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Non-destructive evaluation is concerned with the detection and characterisation of flaws. In eddy-current inspection, measurements of the electro-magnetic field are made at the surface of a flawed conductor, in an oscillating electric or magnetic field. The aim of this study is to develop an eddy-current method of imaging flaws based on measurements of the magnetic field data. In the presence of an oscillating current, it is shown that the physical behaviour of a thin crack can be modelled by a layer of electric dipoles. Green's functions are introduced, relating the dipole distribution on the crack to the magnetic field above the conductor. It is shown how the resulting integral expressions can predict the magnetic field. These relationships also provide a means of deducing the dipole density on a crack from measurements of the magnetic field. The distribution of dipoles reflects the crack geometry and essentially represents an image of the crack. A scanning rig is described and optimised for use in the study. Alternating current, at a pre-selected frequency (typically around 1kHz), is injected into aluminium alloy plates containing manufactured slots, and spatially distributed measurements of the magnetic field are made with a Hall transducer. The Hall transducer has advantages over traditional coil type transducers, in particular having better spatial resolution and improved detection efficiency, over the range of frequencies used in this study. The dipole density is generally a vector quantity and the problem of recovering it is ill-posed. However, by orientating the plane of the slot perpendicular to the direction of a uniform incident field, it was possible to induce only one component of the dipole density and then recover this from field measurements. The data collected by the experimental rig was used to image two types of manufactured slot. Initially, relatively shallow surface-breaking slots were imaged. For surface cracks, the imaging process was formulated as one of deconvolution, and a Wiener filter was used to perform this operation, to overcome the effects of experimental noise. Secondly, images were obtained of thin slots, which did not break the surface of the conductor, and whose plane extended into the specimens. For these sub-surface slots, the imaging problem was formulated as one of matrix inversion and several techniques were tested for their suitability to invert large ill-conditioned systems, relatively quickly and reliably. The favoured inversion techniques were singular value decomposition (SVD) and a recently developed bi-diagonalisation algorithm known as the Jones-Lanczos (JL) algorithm. The JL algorithm seems a promising technique for the inversion of large, ill-conditioned systems, particularly if noise is present. It is robust and relatively fast, performing the same inversion in one-third the time taken by SVD. Existing conjugate gradient algorithms were also tested, but were found to be inadequate for the solution of the current problem. Dipole images of the two classes of slot were obtained. The images allowed good estimation of geometry and position of the respective slot. Reconstruction of the dipole density on a crack would appear to be an effective method for imaging cracks.

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Master of Science / Department of Electrical and Computer Engineering / Balasubramaniam Natarajan / This thesis proposes an automated crack detection and classification algorithm to detect durability cracking (“D”-cracking) in pavement by using image processing and pattern recognition techniques. For the Departments of Transportation across the country, efficient and effective crack detection is vital to maintaining quality roadways. Manual inspection of roadways is tedious and cumbersome. Previous research has focus on distinct transverse and longitudinal cracks. However, “D”-cracking presents a unique challenge since the cracks are fine and have a distinctive shape surrounding the intersection of the transverse and longitudinal joints. This thesis presents an automated crack detection and classification system using several known image processing techniques. The algorithm consists of four sections: 1) lighting correction, 2) subimage processing, 3) postprocessing and 4) classification. Some images contain uneven lighting, which are corrected based on a model of the lighting system. The region of interest is identified by locating the lateral joints. These regions are then divided into overlapping subimages, which are then divided into cracked and noncracked pixels using thresholds on the residual error. Postprocessing includes a row/column sum filter and morphological open operation to reduce noise. Finally, metrics are calculated from the final crack map to classify each section as cracked or noncracked using the Mahalanobis distance from the noncracked distribution.

Roads are major public assets. The USA spends billions of dollars each year on road construction and maintenance. To keep these roads in a healthy condition and for better planning and allocation of maintenance budgets, knowledge of distressed locations is needed. Roads develop cracks when they are subjected to stresses that exceed their designed criteria or their materials properties. Early detection and repair of cracks has proven to be the most cost-effective strategy in limiting the damage to roads and reducing expenditures. Various methodologies of crack detection were developed and significant techniques were made in the last few years. One of the most important recent technologies is the infrared thermography, which allows the use of infrared waves for crack detection. Another important technology is the global navigation satellite system (GNSS) which currently includes the GPS and GLONASS constellations. With the help of these systems, accurate location coordinates (longitude, latitude and altitude) up to a few centimeters were located. The objective of this research is to test the combined use of GNSS and infrared thermography in an automated system for the detection of asphalt cracks and their locations. To achieve this goal, two tests have been conducted. The first one, regarding the location tagging, was done using two pairs of GPS receivers which can detect signals from both GPS and GLONASS navigation systems in single and dual frequencies (L1 and L2). Different modes have been set to the receiver and comparison graphs were developed to compare accuracies against modes. The second test involves an infrared camera mounted on a car and moving in speeds approaching highway speed limit. The images obtained from the camera were processed using cracks detection software to analyze cracks properties (length, width, density and severity). It was found that the images that were taken by a moving infrared camera were recognized by crack detection software for moving speeds up to 50 mph. At speeds higher than 50 mph, images were blurred. As for location test, The GLONASS combined by GPS receivers got slightly better results than GPS only in both dual and single frequencies. The GLONASS satellites are not always available in view and when they are there, the number of satellites that can be detected by receiver range from one to three satellites at the most and for only a short period of time. It is recommended that future research be conducted to investigate the effect of using different camera lenses on the clarity of the images obtained as well as the effect of raising the camera level above the pavement surface in such a way that the whole lane width (12 ft.) would be covered in one image. Also the total reliance on GPS only receivers in determining cracks location has proven to be enough for this application.

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<p>Abstract: The process of inspecting welds done in production at Volvo Aero in Trollhättan is timeconsuming and a lot of this time goes into examining faulty objects. The aim of this thesis is to startdevelopment of a system that analyses acoustic emission from cooling welds to determine the qualityof the weld. Our aim is to be able to detect cracks in the material and to give information on thecracks using the data gathered by our sensors. To do this we will use methods to locate sound sourcesand then rate our findings and do some simplifications on the result of our calculations. We willanalyze our calculated data to find crack signatures and classify our findings and give alarms if wefind cracks that are considered too big for comfort. We will also give insight in to future aspects of ourwork and look at ways to improve on our proposed methods. We will discuss our systems pros, consand what things have been taken into consideration during design, and what strategies we proposeto handle the results from the system.</p>

Abstract: The process of inspecting welds done in production at Volvo Aero in Trollhättan is timeconsuming and a lot of this time goes into examining faulty objects. The aim of this thesis is to startdevelopment of a system that analyses acoustic emission from cooling welds to determine the qualityof the weld. Our aim is to be able to detect cracks in the material and to give information on thecracks using the data gathered by our sensors. To do this we will use methods to locate sound sourcesand then rate our findings and do some simplifications on the result of our calculations. We willanalyze our calculated data to find crack signatures and classify our findings and give alarms if wefind cracks that are considered too big for comfort. We will also give insight in to future aspects of ourwork and look at ways to improve on our proposed methods. We will discuss our systems pros, consand what things have been taken into consideration during design, and what strategies we proposeto handle the results from the system.