-noise and its consequences in pseudorandom correlation systems is investigated, followed by the development of various optimum ...


Invariance Transformations For Processing Nde Signals , Shreekanth Ammanji Mandayam Jan 1996

Invariance Transformations For Processing Nde Signals , Shreekanth Ammanji Mandayam

Retrospective Theses and Dissertations

The ultimate objective in nondestructive evaluation (NDE) is the characterization of materials, on the basis of information in the response from energy/material interactions. This is commonly referred to as the "inverse problem." Inverse problems are in general ill-posed and full analytical solutions to these problems are seldom tractable. Pragmatic approaches for solving them employ a constrained search technique by limiting the space of all possible solutions. A more modest goal is therefore to use the received signal for characterizing defects in objects in terms of the location, size and shape. However, the NDE signal received by the sensors is ...


Projection Based Edge Recovery In Low Bit Rate Vector Quantizers , Ajai Narayan Jan 1996

Projection Based Edge Recovery In Low Bit Rate Vector Quantizers , Ajai Narayan

Retrospective Theses and Dissertations

Data compression is probably the single most important factor in every information service that is being visualized and proposed by engineers. The effectiveness of such services are dependent upon achievable compression of real time speech and video signals. Several approaches to signal encoding have been proposed and realized, each with its unique advantages and costs. Large compression ratios can only be achieved through lossy source encoding methods. One such method is Vector Quantization (VQ);The lossy nature of such encoders imply that the process of encoding is non invertible. At low bit rates, lossy compression with conventional decoders (realized as ...


Pattern Recognition And Image Processing Of Infrared Astronomical Satellite Images , Lun Xiong He Jan 1996

Pattern Recognition And Image Processing Of Infrared Astronomical Satellite Images , Lun Xiong He

Retrospective Theses and Dissertations

The Infrared Astronomical Satellite (IRAS) images with wavelengths of 60 [mu] m and 100 [mu] m contain mainly information on both extra-galactic sources and low-temperature interstellar media. The low-temperature interstellar media in the Milky Way impose a "cirrus" screen of IRAS images, especially in images with 100 [mu] m wavelength. This dissertation deals with the techniques of removing the "cirrus" clouds from the 100 [mu] m band in order to achieve accurate determinations of point sources and their intensities (fluxes). We employ an image filtering process which utilizes mathematical morphology and wavelet analysis as the key tools in removing the ...


Signal Estimation Using H [Infinity Sign] Criteria , Sanjeev Tavathia Jan 1996

Signal Estimation Using H [Infinity Sign] Criteria , Sanjeev Tavathia

Retrospective Theses and Dissertations

In many signal processing and communication (SPC) applications we require to estimate signal corrupted by channel and additive noise. Optimal linear filters and predictors are used to recover signal from given observed (corrupted) signal. Kalman and Wiener filters are commonly used as optimal filters. These filters minimize the mean square error (MSE) or variance of the output error. The minimization require exact knowledge of input signal and noise power spectral density (PSD). Therefore, the performance of Kalman or Wiener filters degrade if the input signal and noise statistics is changing with time and is not known a priori. In many ...


Blind Adaptive Near-Far Resistant Receivers For Ds/Cdma Multi-User Communication Systems , Sang Chul Park Jan 1996

Blind Adaptive Near-Far Resistant Receivers For Ds/Cdma Multi-User Communication Systems , Sang Chul Park

Retrospective Theses and Dissertations

Code-division multiple-access (CDMA) systems have multiple users that simultaneously share a common channel using pre-assigned signature waveforms. The conventional receiver suffers from the near-far problem when the received signal power of the desired user is weaker than those of the other users. Optimum and suboptimum multi-user detectors outperform the conventional receiver at the expense of a significant increase in complexity and need for side-information about interfering users. Complexity of these detectors may not be acceptable for many practical applications and communication security may restrict the distribution of all users' signature waveforms to all the receivers;For a single-user receiver, the ...


Image Fusion Using Multi-Resolution Decomposition And Lmmse Filter , Jaewon Yim Jan 1995

Image Fusion Using Multi-Resolution Decomposition And Lmmse Filter , Jaewon Yim

Retrospective Theses and Dissertations

The subject of data fusion utilizing heterogeneous sensors has received significant attention in recent years. Each of the sensors provides a limited perspective of the desired information. A heterogeneous sensor environment combined with a procedure for synergistically combining data from each of the transducers can potentially lead to a more comprehensive and accurate estimate of the desired information. An example of a field that can profit from the application of data fusion techniques is the area of nondestructive evaluation (NDE);This dissertation is concerned with developing efficient image fusion techniques for NDE applications. This dissertation begins with a brief description ...


Nde Data Fusion Using Phenomenological Approaches , Kai Sun Jan 1995

Nde Data Fusion Using Phenomenological Approaches , Kai Sun

Retrospective Theses and Dissertations

Data fusion techniques are beginning to attract considerable attention. In the NDE context, such techniques can be used to combine information from two or more NDE test methods to improve the probability of detection and enhance characterization results. An example of such an application involves the fusion of eddy current and ultrasonic NDE data. The eddy current phenomena relies on the diffusion process to propagate energy. Ultrasonic phenomena, in contrast, rely on wave propagation. The manner in which the energy interacts with the material under test is fundamentally different. It can therefore be argued that each test method provides a ...


Automated Image Inspection Using Wavelet Decomposition And Fuzzy Rule-Based Classifier , Zhong Zhang Jan 1995

Automated Image Inspection Using Wavelet Decomposition And Fuzzy Rule-Based Classifier , Zhong Zhang

Retrospective Theses and Dissertations

A general purpose image inspecting system has been developed for automatic flaw detection in industrial applications. The system has a general purpose image understanding architecture that performs local feature extraction and supervised classification. Local features of an image are extracted from the compactly supported wavelet transform of the image. The features extracted from the wavelet transform provide local harmonic analysis and multi-resolution representation of the image. Image segmentation is achieved by classifying image pixels based on features extracted within a local area near each pixel. The supervised classifier used in the segmentation process is a fuzzy rule-based classifier which is ...