This thesis is concerned with detection of transient signal families and detectors in nonlinear static sensor systems. The detection problems are treated within the framework of likelihood ratio based binary hypothesis testing. An analytical solution to the noncoherent detection problem is derived, which in contrast to the classical noncoherent detector, is optimal for wideband signals. An optimal detector for multiple transient signals with unknown arrival times is also derived and shown to yield higher detection performance compared to the classical approach based on the generalized likelihood ratio test. An application that is treated in some detail is that of ultrasonic nondestructive testing, particularly pulse-echo detection of defects in elastic solids. The defect detection problem is cast as a composite hypothesis test and a methodology, based on physical models, for designing statistically optimal detectors for cracks in elastic solids is presented. Detectors for defects with low computational complexity are also formulated based on a simple phenomenological model of the defect echoes. The performance of these detectors are compared with the physical model-based optimal detector and is shown to yield moderate performance degradation. Various aspects of optimal detection in static nonlinear sensor systems are also treated, in particular the stochastic resonance (SR) phenomenon which, in this context, implies noise enhanced detectability. Traditionally, SR has been quantified by means of the signal-to-noise ratio (SNR) and interpreted as an increase of a system's information processing capability. Instead of the SNR, rigorous information theoretic distance measures, which truly can support the claim of noise enhanced information processing capability, are proposed as quantifiers for SR. Optimal detectors are formulated for two static nonlinear sensor systems and shown to exhibit noise enhanced detectability.

Cold rolled carbon steel 1018C is widely used in pressurized fuel pipelines. For those structures, stress corrosion cracking (SCC) can pose a significant problem because cracks initiate late in the lifetime and often unexpectedly, but grow fast once they get started. To ensure a safe operation, it is crucial that any damage can be detected before the structural stability is reduced by large cracks. In the early stages of SCC, microstructural changes occur which increase the acoustic nonlinearity of the material. Therefore, an initially monochromatic Rayleigh wave is distorted and measurable higher harmonics are generated. Different levels of stress corrosion cracking is induced in five specimens. For each specimen, nonlinear ultrasonic measurements are performed before and after inducing the damage. For the measurements, oil coupled wedge transducers are used to generate and detect tone burst Rayleigh wave signals. The amplitudes of the received fundamental and second harmonic waves are measured at varying propagation distances to obtain a measure for the acoustic nonlinearity of the material. The results show a damage-dependent increase in nonlinearity for early stages of damage, indicating the suitability for this nonlinear ultrasonic method to detect stress corrosion cracking before structural failure.

An automated method in damage state assessment of reinforced concrete columns for the purpose of establishing a rapid and quantitative post-earthquake safety and structural evaluation procedure is proposed. Several techniques from the fields of computer vision and image processing are employed in order to develop a set of methods capable of automatically detecting spalled regions on the surface of reinforced concrete columns as well as the properties of cracks and spalled regions on these surfaces. The resulting properties of the observed visible damage on the reinforced concrete column surfaces are then utilized to automatically estimate the existing condition and safety of the column. The damage state is quantified according to the maximum drift capacity of the column. The methods proposed in this research were implemented in a Microsoft Visual Studio .NET environment, and tested on real images of damaged columns. The test results indicated that the methods could automatically detect spalled regions and retrieve the properties of spalling and cracks on reinforced concrete column surfaces in images or video frames, and further, that this retrieved information could be accurately translate to a meaningful assessment of the column's existing damage state in the form of the maximum drift capacity.

Esta Tesis Doctoral presenta un sistema automatizado de inspección no destructiva de materiales usando ultrasonidos para la detección de heterogeneidades en piezas metálicas, en concreto, de acero al carbono de tipo S275JR. Para ello, se han utilizado guías lineales que se han automatizado con motores paso a paso cuyos movimientos se controlan desde el computador, mediante una aplicación gráfica diseñada específicamente para este trabajo. Una vez detectados los defectos, se permite una posterior clasificación de los defectos según morfología, posición y tamaño con programas que utilizan algoritmos basados en Reconocimiento de Patrones. Tras su ejecución se obtienen los informes de resultados indicando la estimación de los datos buscados. / This Thesis presents an automated system to the inspection of materials using ultrasounds to the detection of heterogeneities in metallic pieces, in particular, carbon steel S275JR. For that, it used linear guides that have been automated with stepper motors, whose movements are controlled from the computer using a graphic application designed specifically to this research. When defects are detected, it allows the later classification of defects according to their morphology, size and position with programs that use algorithms based on Pattern Recognition. After execution of the programs, results reports provide an optimal estimation of expected data.

The impedance response of silicon carbide whisker-alumina composites is investigated utilizing novel stereological techniques along with a microstructural simulation. The stereological techniques developed allow for a measurement of the trivariate length, radius and orientation distribution of whiskers in the composite from measurements made on two-dimensional sectioning planes. The measured distributions are then utilized in a Monte Carlo simulation that predicts connectivity in the composite for a given volume fraction. It is assumed in the simulation that connectivity factors dominate the electrical response, not interfacial phenomena. The results of the simulation are compared with impedance spectra taken from real samples, and conclusions are drawn regarding the nature of the impedance response.

The objective of this research is to develop a bearing fault detection scheme for electric machines via stator current. A new method, called the stator current noise cancellation method, is proposed to separate bearing fault-related components in the stator current. This method is based on the concept of viewing all bearing-unrelated components as noise and defining the bearing detection problem as a low signal-to-noise ratio (SNR) problem. In this method, a noise cancellation algorithm based on Wiener filtering is employed to solve the problem. Furthermore, a statistical method is proposed to process the data of noise-cancelled stator current, which enables bearing conditions to be evaluated solely based on stator current measurements. A detailed theoretical analysis of the proposed methods is presented. Several online tests are also performed in this research to validate the proposed methods. It is shown in this work that a bearing fault can be detected by measuring the variation of the RMS of noise-cancelled stator current by using statistical methods such as the Statistical Process Control. In contrast to most existing current monitoring techniques, the detection methods proposed in this research are designed to detect generalized-roughness bearing faults. In addition, the information about machine parameters and bearing dimensions are not required in the implementation.

The measurement and monitoring of the elastic properties of cement-based materials is very important for assessing their quality, integrity and performance. Due to the nonhomogeneous and time-dependent characteristics of these materials, it is difficult to observe the developments in elastic properties with traditional destructive methods. The aim of this thesis is to determine and monitor elastic properties of mortar specimens made with different cements by using resonant frequency and ultrasonic pulse velocity test methods, and to obtain relationships between these elastic properties. For this purpose, eight different cement mortar mixtures were prepared with different constituent CEM I cements. Dynamic elastic moduli, static elastic moduli, dynamic Poisson&rsquo / s ratio and strength of these mixtures were observed for different ages. The relationships between these elastic properties are determined and the results obtained from two different nondestructive test methods are compared. Although nondestructive tests made it possible to obtain elastic properties of mortar mixtures, the results revealed that it is very difficult to develop a single relationship between different elastic properties of mortars with varying mixture proportions. This situation is mainly due to the anisotropy and nonlinear behavior of the mortar and the difficulty of describing the actual behavior of mortar by formulations defined for perfectly elastic materials.

Gas Metal Arc Welding (GMAW) is one of the main methods used to join structural members. One of the largest challenges involved in production of welds is ensuring the quality of the weld. One of the main factors attributing to weld quality is penetration depth. Automatic control of the welding process requires non-contact, non-destructive sensors that can operate in the presence of high temperatures and electrical noise found in the welding environment. Inspection using laser generation and electromagnetic acoustic transducer (EMAT) reception of ultrasound was found to satisfy these conditions. Using this technique, the time of flight of the ultrasonic wave is measured and used to calculate penetration depth. Previous works have shown that penetration depth measurement performance is drastically reduced when performed during welding. This work seeks to realize in-process penetration depth measurement by compensating for errors caused by elevated temperature. Neuro-fuzzy models are developed that predict penetration depth based on in-process time of flight measurements and the welding process input. Two scenarios are considered in which destructive penetration depth measurements are or are not available for model training. Results show the two scenarios are successful. When destructive measurements are unavailable, model error is comparable to that of offline ultrasonic measurements. When destructive measurements are available, measurement error is reduced by 50% compared to offline ultrasonic measurements. The two models can be effectively applied to permit in-process penetration depth measurements for the purpose of real-time monitoring and control. This will reduce material, production time, and labor costs and increase the quality of welded parts.

This research deals with the second harmonic generation of Lamb waves in nonlinear elastic, homogeneous, isotropic plates. These waves find current applications in the field of ultrasonic, nondestructive testing and evaluation of materials. The second harmonic Lamb wave generation is investigated analytically in order to provide information on suitable excitation modes maximizing the second harmonic amplitude. Using an existing solution for the problem of second harmonic generation in wave guides, the solution is explained for the plate and examined as to the symmetry properties of the second harmonic wave, since published results are contradictory. It is shown that the cross-modal generation of a symmetric secondary mode by an antisymmetric primary mode is possible. Modes showing internal resonance, whose conditions are nonzero power flux from the primary wave and phase velocity matching, are shown to be most useful for measurements. In addition, group velocity matching is required. A material-independent analysis of the linear Lamb mode theory provides mode types satisfying all three requirements. Using the example of an aluminum plate, the found internally resonant modes are evaluated with regard to the rate of second harmonic generation and practical issues such as excitability and ease of measurement. Pros and cons of each mode type are presented.

The employment of real time NDT systems has been spread widely last years. It is very important to control in real-time layer thicknesses of multi-layered materials during manufacturing process. In this work multi-layer thickness measurement digital signal processing methods are evaluated. Presented real-time nondestructive testing system and signal propagation model is a background for measurement algorithm analysis and development. In this work multi-layer thickness measurement problem is addressed with a different approach, by applying correlation functions on parts of the ultrasonic signal, thus reducing the overall computational complexity.