Crack detection in hollow section structures through coupled response measurements

Detection of a circumferential crack in a hollow section beam is investigated using coupled response measurements. The crack section is represented by a local flexibility matrix connecting two undamaged beam segments. This matrix defines the relationship between the displacements and forces across the crack section and is derived by applying fundamental fracture mechanics theory. The suitability of the mode coupling methodology is first demonstrated analytically. Laboratory test results are then presented for circular hollow section beams with artificially generated cracks of varying severity. It is shown that this method has the potential as a damage detection tool for mechanical structures. (C) 2002 Elsevier Science Ltd. All rights reserved.

Crack detection in welded mechanical structures using coupled vibrations

Detection of a fatigue crack in a welded frame structure is studied in this paper using coupled response measurements. Similarity to real engineering structures is maintained in the fabrication of the test frame with hollow section chords and branch members. The fatigue crack was created by a special reciprocating mechanism that generates cyclic stress on a beam member of the structure. The methodology of coupled response measurements is first demonstrated on a single hollow section beam by analytical simulation and experimental validation. The issues of using this approach for fatigue crack detection in real structures are then examined. Finally, the experimental results of the frame under different scenarioes are presented. The existence of the crack is clearly observable from the FRF plots. It is suggested that this approach offers the potential to detect cracks in welded frame structures and is a useful tool for routine maintenance work and health assessment.

Experimental damage detection using system norms

Nowadays there is great interest in structural damage detection in systems using nondestructive tests. Once the failure is detected, as for instance a crack, it is possible to take providences. There are several different approaches that can be used to obtain information about the existence, location and extension of the fault in the system by non-destructive tests. Among these methodologies, one can mention different optimization techniques, as for instance classical methods, genetic algorithms, neural networks, etc. Most of these techniques, which are based on element-byelement adjustments of a finite element (FE) model, take advantage of the dynamic behavior of the model. However, in practical situations, usually, is almost impossible to obtain an accuracy model. In this paper, it is proposed an experimental technique for damage location. This technique is based on H: norm to obtain the damage location. The dynamic properties of the structure were identified using experimental data by eigensystem realization algorithm (ERA). The experimental test was carried out in a beam structure through varying the mass of an element. For the output signal was used a piezoelectric sensor. The signal of input of sine form was generated through SignalCalc® software.

Anomaly Detection in Noisy Images

Finding rare events in multidimensional data is an important detection problem that has applications in many fields, such as risk estimation in insurance industry, finance, flood prediction, medical diagnosis, quality assurance, security, or safety in transportation. The occurrence of such anomalies is so infrequent that there is usually not enough training data to learn an accurate statistical model of the anomaly class. In some cases, such events may have never been observed, so the only information that is available is a set of normal samples and an assumed pairwise similarity function. Such metric may only be known up to a certain number of unspecified parameters, which would either need to be learned from training data, or fixed by a domain expert. Sometimes, the anomalous condition may be formulated algebraically, such as a measure exceeding a predefined threshold, but nuisance variables may complicate the estimation of such a measure. Change detection methods used in time series analysis are not easily extendable to the multidimensional case, where discontinuities are not localized to a single point. On the other hand, in higher dimensions, data exhibits more complex interdependencies, and there is redundancy that could be exploited to adaptively model the normal data. In the first part of this dissertation, we review the theoretical framework for anomaly detection in images and previous anomaly detection work done in the context of crack detection and detection of anomalous components in railway tracks. In the second part, we propose new anomaly detection algorithms. The fact that curvilinear discontinuities in images are sparse with respect to the frame of shearlets, allows us to pose this anomaly detection problem as basis pursuit optimization. Therefore, we pose the problem of detecting curvilinear anomalies in noisy textured images as a blind source separation problem under sparsity constraints, and propose an iterative shrinkage algorithm to solve it. Taking advantage of the parallel nature of this algorithm, we describe how this method can be accelerated using graphical processing units (GPU). Then, we propose a new method for finding defective components on railway tracks using cameras mounted on a train. We describe how to extract features and use a combination of classifiers to solve this problem. Then, we scale anomaly detection to bigger datasets with complex interdependencies. We show that the anomaly detection problem naturally fits in the multitask learning framework. The first task consists of learning a compact representation of the good samples, while the second task consists of learning the anomaly detector. Using deep convolutional neural networks, we show that it is possible to train a deep model with a limited number of anomalous examples. In sequential detection problems, the presence of time-variant nuisance parameters affect the detection performance. In the last part of this dissertation, we present a method for adaptively estimating the threshold of sequential detectors using Extreme Value Theory on a Bayesian framework. Finally, conclusions on the results obtained are provided, followed by a discussion of possible future work.

Classificação de sinais acústicos utilizando a transformada wavelet discreta e a decomposição de modo empírico: aplicações na área de alimentos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Diagnose de trincas em sistemas rotativos, utilizando modelos de falhas através da metodologia dos observadores de estados

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detección de grietas en placas con técnicas multifrecuencia

Safety is one of the most important feature in the aviation industry, and this involves too many factors. One of these is the aircraft maintenance. Over time, the procedures have been changing, and improving themselves. Non Destructive Testing (NDT) appeared in the late 19th century as a great option, because it enabled to inspect any structure without damaging it. Nowadays, there are several kinds of NDT, but ultrasound is one of the most widely used. This Master Thesis is devoted to an innovative ultrasound technique for crack detection. A technique, whose main aim lies in getting a good location of defects from a few measures, breaking with the currently widespread methods, as phased array. It is not necessary to use trains of waves, only discrete excitations, which means a great saving of time and energy. This work is divided into two steps: the first is to develop a multiphysics simulator, which is able to solve linear elasticity 3D problems (via Finite Element Method, FEM). This simulator allows to obtain in a computationally efficient way the displacement field for different frequencies and excitations. The solution of this elastic problem is needed to be used in the second step, which consists of generating a code that implements a mathematical tool named topological derivative, allowing to locate defects in the studied domain. In this work, the domain is a plate, and the defect is a hidden spherical void. The simulator has been developed using open source software (Elmer, Gmsh, ...), achieving a highly versatile simulator, which allows to change the configuration easily: domain size and shape, number and position of transducers, etc. Just one comercial software is used, Matlab. It is used to implement the topological derivative. In this work, the performance of the method is tested in several examples comparing the results when one or more frequencies are considered for different configurations of emisors/receptors.

Multiple paths extraction in images using a constrained expanded trellis

Single shortest path extraction algorithms have been used in a number of areas such as network flow and image analysis. In image analysis, shortest path techniques can be used for object boundary detection, crack detection, or stereo disparity estimation. Sometimes one needs to find multiple paths as opposed to a single path in a network or an image where the paths must satisfy certain constraints. In this paper, we propose a new algorithm to extract multiple paths simultaneously within an image using a constrained expanded trellis (CET) for feature extraction and object segmentation. We also give a number of application examples for our multiple paths extraction algorithm.

Surface wave techniques for the study of engineering structures and materials

A wire drive pulse echo method of measuring the spectrum of solid bodies described. Using an 's' plane representation, a general analysis of the transient response of such solids has been carried out. This was used for the study of the stepped amplitude transient of high order modes of disks and for the case where there are two adjacent resonant frequencies. The techniques developed have been applied to the measurenent of the elasticities of refractory materials at high temperatures. In the experimental study of the high order in-plane resonances of thin disks it was found that the energy travelled at the edge of the disk and this initiated the work on one dimensional Rayleigh waves.Their properties were established for the straight edge condition by following an analysis similar to that of the two dimensional case. Experiments were then carried out on the velocity dispersion of various circuits including the disk and a hole in a large plate - the negative curvature condition.Theoretical analysis established the phase and group velocities for these cases and experimental tests on aluminium and glass gave good agreement with theory. At high frequencies all velocities approach that of the one dimensional Rayleigh waves. When applied to crack detection it was observed that a signal burst travelling round a disk showed an anomalous amplitude effect. In certain cases the signal which travelled the greater distance had the greater amplitude.An experiment was designed to investigate the phenanenon and it was established that the energy travelled in two nodes with different velocities.It was found by analysis that as well as the Rayleigh surface wave on the edge, a seoond node travelling at about the shear velocity was excited and the calculated results gave reasonable agreement with the experiments.

Crack origin and detection in thin cristallyne solar cells in a production line

In order to reduce cost and make up for the rising price of silicon, silicon wafers are sliced thinner and wider,eading to weaker wafers and increased breakage rates during fabrication process. In this work we have analysed different cracks origins and their effect on wafer’s mechanical strength. To enhance wafer’s strength some etching methods have been tested. Also, we have analysed wafers from different points of an entire standard production process. Mechanical strength of the wafers has been obtained via the four line bending test and detection of cracks has been tested with Resonance Ultrasonic Vibration (RUV) system, developed by the University of South Florida.

Corrosion Versus Mechanical Tests for Indirect Detection of Alpha Prime Phase in UNS S32520 Super Duplex Stainless Steel

Alpha prime formation leads to material embrittlement and deterioration of corrosion resistance. In the present study, the mechanical and corrosion behavior of super duplex stainless steel UNS S32520 aged at 475 degrees C from 0.5 h to 1,032 h was evaluated using microhardness measurements, Charpy impact tests, electrochemical impedance spectroscopy, and cyclic polarization curves. The sensibility of these tests to the effects of alpha prime phase was investigated. The microhardness test showed a gradual increase in hardness with aging time, whereas the impact tests revealed losses of about 80% in the energy absorption capacity for the material aged for 12 h in comparison with the solution-annealed samples. The most responsive analysis was the impact test, which indirectly revealed the presence of this deleterious phase in samples aged for 0.5 h. The electrochemical impedance spectroscopy and polarization tests were not highly sensitive to the alpha prime phase unless these are present in large amounts in the stainless steel.

Fault detection in rotating machines by vibration signal processing techniques

Machines with moving parts give rise to vibrations and consequently noise. The setting up and the status of each machine yield to a peculiar vibration signature. Therefore, a change in the vibration signature, due to a change in the machine state, can be used to detect incipient defects before they become critical. This is the goal of condition monitoring, in which the informations obtained from a machine signature are used in order to detect faults at an early stage. There are a large number of signal processing techniques that can be used in order to extract interesting information from a measured vibration signal. This study seeks to detect rotating machine defects using a range of techniques including synchronous time averaging, Hilbert transform-based demodulation, continuous wavelet transform, Wigner-Ville distribution and spectral correlation density function. The detection and the diagnostic capability of these techniques are discussed and compared on the basis of experimental results concerning gear tooth faults, i.e. fatigue crack at the tooth root and tooth spalls of different sizes, as well as assembly faults in diesel engine. Moreover, the sensitivity to fault severity is assessed by the application of these signal processing techniques to gear tooth faults of different sizes.

Crack measurements in structural concrete with D.I.C. system and validation of a tensile constitutive law

Compared with other mature engineering disciplines, fracture mechanics of concrete is still a developing field and very important for structures like bridges subject to dynamic loading. An historical point of view of what done in the field is provided and then the project is presented. The project presents an application of the Digital Image Correlation (DIC) technique for the detection of cracks at the surface of concrete prisms (500mmx100mmx100mm) subject to flexural loading conditions (Four Point Bending test). The technique provide displacement measurements of the region of interest and from this displacement field information about crack mouth opening (CMOD) are obtained and related to the applied load. The evolution of the fracture process is shown through graphs and graphical maps of the displacement at some step of the loading process. The study shows that it is possible with the DIC system to detect the appearance and evolution of cracks, even before the cracks become visually detectable.

In-situ detection of defect formation in organic flexible electronics by Kelvin Probe Force Microscopy

Organic semiconductor technology has attracted considerable research interest in view of its great promise for large area, lightweight, and flexible electronics applications. Owing to their advantages in processing and unique physical properties, organic semiconductors can bring exciting new opportunities for broad-impact applications requiring large area coverage, mechanical flexibility, low-temperature processing, and low cost. In order to achieve highly flexible device architecture it is crucial to understand on a microscopic scale how mechanical deformation affects the electrical performance of organic thin film devices. Towards this aim, I established in this thesis the experimental technique of Kelvin Probe Force Microscopy (KPFM) as a tool to investigate the morphology and the surface potential of organic semiconducting thin films under mechanical strain. KPFM has been employed to investigate the strain response of two different Organic Thin Film Transistor with active layer made by 6,13-bis(triisopropylsilylethynyl)-pentacene (TIPS-Pentacene), and Poly(3-hexylthiophene-2,5-diyl) (P3HT). The results show that this technique allows to investigate on a microscopic scale failure of flexible TFT with this kind of materials during bending. I find that the abrupt reduction of TIPS-pentacene device performance at critical bending radii is related to the formation of nano-cracks in the microcrystal morphology, easily identified due to the abrupt variation in surface potential caused by local increase in resistance. Numerical simulation of the bending mechanics of the transistor structure further identifies the mechanical strain exerted on the TIPS-pentacene micro-crystals as the fundamental origin of fracture. Instead for P3HT based transistors no significant reduction in electrical performance is observed during bending. This finding is attributed to the amorphous nature of the polymer giving rise to an elastic response without the occurrence of crack formation.