Showing papers in "Journal of Nondestructive Evaluation in 2019"

Role of Signal Processing, Modeling and Decision Making in the Diagnosis of Rolling Element Bearing Defect: A Review

Abstract: A significant development in condition monitoring techniques has been observed over the years. The scope of condition monitoring has been shifted from defect identification to its measurement, which was later on extended to automatic prediction of defect. This development is possible because of advancement in the area of signal processing. A number of signal processing and decision making techniques are available each having their own merits and demerits. A specific technique can be most appropriate for a given task, however, it may not be suitable or efficient for a different task. This paper reviewed recent and traditional research, and development in area of defect diagnosis, defect modelling, defect measurement and prognostics. Also it highlights the merit and demerit of various signal processing techniques. This paper is written with the objective to serve as guide map for those who work in the field of condition monitoring.

Phased Array Ultrasonic Inspection of Metal Additive Manufacturing Parts

Abstract: The adoption of wire and arc additive manufacturing (WAAM) in the market has been retained by the need to find a suitable method to ensure the quality of the parts produced. WAAM processes build up parts through the deposition of weld beads, consequently components with rough finish surfaces are characteristics of the method. Non-destructive testing (NDT) by ultrasonic (UT) method, namely the phased array technique (PAUT), is usually used to detect these defects in welding. However, the roughness of the parts represents a challenge for the UT application, since these variations influence the interaction between the emitted UT beam and the component. This study is thus focused on assessing the capability of detecting WAAM defects. The effectiveness of phased array ultrasonic testing to detect defects in aluminium WAAM components with several degrees of surface finish was evaluated. Simulations were first performed with CIVA software to characterize the beam emitted and select the probes and inspection parameters. Afterwards, physical inspections were performed on three reference specimens. Experimental outcomes prove that PAUT techniques are suitable for WAAM defects detection, including sizing, morphology and location. In addition, the experimental results were consistent with the simulated ones. The probes were able to overcome the limitations caused by the surface roughness of the samples, for a maximum of 89.6 μm average waviness profile. Also, defects ranging from 2 to 5 mm were characterized, in size and depth. These preliminary results represent an essential step for the development of an NDT system for inspecting WAAM parts.

Pulsed Phase Thermography Approach for the Characterization of Delaminations in CFRP and Comparison to Phased Array Ultrasonic Testing

Abstract: Pulsed phase thermography (PPT) is a well-established algorithm used for processing thermographic data in frequency domain with the aim to extract information about the defect size and depth. However, few works demonstrated the capability of PPT technique in defects evaluation in real components. The aim of this work is the assessment of capability of PPT technique in determining delaminations in CFRP components used in aeronautics. The component chosen for implementing the technique has a non-uniform geometry and the defects inside it are not simulated, but they are real and generated during the production process. The specimen has been investigated through the application of both the ultrasonic technique and the thermographic one. Thermographic phase images elaborated with a suitable computational processing have been compared with Ultrasonic C-scan images and, the agreement between the location and depth of defects has been verified. Besides, the ultrasonic technique has been used to validate the PPT results.

A New Signal Processing Method Based on Notch Filtering and Wavelet Denoising in Wire Rope Inspection

Abstract: Wire rope is a necessary tool in practical applications especially in crane, elevator and bridge construction, which plays an important role in the national economy and daily life, and safety inspection for wire rope is the key to ensure people’s life and property. However, detection signals are usually complicated due to the twining structures, which make the wire rope defect signal and strand signal mix together. What’s more, no reports and studies have appeared to solve this problem. In view of the situation and challenges above, this paper proposes a combined signal processing method based on notch filtering and wavelet denoising to process detected wire rope signals. Basic time domain, frequency domain and joint time–frequency analysis are first conducted, thereafter, conventional signal processing methods such as lowpass filtering and adaptive analysis are presented according to the signal characterizations. These comparisons and results demonstrate that a conventional single method is incapable of wire-rope-detection signal identification and differentiation. Nonetheless, after the notch filter design and calculation, the processing results for the typical wire rope inspection signals in the experiments indicate that the combined methods can not only distinguish steel wire rope defect signal and strand signal effectively but also with high detection accuracy, even for the inner defect. Finally, the feasibility and reliability are verified by a series of signal processing results and comparisons, which demonstrate that this new method has great application potential and is of vital significance to the development of wire rope safety inspection.

On-line Time Domain Vibration and Current Signals Based Multi-fault Diagnosis of Centrifugal Pumps Using Support Vector Machines

Abstract: It has been observed that centrifugal pumps (CPs) usually fail due to flow instabilities and other factors related to the hydraulic pump design. What is often ignored is the role of one fault in the pump system on the commencement/enhancement of another fault in it. Also, in a CP it is not only important to identify a fault, but it is also important to find the severity of it. In this research, causes of flow instabilities like, the blockage faults, impeller defects, pitted cover plate faults and dry runs are considered with varying severity. These faults are considered both independently and also in combinations with blockage faults. The CP vibration data and the motor line current data in time domain are used for the purpose of fault classification. The multi-fault diagnosis is attempted with the help of support vector machine (SVM) classifier. A fivefold cross-validation technique is used for the selection of optimum SVM hyper parameters. Wrapper model is used to select the best statistical feature(s). Novel features which give the best fault prediction performance of CP faults have been brought out in this work. The fault prediction from the experiments and the established approaches, aid the segregation of all the individual faults, fault combinations and their severities with promising execution, not only at the same training and testing speeds but also at the intermediate and overlying test speeds. The fault prediction of developed methodology has been inspected at various operating conditions of the CP and is found to be remarkably robust.

Detection of Delaminations in Sunlight-Unexposed Concrete Elements of Bridges Using Infrared Thermography

Abstract: Infrared thermography is a non-destructive test used in the inspection of structures. However, its use for bridge inspection is still under development and in many cases its application may be limited to bridge sections exposed to direct sunlight. This study aims to evaluate infrared thermography test for the detection of delaminations in different types of concrete not exposed directly to sunlight. The experimental methodology uses two concrete specimens with water/cement ratios (w/c) equal to 0.5 and 0.6, through the insertion of polystyrene plates of different thicknesses (3, 6 and 12 mm) and depths (25, 50 and 75 mm), in order to simulate defects within the concrete and evaluate the capacity of infrared thermography to detect them. The results show that detection is possible, but limited to short periods of time. In relation to the concrete quality, defects were more easily detected in the test specimen with lower w/c ratio. It can be said that the nearer to the surface and larger the delamination, the easier it is to detect. Also, the better the quality of the concrete, the more effective the technique becomes.

Non-destructive Damage Detection in Fibre Metal Laminates

Abstract: The work explores the possibilities of application of ultrasonic testing in the assessment of fibre metal laminates. Basic problems concerning the use of ultrasonic methods in the research of laminates are explained, and methods for solving these problems are suggested. Tests were conducted using two phased array methods: ultrasonic pulse-echo and through transmission. The efficiency of both selected ultrasonic methods are compared with respect to detecting and dimensioning defects in laminate structures. Based on the analyses and proposed solutions, it has been proven that the developed through transmission phased array (TTPA) method ensures a much more effective, in terms of quality and quantity, assessment of the condition of hybrid laminates than conventional ultrasonic methods, irrespective of the degree of surface deformation and the type of laminate structure.

Performance Based Modifications of Random Forest to Perform Automated Defect Detection for Fluorescent Penetrant Inspection

Abstract: The established Machine Learning algorithm Random Forest (RF) has previously been shown to be effective at performing automated defect detection for test pieces which have been processed using fluorescent penetrant inspection (FPI). The work presented here investigates three methods (two previously proposed in other fields, one novel method) of modifying the FPI RF based on the individual performance of decision trees within the RF. Evaluating based on the $$F_{2}$$ Score, which is the harmonic mean of precision and recall which places a larger weighting on recall, it is possible to reduce the RF in size by up to 50%, improving speed and memory requirements, whilst still gain equivalent results to a full RF. Introducing a performance based weighting or retraining decision trees which fall below a certain performance level however, offers no improvement on results for the increased computation time required to implement.

Barkhausen Noise Probes and Modelling: A Review

Abstract: This review looks at the main types of magnetic Barkhausen noise (BN) probes that have been developed. The aim of this review is to summarize the existing knowledge of magnetic Barkhausen noise probes and the magnetic modelling of them. The BN probes have been the focus of many previous studies, but no sufficient review or conclusions have been made so far. This review focuses on combining information regarding the different types of BN probes and their modelling. The review is divided into two sections; in the first part the different designs and types of Barkhausen noise probes are introduced. The second part of the review deals with the BN probe modelling with various modelling software. Finally, a comparison of the experimental measurements is made and BN sensitivity is discussed.

A Comprehensive Study on Detection of Hidden Delamination Damage in a Composite Plate Using Curvatures of Operating Deflection Shapes

Abstract: The aim of this work is to investigate the accuracy and sensitivity of a continuously scanning laser Doppler vibrometer (CSLDV) for detection of hidden delamination damage in composite plates. Some work on using a CSLDV for detection of damage in aluminum beams and plates has been done by the authors. The current work is related to a worldwide round robin study sponsored by the Society of Experimental Mechanics. The main difference between the current work and previous work is that the damaged composite plate was provided by the organizer of the round robin study instead of being made by the authors. Hence, the authors have no information about locations of the damage, which means this is more like a blind test. The most significant advantage of using a CSLDV for vibration measurement of a structure is that a spatially dense operating deflection shape (ODS) of the structure can be obtained and further used to calculate the curvature of the ODS (CODS). A comprehensive study to detect the hidden damage in the composite plate by using the first seven CODSs from the corresponding ODSs of the plate is conducted. The study shows that different CODSs have different sensitivities to local anomaly induced by the damage and only two of the seven CODSs can be used to detect the locations of the hidden damage.

Metal Magnetic Memory Inspection of Q345 Steel Specimens with Butt Weld in Tensile and Bending Test

Abstract: Metal magnetic memory (MMM) method is a non-destructive testing method based on the analysis of self-magnetic-leakage field (SMLF) distribution on components’ surfaces. The MMM method can determine stress concentration zones, imperfections, and heterogeneity in the microstructure of the material and in welded joints. In order to study the magnetization of defective and non-defective butt welded Q345 steel specimens under tensile and bending loads, the normal component of the SMLF (Hp(y)) field values were measured. The results demonstrate that Hp(y) field values and gradients are effective in capturing different stress states under tensile and bending loads. The distribution of Hp(y) field values for flexural tests are quite different from that of tensile tests. The gradient values can be used to determine the degree of stress concentration. In addition, three characteristic parameters were calculated. All three parameters can predict failures with early warnings. Specifically, whether the specimen is in tensile stress state or in compressive stress state can be distinguished by the average value of Hp(y) field area. The quality of the butt weld can be judged by the magnetic index (m). The judging criteria can be a significant complement to the inspection of welded joints using MMM method. Further research could help to validate the judging criteria and analyse the factors affecting the accuracy of the predictions.

Porosity Determination of Carbon and Glass Fibre Reinforced Polymers Using Phase-Contrast Imaging

Abstract: This paper presents multi-modal image data of different fibre reinforced polymer samples acquired with a desktop Talbot-Lau grating interferometer (TLGI) X-ray computed tomography (XCT) system and compare the results with images acquired using conventional absorption-based XCT. Two different fibre reinforced polymer samples are investigated: (i) a carbon fibre reinforced polymer (CFRP) featuring a copper mesh embedded near the surface for lightning conduction and (ii) a short glass fibre reinforced polymer (GFRP) sample. The primary goal is the non-destructive detection of internal defects such as pores and the quantification of porosity. TLGI provides three imaging modalities including attenuation contrast (AC) due to absorption, differential phase contrast (DPC) due to refraction and dark-field contrast (DFC) due to scattering. In the case of the CFRP sample, DPC is less prone to metal streak artefacts improving the detection of pores that are located close to metal components. In addition, results of a metal artefact reduction (MAR) method, based on sinogram inpainting and an image fusion concept for AC, DPC and DPC, are presented. In the case of the GFRP sample, DPC between glass fibres and matrix is lower compared to AC while DPC shows an increased contrast between pores and its matrix. Porosity for the CFRP sample is determined by applying an appropriate global thresholding technique while an additional background removal is necessary for the GFRP sample.

Evaluation of Different Non-destructive Testing Methods to Detect Imperfections in Unidirectional Carbon Fiber Composite Ropes

Abstract: Online monitoring of carbon fiber reinforced plastic (CFRP) ropes requires non-destructive testing (NDT) methods capable of detecting multiple damage types at high inspection speeds. Three NDT methods are evaluated on artificial and realistic imperfections in order to assess their suitability for online monitoring of CFRP ropes. To support testing, the microstructure and electrical conductivity of a carbon fiber rope is characterized. The compared methods are thermography via thermoelastic stress analysis, ultrasonic testing with commercial phased array transducers, and eddy current testing, supported by tailor-made probes. While thermoelastic stress analysis and ultrasonics proved to be accurate methods for detecting damage size and the shape of defects, they were found to be unsuitable for high-speed inspection of a CFRP rope. Instead, contactless inspection using eddy currents is a promising solution for real-time online monitoring of CFRP ropes at high inspection speeds.

Material Decomposition in X-ray Spectral CT Using Multiple Constraints in Image Domain

Abstract: X-ray spectral CT appears as a new promising imaging modality for the quantitative measurement of materials in an object, compared to conventional energy-integrating CT or dual energy CT. We consider material decomposition in spectral CT as an overcomplete ill-conditioned inverse problem. To solve the problem, we make full use of multi-dimensional nature and high correlation of multi-energy data and spatially neighboring pixels in spectral CT. Meanwhile, we also exploit the fact that material mass density has limited value. The material decomposition is then achieved by using bounded mass density, local joint sparsity and structural low-rank (DSR) in image domain. The results on numerical phantom demonstrate that the proposed DSR method leads to more accurate decomposition than usual pseudo-inverse method with singular value decomposition (SVD) and current popular sparse regularization method with l1-norm constraint.

Evaluation of Meso-damage Processes in Concrete by X-Ray CT Scanning Techniques Under Real-Time Uniaxial Compression Testing

Abstract: Concrete damage characteristics were investigated by X-ray computed tomography (CT) under uniaxial compression, with medical X-ray CT and a loading device used to carry out real-time uniaxial compression scanning tests, obtaining two-dimensional CT images of crack generation, propagation, coalescence, and failure. Damage deterioration of internal structures under different loading conditions was analyzed by means of a digital image-processing technique, which allowed the recognition and extraction of meso cracks. Furthermore, the crack lengths were extracted and measured from CT images. Methods of divisional regions were applied to carry out the quantitative analysis of CT numbers in specific representative regions. The fractal dimensions (FDs) of crack propagation in CT images were estimated using the box-counting dimension, and the relationship between the strain, crack propagation, and FD examined. Complicated and disordered internal cracks were clearly observed with increased load. The results indicated that such CT tests were a promising means for identifying the evolution and propagation of internal cracks and for studying the mesoscopic damage fracture mechanism under uniaxial compression.

New Approach for Verifying the Accuracy of X-ray Computed Tomography Measurements of Surface Topographies in Additively Manufactured Metal Parts

Abstract: Surface topographies of metal additively manufactured components are inherently characterized by the presence of complex surface characteristics that are not accessible by contact or optical measuring techniques. Micro X-ray computed tomography is capable of measuring non-accessible surfaces and micro-scale surface features, including undercuts. In this work, an innovative approach for evaluating the accuracy and establishing the traceability of surface topography measurements obtained by X-ray computed tomography is presented. Reference samples produced by selective laser melting of Ti6Al4V were specifically designed in order to acquire reference cross-sectional surface profiles representing the actual morphology (including re-entrant features) using an imaging probing system. Surface topographies were measured on these samples by using three different techniques: X-ray computed tomography, confocal microscopy and focus variation. Moreover, the effect of different voxel dimensions on the accuracy of surface topography measurements performed by X-ray computed tomography was investigated. Results showed that X-ray computed tomography (at the highest tested resolution) can acquire surfaces and re-entrant features with small deviations with respect to the reference profiles; the deviations were quantified. On the contrary, focus variation and confocal microscopy can measure surfaces obtaining results that are close to the reference profiles only if such surfaces have no undercuts or inaccessible features.

A Multi-scale Fuzzy Measure Entropy and Infinite Feature Selection Based Approach for Rolling Bearing Fault Diagnosis

Abstract: Fuzzy measure entropy (FuzzyMEn) is a recently improved non-linear dynamic parameter for evaluating the signals’ complexity. In comparison with fuzzy entropy (FuzzyEn), which only emphasizes the local characteristics of the signal but neglects its global trend, FuzzyMEn can reflect not only the local but also the global characteristics of the signal. Therefore, by calculating the FuzzyMEn values in different scales, the multi-scale fuzzy measure entropy (MFME) method is put forward in this paper and used for extracting the fault features from vibration signals of rolling bearing. After the feature extraction, the newly developed infinite feature selection (Inf-FS) method is employed to choose the most representative features from the original ones of high dimension. Finally, a new rolling bearing fault diagnosis approach is presented based on MFME, Inf-FS and support vector machine (SVM). The experimental analysis indicates that the presented approach can realize the rolling bearing fault diagnosis effectively.

A Novel Method for Predicting Pixel Value Distribution Non-uniformity Due to Heel Effect of X-ray Tube in Industrial Digital Radiography Using Artificial Neural Network

Abstract: The heel effect in X-ray radiation imaging systems causes a non-uniform radiation distribution on the imaging plane. In this research, a novel method was developed for predicting the pixel value’s non-uniformity due to the heel effect of X-ray tube on the imaging plane using Monte Carlo N particle (MCNP) simulation code and artificial neural network (ANN). At first, an industrial X-ray tube and a computed radiography (CR) image plate were simulated using MCNP. Then, the simulation procedure was benchmarked with an experiment. In the next step, nine images were obtained from the simulation for nine different tube voltages in the range of 100–300 kV. Furthermore, some pixels with tangential and polar angles in the range of 0°–20° and of 0°–180° with respect to the centered pixel were chosen from these nine simulated images in order to train the ANN, respectively. The tube voltage, tangential and polar angles of each pixel were used as the three inputs of the ANN and gray value in each pixel was used as the output. After training, the proposed ANN model could predict the gray value of each pixel on the imaging plane with mean relative error of less than 0.23%. In the last step, the predicted gray value difference between the centered pixel and other pixels was calculated. The great advantage of proposed methodology is providing the possibility of predicting the pixel value’s non-uniformity due to the heel effect of the X-ray tube on the imaging plane for a wide range of the tube voltages and source to film distances independent of the tube current and exposure time. Although the proposed methodology in this paper was developed for a specific X-ray tube and a CR imaging plate, it can be used for every digital radiography system.

Automated Air-Coupled Impact-Echo Testing of a Concrete Bridge Deck from a Continuously Moving Platform

Abstract: The objective of this work was to develop an automated air-coupled impact-echo testing device for mapping the occurrence of delamination in a concrete bridge deck from a continuously moving platform with a fast, repeatable excitation mechanism and algorithms for collecting and analyzing the acoustic data. The apparatus developed in this research included an impactor unit, a moving platform, a microphone for air-coupled sensing, a distance measurement instrument, and signal processing modules. Given the absence of an existing universal threshold for differentiating among intact and delaminated areas using the new device, a delamination detection threshold value was determined in a first field demonstration also involving chain dragging and coring of a concrete bridge deck. While the maps of the air-coupled impact-echo data and chain-dragging data exhibit a high degree of similarity and are highly consistent with the results of coring, a quantitative method of comparison also demonstrates the utility of the new device across a broad range of delamination percentages. Specifically, the results indicate that the percentage of the deck area determined to be delaminated using impact-echo testing was within 3 percentage points of that determined to be delaminated using chain dragging for 10 of the 13 deck test sections, which generally exhibited delamination percentages ranging from 7 to 21%. Finally, testing with the new device was more than seven times faster than chain dragging.

Water Migration in One-Side Heated Concrete: 4D In-Situ CT Monitoring of the Moisture-Clog-Effect

Abstract: Explosive spalling due to fire exposure in concrete structures can lead severe damage and, in the worst case, to premature component failure. For this reason, an in situ investigation of water migration in concrete due to surface heating was undertaken. During these experiments, a miniaturized concrete specimen within a confining and insulating double-hull was subjected to surface heating during simultaneous X-ray computed tomography (CT) scanning. Through the use of subtraction-based image analysis techniques, it was possible to observe and quantify not only drying within areas of the concrete matrix close to the heated surface, but also the migration of moisture to both pore and matrix regions deeper within the specimen. It was also discovered that the correction of CT images for specimen deformation using DVC and variable detector performance using calibrated image filters significantly improved the quality of the results. This clearly demonstrates the potential of X-ray CT for evaluation of other rapid-density-change phenomena in concrete and other building materials.

Evaluation of Acoustic Emission Source Location in Long Steel Pipes for Continuous and Semi-continuous Sources

Abstract: Acoustic emission (AE) is a commercially-available technique used for structural health monitoring in large structures such as pipeline systems. It is a passive technique that relies on AE and can be generated in continuous and/or burst form (semi-continuous), recorded at one or more sensors with known positions. In truly continuous emission, the source has little or no temporal structure, making it difficult to identify the departure time of a source. In this research, the focus of the analysis was to evaluate distortions of AE continuous and semi-continuous sources in time and frequency domains and to examine how attenuation compares with a discontinuous on long steel pipe. Two different methods have generated artificial, relatively white, sources; continuous AE from a compressed air jet, and semi-continuous signals using a solenoid valve to modulate the air jet. Several arrays have been used to study axial and circumferential propagation, and a combination of time (energy-based) and frequency (time-based) domain processing has been used to develop generic approaches for source location. It is concluded that an energy-based technique combining a digital filter applied to the more heavily attenuated spectral component is more effective in location continuous emission, while semi-continuous signals are more effectively dealt with using cross-correlation applied to a less heavily attenuated spectral component to determine the arrival time of a recognizable time segment. Moreover, it has been observed that the distinction between axial and circumferential propagation of AE is less significant in long pipes.

A Modified Time Reversal Method for Guided Wave Based Bolt Loosening Monitoring in a Lap Joint

Abstract: Loss of preload in pretensioned bolts is inevitable. Reliable monitoring of bolt preload is significant to ensure structural reliability and safety. This paper proposes a modified time reversal method for bolt loosening monitoring. In this method, both phase shift and signal amplitude of the focalized wave packet in the reconstructed signal are extracted as tightness indices. To this end, the conventional time reversal method is modified. Initially, for a nominal healthy structure, the conventional time reversal method is performed. The reemitted signal used in this step is recorded as a ‘standard’ reemitted signal. Then, the ‘standard’ reemitted signal is inputted back to the structure for detecting damage. If the structure is damaged, the focalized wave packet in the reconstructed response signal due to the ‘standard’ remitted signal can have both phase shift and peak amplitude difference compared to the focalized wave packet at the healthy state. The main difference between the modified time reversal method and the conventional method is that for all damage cases the proposed method uses the same remitted signal which is recorded for a nominal healthy structure. Numerical and experimental studies are performed to validate the effectiveness of the proposed method for quantitative monitoring of bolt preload in a lap-jointed specimen. The experimental results of the proposed method are compared with those the wave energy dissipation based and the conventional time reversal methods. It is found that the proposed method outperforms the other methods in terms of accuracy and the sensitive range for bolt loosening detection.

Sensitivity and Robustness of Neural Networks for Defect-Depth Estimation in CFRP Composites

Abstract: Carbon fiber reinforced composites are lightweight materials that possess a desirable mechanical performance manifested in high strength to weight ratio. However, due to their anisotropic and low thermal conductive nature; the detection of delamination and impact damages using thermography is still a challenging task. This research paper aims at conducting a comprehensive analysis of the neural network when used as a post-processor to quantify defects depths from thermograms of CFRP; a pulsed thermography inspection routine was used to generate the thermograms. A thorough study is conducted to compare and analyze the effect of the different parameters on the accuracy and the robustness of the neural network outcome. The optimized neural network architecture and hyper-parameters are realized based on the accuracy yields (defect depths estimate). This research explores the (i) network related parameters and the (ii) thermography-data specific factors such as frame rate, number of considered points per defect location, etc.; showing that the robustness of the neural network is found more sensitive to: the network architecture, noise, training hyperparameters and the type, amount and diversity of the training data.

Introduction of a Surface Characterization Parameter Sdrprime for Analysis of Re-entrant Features

Abstract: Producing components using metal additive manufacturing processes, such as powder bed fusion, presents manufacturing and measurement challenges, but also significant opportunities. The as-built surface may include overhanging (re-entrant) features not intentionally included in the design, but that aid in component functionality. In addition, the additive manufacturing process presents opportunities to design and manufacture re-entrant features intentionally. Re-entrant features increase the specific surface area and, in addition, produce mechanical locking to the surface. These re-entrant features may be intended to improve surface performance in areas such as biological cell attachment, coating adhesion, electrical capacitance and battery plate design, fluid flow and material cooling. Re-entrant features may prove difficult or impossible to measure and characterise using conventional line-of-sight surface metrology instrumentation, however the correct measurement of these surfaces may be vital for functional optimisation. X-ray computed tomography does have the ability to image internal and re-entrant features. This paper reports on the measurement of re-entrant features using X-ray computed tomography and the extraction of actual surface area information (including re-entrant surfaces) from sample additively manufactured surfaces. A proposed new surface texture parameter, Sdrprime, is discussed. This parameter is applicable to true 3D data, including re-entrant features, and is intended to relate directly to the component surface functional performance. The errors produced when using line-of-sight instruments and height map parameter generation per ISO 25178-2 to evaluate surfaces that include re-entrant features are discussed. Measurement results for electron beam melting and selective laser melting additively manufactured components, together with simulated structured surfaces, are presented.

Magnetic Barkhausen Effect in Steel Under Biaxial Strain/Stress: Influence on Stress Measurement

Abstract: Experimental investigation of bi-axial steel deformation is presented using new equipment for bi-axial loading. Main conclusion obtained from displayed results is the condition of the invariance of Barkhausen noise intensity relative to any changes of spherical (isotropic) strain/stress tensor, the last being influenced only by material microstructure. This conclusion is supported by independent measurement of Barkhausen noise (BN) intensity on cross-shaped specimens of optimized shape using novel biaxial loading equipment, and tubular specimens like pipe and a balloon loaded by means of oil pressure. Finite Element Modeling (FEM) simulation was also investigated. Thus the BN intensity depends only on the deviatoric (shear) stress tensor value. The presence of this symmetric effect yields too many uncertainties in strain/stress evaluation via BN. Further investigation should identify whether this condition is also present in other magnetic parameters, such as coercive force, remanence, permeability, associated with BN.

Preliminary Experimentation of Fast Neutron Radiography with D-T Neutron Generator at BARC

Abstract: An experimental study on fast neutron radiography (FNR) has been carried out using a laboratory based D-T neutron generator facility at Bhabha Atomic Research Centre (BARC) and initial results are presented. The aim was to develop an FNR system with a moderate intensity neutron source for imaging of specimen containing mixed low-Z and high-Z materials. The experimental set-up consists of a D-T neutron generator, collimator and an EMCCD camera based imaging system. Experiments were carried out with the neutron generator having a source strength of about 2 × 109 n/s and source spot size of 20 mm. To obtain optimum image quality with such a moderate neutron yield, a collimator has been designed having an inlet aperture of 10 mm and an L/D of 43. The imaging system was kept at an optimum distance from the collimator and various test samples of materials ranging from low Z to high Z were imaged. Thick samples in step wedge form, hole features in step wedge of polyethylene, mild steel and lead were imaged and analysed. Also a test sample of a low Z material (HDPE) with a hole placed behind a thick Pb was imaged to study the effect of thickness of high Z material on image quality with fast neutrons. The initial results emphasizes that a moderate yield D-T neutron generator based fast neutron radiography system with EMCCD camera could be deployed for field applications yielding moderate image quality to obtain first hand information of the investigated samples.

Evaluation of Vertical Fatigue Cracks by Means of Flying Laser Thermography

Abstract: The present paper proposes a new procedure to analyze the temperature field distribution during Flying Laser Spot and Laser Line Thermographic scanning (FLST, FLLT) of metallic components, in order to detect vertical surface cracks. The methodology exploits the changes in the temperature field produced by a vertical crack, acting as a barrier towards heat diffusion, when the laser approaches the defect. A number of small regions of interests (ROIs) is placed nearby and around the laser source. The average temperature from each ROI is then monitored during the laser scanning. Vertical cracks can be detected by analyzing and comparing the temperature fluctuations from each ROI when the laser crosses a crack. The paper, in particular, illustrates how the use of multiple ROIs, placed at different locations, may provide additional information that can be used to characterize the defect, and to identify the crack tip location. The approach is validated on plates made of steel and aluminum alloy, where natural cracks have been introduced by fatigue loading, and whose surface has been painted to enhance emissivity. Scratches in the paint have been artificially made in order to analyze their influence on the defect signature. The proposed experimental setup is further simplified by moving the plate samples, mounted on slits, in front of a still laser source and camera head.

Characterization of Aging Treated 6061 Aluminum Alloy Using Nonlinear Rayleigh Wave

Abstract: The mechanical properties of 6061 aluminum alloys can be enhanced by appropriate heat treatment, but strongly weakened due to over-aging treatment. In this work, the material properties of aged 6061 aluminum alloys are nondestructively evaluated using nonlinear Rayleigh waves. Nonlinear Rayleigh wave experiments are performed on these aluminum specimens through long distances (c.a. 150 mm) to measure the velocity, attenuation and nonlinear parameter simultaneously. The wave velocity is calculated using the time-of-flight method, and the attenuation coefficient is extracted using a data fitting method. By taking into account the effects of diffraction, attenuation and source nonlinearity, the nonlinear parameter is measured. The results show that the nonlinear parameters have a positive correlation with the hardness, which is associated with the precipitate sequence due to aging treatment. It is also found that the Rayleigh wave attenuation is an effective indicator for monitoring the changes of the material microstructures. A technique is developed for evaluating material properties using multiple parameters of nonlinear Rayleigh waves, and its efficacy is verified through experiments.

Detection of Internal Defects in Carbon Fiber Reinforced Plastic Slabs Using Background Thermal Compensation by Filtering and Support Vector Machines

Abstract: Composite materials, such as Carbon-Fiber-Reinforced Plastic (CFRP), are used in many industries because they have advantages over more traditional materials. However, CFRPs may have structural flaws, because mechanical stress or manufacturing process, that represent an important risk for the safe operation of CFRP-made structures. This study analyzes the performance in detection of internal defects, by means of training and operating Support Vector Machines (SVM) with thermal contrast information obtained from Background Thermal Compensation by Filtering (BTCF) technique. IR images were obtained by using an Active Pulsed Thermography (PT) system, under two different conditions, for inspection of a 20 × 20 cm CFRP slab with 25 squared Teflon insertions as emulated defects. Detection results show that the combination of BTCF contrast technique and SVM classifier leads to a greater sensibility (22 of 23 defects considered) than other combinations of thermal contrast, feature selection and classifiers proposed in previous works.

Estimating Fatigue Damage of Austenitic Steel by Combining the Ultrasonic with Eddy Current Monitoring

Abstract: We propose a non-destructive testing methodology of estimating fatigue damage in austenitic stainless steel (prior to formation of macrocracks) that is based on monitoring changes in the effective elastic properties (more precisely, the Poisson’s ratio) due to microstructural damage. The elastic properties are also affected by growth of the martensitic phase, and the problem arises of separating the two factors. This is achieved by a combination of (1) measuring Poisson’s ratio with four-digit accuracy by ultrasonic devices, and (2) estimating volume fraction of the martensitic phase by the eddy current method. It is suggested that the critical value of the change of the Poisson’s ratio due to microstructural damage can be used as a criterion of failure.