Showing papers in "Ndt & E International in 2009"

Measurement of the ultrasonic nonlinearity of kissing bonds in adhesive joints

Abstract: This paper presents a study of the detectability of kissing bonds in adhesive joints using an ultrasonic inspection technique to measure nonlinearity. Kissing bonds are defined as adhesive bonding defects in which the adhesive and the substrate are not fully bonded together but are in some way connected, for example, through contact between disbonded surfaces or through coupling via a very thin layer of contaminant. The result is a region that exhibits reduced normal or shear stiffness and is difficult to detect using conventional non-destructive testing techniques. It is hypothesised that when an ultrasonic wave of large magnitude propagates through the kissing bond area, the system will behave nonlinearly. This hypothesis is the starting point for this paper, and it is tested by measuring the degree of nonlinearity exhibited by perfectly and imperfectly bonded specimens. Perfectly disbonded adhesive joints are tested over a range of compressive loads from an initial zero-load ‘open’ condition to a final highly loaded ‘closed’ condition and the degree of nonlinear behaviour measured. It is shown that adhesive joints exhibit significant nonlinearity under light compressive loads and that the level of nonlinearity decreases rapidly with compressive load. Good agreement is also observed between experimental results and a nonlinear spring model of the adhesive joint, based on its quasi-static interfacial stiffness.

Evaluation of multilayer perceptron and self-organizing map neural network topologies applied on microstructure segmentation from metallographic images

Abstract: Artificial neuronal networks have been used intensively in many domains to accomplish different computational tasks. One of these tasks is the segmentation of objects in images, like to segment microstructures from metallographic images, and for that goal several network topologies were proposed. This paper presents a comparative analysis between multilayer perceptron and self-organizing map topologies applied to segment microstructures from metallographic images. The multilayer perceptron neural network training was based on the backpropagation algorithm, that is a supervised training algorithm, and the self-organizing map neural network was based on the Kohonen algorithm, being thus an unsupervised network. Sixty samples of cast irons were considered for experimental comparison and the results obtained by multilayer perceptron neural network were very similar to the ones resultant by visual human inspection. However, the results obtained by self-organizing map neural network were not so good. Indeed, multilayer perceptron neural network always segmented efficiently the microstructures of samples in analysis, what did not occur when self-organizing map neural network was considered. From the experiments done, we can conclude that multilayer perceptron network is an adequate tool to be used in Material Science fields to accomplish microstructural analysis from metallographic images in a fully automatic and accurate manner.

Feature extraction of a concrete tunnel liner from 3D laser scanning data

Abstract: Underground structures require routine inspections and maintenance processes for their optimal use In particular, the practical inspection of tunnels commonly relies on human-based methods that entail inherent limitations The applications of laser technology are rapidly expanding, with decreased cost and increased accuracy This study attempted to investigate the feasibility of applying laser scanning technology to the management of infra-structures A trial model of a laser-based tunnel scanning system was developed to facilitate an automated tunnel inspection process The trial model scanner scans a tunnel in the time-of-flight manner, and delivers the scanned data in ASCII files containing x, y and z coordinates In addition, this paper proposed an algorithm to extract the information for tunnel management from the data set acquired from the trial model The proposed algorithm extracts installations on the liner and the physically damaged parts of a tunnel liner using the geometric and radiometric features of the scanning data The algorithm was tested and evaluated by using the scanned data set from an operating railway tunnel and a concrete box with various diameters of pipes attached on one wall of the box Due to the mechanical and laser sensor limitations, the developed trial model is limited with respect to the identification of cracks and installations; cracks and installations having a gap or width of less than 5 mm are not detected well This limitation, however, will be overcome by upgrading the scanning system and through increased density of the point cloud (A) Reprinted with permission from Elsevier

An automatic system of classification of weld defects in radiographic images

Abstract: In this paper, we describe an automatic detection system to recognise welding defects in radiographic images. In a first stage, image processing techniques, including noise reduction, contrast enhancement, thresholding and labelling, were implemented to help in the recognition of weld regions and the detection of weld defects. In a second stage, a set of geometrical features which characterise the defect shape and orientation was proposed and extracted between defect candidates. In a third stage, an artificial neural network (ANN) for weld defect classification was used. With the aim of obtaining the best performance of ANN three different methods for improving network generalisation was used. The results was compared with a method without generalisation. For the input layer, the principal component analysis technique was used in order to reduce the number of feature variables; and, for the hidden layer, a different number of neurons was used.

Development of a magnetic sensor for detection and sizing of internal pipeline corrosion defects

Abstract: Magnetic flux leakage (MFL) is the most used technique for pipeline inspection, being applied through the use of instrumented PIGs. The pipe wall is magnetized and when metal loss or other irregularities occur, a larger fraction of the magnetic flux “leaks” outwards from the wall and is detected by sensors. MFL presents some limitations since it requires magnetic saturation of the pipe wall. Therefore, it is difficult to inspect small diameter and thick wall pipelines. Internal corrosion sensor (ICS) has been developed as a solution for internal corrosion measurements of thick walls. The technique, also called “field disturbance”, is based in a direct magnetic response from a small area of the wall. It is not necessary to achieve the magnetic saturation of the pipe material, and thus ICS performance is not affected by the thickness of the pipe wall. In the present work, finite element calculations are performed and the best resultant configuration of the sensor is proposed. Experimental tests with a prototype were carried out and the results give a strong indication of the validity of the theoretical model proposed for sizing.

GPR signal de-noising by discrete wavelet transform

Abstract: Ground penetrating radar (GPR) is a non-destructive investigation tool used for several applications related to civil infrastructures; including buried objects detection and structural condition evaluation. Although GPR can be effectively used to survey structures, signal analysis can be sometimes challenging. The GPR signals can be easily corrupted by noise because the GPR receiver has usually an ultra-wide bandwidth (UWB). The noise collected by the system can easily mask relatively weak reflections resulting from the inhomogeneities within the surveyed structure; especially when they are at a relatively deep location. This paper presents the use of discrete wavelet transform (DWT) to de-noise the GPR signals. Various mother wavelets were used in this study to de-noise experimental GPR signals collected from flexible pavements. The performance of wavelet de-noising was evaluated by computing the signal-to-noise ratio (SNR) and the normalized root-mean-square error (NRMSE) after de-noising. The study found that wavelet de-noising approach outperforms traditional frequency filters such as the elliptic filter. At the same level of decomposition, the Daubechies order 6 and Symlet order 6 outperform the Haar and Biorthogonal mother wavelets when de-noising GPR signals by soft thresholding.

Measurement of axial stress using mode-converted ultrasound

Abstract: A new ultrasonic technique for stress measurement using mode conversion is proposed and applied to the estimation of axial stresses in high-tension bolts The effect of axial stresses on acoustic wave velocities in axisymmetric cylindrical solids is analyzed, and a linear acousto-elastic equation is formulated Theoretical ray analysis is performed to compute time of flight (TOF) of mode-converted waves in cylindrical solids To evaluate the validity of the proposed method, mode-converted longitudinal and shear waves in carbon-steel bolts are generated and captured to measure the TOF of the waves Simultaneous velocity measurement of two differently polarized acoustic waves are made with enough resolution to estimate axial stresses with values less than 10% of the yield stress of the bolt material It is observed from experimental results that the TOF ratio of longitudinal and shear waves is linearly proportional to the axial stress in bolts within 5% error, as expected from theory

Contactless recognition of concrete surface damage from laser scanning and curvature computation

Abstract: A method conceived for automatic recognition of mass loss of concrete using data acquired by terrestrial laser scanner is presented here. The method is based on computation of mean and Gaussian curvatures of the surface and on piecewise comparison of the corresponding distributions, since these distributions strongly change if an area is affected by damage. This contactless damage recognition system, which could be applied together with other NDT techniques to provide a complete picture of the health of the observed structure, has been successfully applied to a concrete bridge.

Stress dependence of the spontaneous stray field signals of ferromagnetic steel

Abstract: Measuring spontaneous stray field signals provides a promising tool to analyze the stress in ferromagnetic materials. However, strong initial stray field signals on the surface of ferromagnetic materials originating from various manufacturing processes can disturb stress-induced stray field signals. Consequently, it is necessary to conduct a study that will clarify the stress dependence of spontaneous stray field signals by eliminating initial random signals. In the present work, the focus is placed on sheet specimens that have a clean initial magnetic state by means of vacuum heat treatment. Measurements of the normal component H p ( y ) signals of stray field were performed during the whole tensile test. The results showed that the stress-induced H p ( y ) signal curve had good linearity after loading, i.e., the slope coefficient K s increased continuously in the elastic deformation stage but decreased slightly during the plastic deformation stage. This phenomenon was discussed and explained from both the stress-induced effective magnetic field and residual compressive stress viewpoints.

Sub-terahertz imaging of defects in building blocks

Abstract: A compact sub-terahertz (THz) imaging system with a 0.2 THz-band GaAs TUNNETT diode oscillator and its application for non-destructive and harmless inspections of timbers, concrete and ceramic tiles are shown. Sub-THz transmission characteristics of various kinds of woods were investigated. It is shown that wood and concrete show a high transmittance in this frequency range, and that the measured absorption coefficients correlate well with the densities of woods. Then, the invisible grains, knots and diffused water inside the timbers were investigated by sub-THz transmission imaging. It is also shown that the sub-THz wave is a very efficient tool for defect recognition in concrete. Invisible cracks, diffused water and the quality of adhesion of tiles were investigated. It is concluded that the sub-THz wave has shown a high sensitivity in detecting these defects in building blocks.

High-temperature integrated and flexible ultrasonic transducers for nondestructive testing

Abstract: Integrated ultrasonic transducers (IUTs) and flexible ultrasonic transducers (FUTs) are presented for nondestructive testing at high temperatures. These transducers are made of sol–gel-sprayed piezoelectric thick (>40 μm) ceramic films. The ceramic materials are lead-zirconate-titanate, bismuth titanate and lithium niobate which are for thickness measurements up to 150, 400 and 800 °C, respectively. The IUT can also be deposited onto one end of a long ultrasonic delay line to perform nondestructive testing at the other end at even higher temperatures. FUTs made of bismuth titanate films onto thin stainless steel foils are also used for thickness measurements at 300 °C with a high-temperature couplant sandwiched between the FUT and a steel substrate. All experiments at high temperatures were performed in pulse-echo mode and ultrasonic echoes with signal-to-noise ratios above 20 dB were obtained. The center operation frequencies of both IUTs and FUTs range from 4.4 to 10.7 MHz.

3D finite element simulations of an air-coupled ultrasonic NDT system

Abstract: A single-sided, air-coupled ultrasonic NDT system based on the generation and reception of the A0 Lamb mode is used for detecting defects in plates. Transmitting and receiving transducers, being oriented at the appropriate coincidence angle for the generation and detection of the mode, are scanned along a line from one side to the other over the surface of the sample, passing the area with the defect. This contact-less NDT system is modelled in three dimensions with a Finite Element -based method. The air-coupled transmitter is modelled by the normal pressure that it locally applies on the surface of the plate, and the air-coupled receiver by integrating normal displacements over a finite area of appropriate position on the surface of the plate. In this way, beam spreading of both incident and scattered fields is considered. Numerical predictions have successfully been compared with experimental data for a through-thickness hole in an Aluminium plate and also for an impact damage in a composite sample.

A nonlinear-guided wave technique for evaluating plasticity-driven material damage in a metal plate

Abstract: This research develops an experimental method for evaluating material damage due to plastic deformation in a metal plate using nonlinear-guided waves. An improved version of a previously proposed measurement technique is used. The material nonlinearities of aluminum specimens loaded to produce different levels of plastic strain are measured with Lamb waves. A pair of wedge transducers is used to generate and detect the fundamental (s1) and second harmonic (s2) Lamb waves. The weak amplitude of the second harmonic wave is extracted from the spectrogram of a received signal. The measured acoustic nonlinearity increases monotonically with the level of plasticity (plastic strain), which is similar to the behavior of longitudinal and Rayleigh waves. This result indicates that Lamb waves can be used to assess plasticity-driven material damage in the established framework of the second harmonic generation technique. The effects and the importance of signal processing in determining the nonlinearity parameter are also discussed.

Analytical modeling for transient probe response in pulsed eddy current testing

Abstract: An improved analytical model by the Fourier method for transient eddy current response is presented. In this work, an alternative approach is considered to solve the harmonic eddy current problem by the reflection and transmission theory of electromagnetic waves, thus a more concise closed-form expression is expected to be obtained. To reduce the inherent Gibbs phenomenon, a harmonic order-dependent decreasing factor is employed to weight the Fourier series (FS) representation. It is shown that the developed model is promising to be used as a fast and accurate analytical solver for the transient probe response and is helpful to gain a deep insight into pulsed eddy current (PEC) testing.

Pulsed eddy current testing with variable duty cycle on rivet joints

Abstract: In pulsed eddy current testing, repetitive excitation signals with different duty cycles have different spectral representations. This work studies the influence of duty cycle on the ability to detect holes and EDM notches beneath rivet heads in subsurface layers of stratified samples. Feature patterns for the integrity of rivet joints are proposed and verified. The proposed method has the added advantage in that no reference sample is needed while employing multiple pulse measurements, with different pulse widths. Experimental testing and modelling approaches are discussed in connection with defect depth quantification, which can be extended to the quantification of complex defects.

High-speed inspection of rails using ACFM techniques

Abstract: High-speed ACFM tests were carried out using a rotary test piece that contained spark-eroded notches. The ACFM sensor detected the induced notches during inspection at 121.5 km/h. The recorded signal remained unaffected by the increases in inspection speed under constant lift-off. To simulate actual rail inspection conditions at high speed, further tests were carried out using a spinning rail rig and a set of rails that contained spark-eroded notches of various shapes and sizes up to a speed of 32 km/h. Although, the ACFM sensor successfully detected the majority of the notches, the signal obtained was affected by lift-off variations.

Flaw detection in radiographic weldment images using morphological watershed segmentation technique

Abstract: In this paper, the concept of application of morphological multistage watershed segmentation for detection of flaws in radiographic weld images is discussed. It is simple and intuitive and always produces a complete division of the image. The multistage watershed segmentation used here reduces the problem of over segmentation besides generating boundaries with very less deviation from their original position. Two-stage water segmentation is implemented here. At the first stage, watershed transform is applied to an X-ray image and the resultant mosaic image pattern is further thresholded by Otsu's thresholding method and converted into the binary image. Then, morphology and top-hat transformation is applied on binary image to separate partially overlapping objects. Euclidean distance map is calculated for each basin to label resultant segments uniquely and to separate ridges. This follows the second stage of watershed segmentation to obtain better-defined boundaries while removing over-segmented regions. Watershed segmentation algorithm has been able to detect flaws like slag inclusions and wormholes-type weld flaws. It shows all defects with reasonable accuracy having close contours. Similarly, small cavities are also highlighted successfully.

Magnetic field variation induced by cyclic bending stress

Abstract: Metal magnetic memory technique has provided a new arena for assessing stress status, especially for detecting early damage in ferromagnetic materials. To investigate the magnetomechanical effect of metal magnetic memory phenomenon, the rotary bending fatigue experiments under different stress levels were conducted. The normal components of magnetic field intensities induced by cyclic bending stresses on the surfaces of 45-steel specimens were measured throughout the fatigue process. The results show that surface magnetic fields generated contains reversible and irreversible process prior to failure, while there is a substantial increase just before fracture. Possible reasons for the variations of magnetic fields and corresponding signal characteristics to identify damage zones were discussed.

Micro-magnetic evaluation of micro residual stresses of the IInd and IIIrd order

Abstract: Micro residual stresses (MRS) of the IInd and IIIrd order play an important role in the fracture mechanical analysis of thermally cycled materials, and thus in lifetime analysis of such affected components. In multi-phase materials there can exist two kinds of MRS: thermally induced MRS of the IInd order and coherent MRS of IIIrd order. The thermally induced stresses of the IInd order appear when individual material phases exhibit different thermal expansion coefficients. The coherent MRS of the IIIrd order appear when the lattice parameter of the second phase particles embedded coherently in the matrix and the lattice parameter of the matrix are different. The main emphasis of the presented research work is the development of a micro-magnetic non-destructive technique for quantitative characterization and separation of MRS of IInd and IIIrd order in iron-based materials.

2D and 3D non-destructive evaluation of a wooden panel painting using shearography and terahertz imaging

Abstract: Structural diagnostics information about artwork is commonly obtained by adapting and applying non-destructive testing techniques from engineering. Shearography is a technique well known for type inspection, and for structural analysis in automotive, aerospace and industrial applications. In art conservation, a limited number of shearography sensors are in use at museums and research institutes throughout the world for detecting surface and sub-surface defects. Terahertz imaging is a new and rapidly developing non-destructive testing technique that has so far found application mainly for security. The aim of this study is to measure a complex object, a wooden panel painting using both techniques and to determine the capability of a combined sensor for cultural heritage applications.

Non-destructive testing of hardened cement specimens at microwave frequencies using a simple free-space method

Abstract: In this research paper, we show microwave reflection and transmission properties measured from various sides of hardened mortar and concrete specimens with different water-to-cement ratios. These properties are important in predicting/measuring accurate electrical properties of cement-based materials which can eventually be utilized in structural health monitoring, public safety, and propagation-related research. Measurements are carried out by a simple and relatively inexpensive non-destructive free-space set-up with its newly developed calibration technique at X-band (8–12 GHz) during 3–36 months after samples’ preparation. A new approach (relative difference approach) is introduced for transmission properties to predict the state and degree of hydration inside specimens. It is shown that concrete specimens will complete the hydration sooner than mortar specimens with the same water-to-cement ratio (w/c) ratio due to heavy aggregates. In addition, among the specimens, while the concrete specimen with a higher w/c ratio will exhibit faster hydration during approximately 3–6.1 months, the mortar specimen with a lower w/c ratio will display rapid hydration during approximately 6.1–30 months. Besides, it is demonstrated that the magnitude of transmission properties for the top (or bottom) is less than those for the right (or left) side due to the effect of gravels and sand particles in specimens. Measurement results indicate that a varying electrical property depending on height should be used for cement-based materials in the predicting the channel properties in propagation-related researches.

Improving the accuracy of computer-aided radiographic weld inspection by feature selection

Abstract: This paper presents new results of our continuous effort to develop a computer-aided radiographic weld inspection system. The focus of this study is on improving accuracy by feature selection. To this end, we propose two versions of ant colony optimization (ACO)-based algorithms for feature selection and show their effectiveness to improve the accuracy in detecting weld flaws and the accuracy in classifying weld flaw types. The performances of ACO-based methods are compared with that of no feature selection and that of sequential forward floating selection, which is a known good feature selection method. Four different classifiers, including nearest mean, k -nearest neighbor, fuzzy k -nearest neighbor, and center-based nearest neighbor, are employed to carry out the tasks of weld flaw identification and weld flaw type classification.

Feasibility of low frequency straight-ray guided wave tomography

Abstract: Corrosion is a major problem in the petrochemical industry. Corrosion patches are often inaccessible, and the majority of the conventional nondestructive evaluation techniques are compromised. There is therefore a need for a rapid, accurate, long range inspection technique to measure the remaining thickness in corrosion patches. Low frequency Lamb wave tomography is a potentially attractive technique to rapidly evaluate the thickness of large sections of partially accessible structures. This approach has been used in the past to detect the shape of defects in a range of applications. Time-of-flight straight-ray tomography relies on the dispersive nature of a guided wave mode to reconstruct the depth profile of a corrosion patch. If the frequency is limited to below the cut-off of the higher order modes the interpretation of the signals and the time-of-flight measurement are easier. In order to reconstruct a thickness map with time-of-flight straight-ray tomography the ray theory needs to be valid. There are two validity criteria: the characteristic size of the defect must be larger than the wavelength and larger than the width of the Fresnel zone. For realistic defect sizes, the likely points of operation in the low frequency regime respect the wavelength condition but not the more stringent Fresnel zone condition. The paper demonstrates, with finite element simulations and experiments, that the ray theory criteria cannot be relaxed for low frequency Lamb wave tomography to evaluate the maximum depth of corrosion patch in typical pipe inspection problems.

Application of laser-generated guided wave for evaluation of corrosion in carbon steel pipe

Abstract: Local wall thinning of pipes, resulting from corrosion, is the major cause of accidents in nuclear power plants. In order to assure the integrity of pipes, a variety of NDE techniques have been proposed. It is well recognized that the utilization of guided waves to detect flaws in pipes has been a very effective tool for long-range inspection in NDE. Since most conventional research on guided waves has focused on long-range inspection, it is difficult to evaluate a defect in a local area. An objective of this study is to develop a non-contact inspection technique for the quantitative evaluation of defects on a local area in a cylindrical tube. Therefore, the purpose of this study is to introduce an advanced inspection system and a new signal processing method for the evaluation of defects such as corrosion in a pipe. In this study, an advanced non-contact method for pipe inspection is proposed, which generates the ultrasonic guided wave by laser and receives it by a dual air-coupled transducer. Information on each directional defect location and length is obtained by using a line scan along a circumferential and longitudinal direction. Received signals are analyzed by using the peak-to-peak amplitude of waveform and the maximum center frequency magnitude of the frequency spectrum. The optimal mode selection of guided waves based on a dispersion curve is also discussed. The experimental results using the proposed method show that the location and the size of the defect could be evaluated successfully in the 2-dimensional scanning images.

Characterization of subsurface defects in aeronautical riveted lap-joints using multi-frequency eddy current imaging

Abstract: The authors present an original eddy current imager (ECI) designed for the fast and accurate non-destructive evaluation of defects buried next to rivets in aeronautical lap-joints. The ECI is associated to a signal processing method based on a principal component analysis (PCA) followed by a maximum likelihood (ML) approach. The PCA was implemented using EC images obtained with selected excitation frequencies. These images are considered as resulting from a linear mixing of different sources including the presence of rivets and defects, and the PCA is used to separate these sources thanks to an eigen decomposition of the EC data covariance matrix. As a result, the defect signatures are enhanced and used to implement an automatic defect characterization. This characterization is carried out by the means of an ML approach which allows the length and depth of the defects to be estimated. The method was implemented for the evaluation of a laboratory made riveted lap joint mock-up featuring buried defects. It was experimentally optimized and successfully implemented for the characterization of calibrated defects ranging from 2 to 10 mm in length and 2 to 8 mm in depth.

Frictional heating model for efficient use of vibrothermography

Abstract: This paper investigates vibrothermography for the detection of fatigue cracks in steel compact tension specimens using combined experimental and numerical analyses. First, a numerical modal analysis is carried out to predict the optimal excitation parameters. A coupled thermo-mechanical model is then built to simulate the thermographic inspection. The model predicts the detection of cracks as short as 0.1 mm that is also confirmed experimentally using a commercial infrared camera with a maximum error of 2.13% on the temperature distribution. The model reveals that the specimens’ temperature increases at the crack vicinity according to the excitation frequency and is modulated due to the nonlinearity induced by the crack. The model also shows that the stress at the crack tip is lower than the material's yield stress, which makes the test truly non-destructive.

Signal characteristics of differential-pulsed eddy current sensors in the evaluation of plate thickness

Abstract: Differential-pulsed eddy current (PEC) signals and their characteristics are investigated as tools for the evaluation of plate thickness by using the reflection-type PEC probe, which consists of an exciter coil and two sensor coils in a differential arrangement. Numerical and experimental signals are first compared to validate numerical simulation results, and good agreement between them is achieved. Investigation of differential PEC signals and their characteristics against thickness and conductivity variations shows that time-related features, such as the time-to-peak and the zero-crossing time, correspond well to plate thickness and conductivity. However, the feature quality of peak value turns out to be very poor. To improve this, the effects of coil characteristics on the input pulse, and consequently on differential PEC signals, are investigated. Results show that the feature quality of peak value may be improved by reducing the time constant, but doing so would worsen the quality of the other two features. Lift-off signals obtained by this probe show that the lift-off point of intersection also appears in the differential reflection-type PEC signals.

Design of modified electromagnetic main-flux for steel wire rope inspection

Abstract: This paper presents the design and construction of modified main-flux equipment for wire rope inspection which has advantages over the in-service inspection and indirect axial-flux measurement used by ordinary main-flux and return-flux methods. The equipment can be adjusted high electromagnetic field strength to produce leakage filed from flaws of various large-diameter ropes. Unique coil sensors connected in series were employed and performed well when sensing leakage fields of the radial, axial and tangential directions. In addition, a standalone system has a simple setup for service inspection. Due to the complicated structure of the wire rope, electromagnetic field theory for anisotropic structures with high electromagnetization was used to design the equipment. The characteristics of the leakage field, in terms of localized fault and loss of metallic cross-sectional area, were distinguished mathematically. The sensor orientation to detect leakage fields was also determined. Performance of the system was then verified experimentally and shown good resolution and repeatability. Furthermore, the equipment is sufficiently sensitive to detect a smallest surface flaw of 1×2 mm at 5 mm equipment lift off. The inspection signals were processed and shown locations, levels and deterioration quantities.

Experimental investigation of nonlinear acoustic effect at crack

Abstract: The nonlinear ultrasonic technique using the feature of higher-harmonic generation that is one of nonlinear acoustic behavior at interfaces has been considered as a positive method for the detection of micro-cracks. However, most previous studies were limited to model development and its verification by testing two blocks contacted together. This paper investigates experimentally the nonlinear acoustic effect at a real crack. For this, we constructed a measurement system using contact PZT transducers, which was able to keep all equipments and their set-up conditions consistent and thus enabled a reliable measurement of nonlinear parameter. A CT specimen of Al6061 with a crack initiated by a fatigue test was tested, and the nonlinear parameter was measured by scanning along the crack depth direction. We could see that the nonlinear parameter had good correlation with the crack, which was identical to the theoretical prediction. From these results, we could show the applicability of the proposed methodology to micro-crack detection.

Automatic detection of cracks in raw steel block using Gabor filter optimized by univariate dynamic encoding algorithm for searches (uDEAS)

Abstract: Recently, there has been an increase in the demand for quality control in the steel making industry. This paper proposes a vision-based method for detection of defects in the surfaces of scale-covered steel billets. Scales are formed on the surface of billets owing to the deposition of oxidized substances that are produced during manufacturing. Because of the presence of scales on the billet surface, its characteristics such as brightness and texture in the background region are inconsistent. Moreover, the similarities in the gray-levels of the defect and defect-free regions make it very difficult to accurately detect defects. In order to solve the abovementioned problems and to detect defects more effectively, we propose a new defect detection algorithm, which is based on Gabor filters. The Gabor filters are optimized using a new optimization algorithm known as univariate dynamic encoding algorithm for searches (uDEAS). The algorithm finds the minimum value of the cost function related to the energy separation criteria between the defect and the defect-free regions. Finally, the experimental results conducted on billet surface images from actual steel production line show the effectiveness of the proposed algorithm.