Showing papers in "Insight in 2010"
TL;DR: In this paper, the design, development and optimisation of a PEC thermography inspection system is detailed, including coil design for global and local heating of samples, optimization of excitation parameters (frequency, power, pulse duration etc) and camera selection.
Abstract: There is a need for fast and efficient techniques to inspect engineering structures and complex components such as aircraft turbine blades to identify potential sites of failure. Pulsed eddy current (PEC) thermography is a new inspection technique which allows the user to capture the eddy current distribution in a component or structure using infrared imaging and detect defects over a relatively wide area. The technique is applicable to materials with a reasonable level of electrical conductivity and has the ability to detect defects under coatings. However, PEC thermography has received relatively little attention compared to other thermographic inspection techniques. In this paper, the design, development and optimisation of a PEC thermography inspection system is detailed, including coil design for global and local heating of samples, optimisation of excitation parameters (frequency, power, pulse duration etc) and camera selection. The system is used to inspect several real-world samples, using different coil designs, and the results are assessed using newly developed feature extraction techniques. The work shows that with judicious coil design and selection of excitation parameters, PEC thermography can be used to obtain quantitative information for defect characterisation through analysis of the surface heating pattern and the transient temperature change.
63 citations
TL;DR: In this paper, the most observable parts of the track such as the rails, rail pads, concrete sleepers and fastening systems are referred to as superstructure, while the substructure is associated with a geotechnical system consisting of ballast, sub-ballast and subgrade.
Abstract: Rail track is a fundamental part of railway infrastructure. Its components can be classified into two main categories: superstructure and substructure. The most observable parts of the track such as the rails, rail pads, concrete sleepers and fastening systems are referred to as superstructure, while the substructure is associated with a geotechnical system consisting of ballast, sub-ballast and subgrade. The dynamic testing of railway track and its components, particularly concrete sleepers and rail pads, can lead to the dynamic model updating for numerical analysis and an alternative experimental set-up to get a better insight into rail track behaviour. The new results obtained can be used as a benchmark for health monitoring of a modern railway track and its components.
57 citations
TL;DR: The GEOSS is already starting to generate a variety of comprehensive, cross-cutting and near-real-time environmental data sets and information services.
Abstract: The Global Earth Observation System of Systems (GEOSS) promises to revolutionize our ability to understand and manage the planet. This emerging global public infrastructure will allow managers and decision makers to respond more effectively to the many environmental challenges facing modern civilization. It is already starting to generate a variety of comprehensive, cross-cutting and near-real-time environmental data sets and information services. GEOSS is being constructed on the basis of a 10-Year Implementation Plan for the period 2005 – 2015 by the Group on Earth Observations (GEO), which currently boasts 77 member governments (plus the European Commission) and 56 international organizations.
53 citations
46 citations
TL;DR: In this article, the authors highlight correlation processing-based detection capabilities of frequency modulated thermal wave imaging techniques through finite element modelling and simulations on a steel sample having flat-bottom blind holes as defects.
Abstract: Active thermal non-destructive testing (TNDT) methods utilise an acquired surface temperature profile over the object and subsequently process the obtained temperature data to detect surface or sub-surface features of the object. Presently, two phase-based conventional active TNDT methods are predominantly in use: pulsed phase thermography (PPT) and modulated lock-in thermography (LT). This paper highlights correlation processing-based detection capabilities of frequency modulated thermal wave imaging techniques through finite element modelling and simulations on a steel sample having flat-bottom blind holes as defects. The present work proposes a finite element-based simulation for comparison of the widely-used conventional thermal imaging methods (PPT and LT) with more recently proposed non-stationary excitation approaches for non-destructive characterisation.
34 citations
TL;DR: This work proposes a method based on the direct multiclass support vector machine (DMSVM) to classify the defect, which has good generalisation under the circumstances of a small training set and suggests four new features to characterise the defect to greatly improve the separability of the feature group.
Abstract: There are two problems that affect the accuracy of defect classification for automated radiographic NDT. One is the poor generalisation of the classification method led by a small training sample or an improper classifier, and the other is the poor separability of the feature group. To solve the former, we propose a method based on the direct multiclass support vector machine (DMSVM) to classify the defect, which has good generalisation under the circumstances of a small training set. To tackle the latter, we suggest four new features (three of them are based on the defect region) to characterise the defect, which greatly improve the separability of the feature group. Three classifiers (one-versus-rest SVM, one-versus-one SVM and MLP neuron network) and a group of feathers are used to compare with the classifier and the feature group we proposed. The bootstrap estimate is used to estimate their performances. The experimental results demonstrate that the bootstrap accuracy estimate of DMSVM is 94.25%, which is higher than that achieved by the three compared classifiers. Moreover, the separability of the suggested feature group is equivalent to that of the counterpart but with a two-thirds size, and the computation time is cut by 22.17%.
25 citations
TL;DR: In this article, the extent of impact damage inflicted on composite panels designed and manufactured for structural applications in the aerospace industry was investigated using optical non-destructive testing methods such as Digital Shearography, Electronic Speckle Pattern Interferometry and Infrared Thermography.
Abstract: The paper presents the work that was carried out in the detection and, beyond of what is obviously visible to the naked eye, the extent of impact damage inflicted on composite panels designed and manufactured for structural applications in the aerospace industry. Using a drop-weight impact tester the composite specimens were subjected to controlled impact conditions i.e. relatively low velocity impact levels analogous to those expected from the drop of a heavy tool, collision with a bird etc. The composite specimens consisted of Monex core sandwiched between thin carbon/glass fibre reinforced plastic skins, typically identical to those used in the fabrication of unmanned air vehicles and helicopter rotor blades. The investigation attempted to establish the probability of detecting such barely visible impact damage with optical non-destructive testing methods such as Digital Shearography, Electronic Speckle Pattern Interferometry and Infrared Thermography. These NDT techniques were chosen to be employed in this study, because they are non-contacting, whole field, not limited to particular material types, provide fast and easy results in real-time and have been proven reliable in a large number of applications in the laboratory/factory/field environment.
25 citations
TL;DR: In this article, the wavelet transform and texture analysis were employed for de-noising and enhancing the quality of data to help in the automatic detection and classification of defects in ultrasonic time-of-flight diffraction data.
Abstract: Ultrasonic time-of-flight diffraction (TOFD) is known as a reliable non-destructive testing technique for the inspection of welds in steel structures, providing accurate positioning and sizing of flaws. The automation of data processing in TOFD is required towards building a comprehensive computer-aided TOFD inspection and interpretation tool. A number of signal and image processing tools have been specifically developed for use with TOFD data. These tools have been adapted to function autonomously, without the need for continuous intervention through automatic configuration of the critical parameters according to the nature of the data and the acquisition settings. This paper presents several multi-resolution approaches employing the wavelet transform and texture analysis for de-noising and enhancing the quality of data to help in the automatic detection and classification of defects. The automatic classification is implemented using a support vector machines classifier, which is considered faster and more accurate than artificial neural networks. The results achieved so far have been promising in terms of accuracy, consistency and reliability.
24 citations
TL;DR: This paper presents an intelligent method for fault diagnosis of the starter motor of an agricultural tractor, based on vibration signals and an Adaptive Neuro-Fuzzy Inference System (ANFIS), which has great potential to serve as an intelligent fault diagnosis system in real applications.
Abstract: This paper presents an intelligent method for fault diagnosis of the starter motor of an agricultural tractor, based on vibration signals and an Adaptive Neuro-Fuzzy Inference System (ANFIS). The starter motor conditions to be considered were healthy, crack in rotor body, unbalancing in driven shaft and wear in bearing. Thirty-three statistical parameters of vibration signals in the time and frequency domains were selected as a feature source for fault diagnosis. A data mining filtering method was performed in order to extract the superior features among the primary thirty-three features for the classification process and to reduce the dimension of features. In this study, six superior features were fed into an adaptive neuro-fuzzy inference system as input vectors. Performance of the system was validated by applying the testing data set to the trained ANFIS model. According to the result, total classification accuracy was 86.67%. This shows that the system has great potential to serve as an intelligent fault diagnosis system in real applications.
24 citations
TL;DR: In this paper, the application of Thermosonics as a screening technique for identifying cracked aero engine turbine blades is described, which is a rapid and potentially, a cost-saving non-destructive testing (NDT) technique for rejecting cracked turbine blades as part of the regular inspection cycle.
Abstract: The application of Thermosonics as a screening technique for identifying cracked aero engine turbine blades is described. Thermosonics is a rapid and potentially, a cost-saving non-destructive testing (NDT) technique for rejecting cracked turbine blades as part of the regular inspection cycle. However, there remains a question over the reliability of the Thermosonic approach. The aim of this work is to assess the reliability of Thermosonics as a screening method for cracks in turbine blades. This work involved the use of 60 turbine blades with known cracks. First, a repeatability study was conducted on a subset of the 60 blades to establish a robust and repeatable experimental procedure, after which all 60 blades were inspected. Results from this work showed the experimental process to be robust and also that the known cracks in 52 out of the 60 blades were detected.
22 citations
TL;DR: The proposed method combines, simultaneously, information gathered from multiple views of the scene; this does not require searching for correspondences or matching and yields promising results: 94% of true positives detected with 95% sensitivity in real flaws.
Abstract: Recently, X-rays have been adopted as the principal non-destructive testing method to identify flaws within an object that are undetectable to the naked eye. Automatic inspection using radiographic images has been made possible by incorporating image processing techniques into the process. In a previous work, we proposed a framework to detect flaws in aluminium castings using multiple views. The process consisted offlaw segmentation, matching andfinally tracking the flaws along the image sequence. While the previous approach required effective segmentation and matching algorithms, this investigation focuses on a new detection approach. The proposed method combines, simultaneously, information gathered from multiple views of the scene; this does not require searching for correspondences or matching. By gathering all the projections from a 3D point, obtained from a sliding box in the 3D space, we train a classifier to learn to detect simulated flaws using all the evidence available. This paper describes our proposed method and presents its performance record in flaw detections using various classifiers. Our approach yields promising results: 94% of true positives detected with 95% sensitivity in real flaws. We conclude that simultaneously combining information from different points of view is a robust approach to flaw identification.
TL;DR: In this paper, the authors present a review of recent developments in electromagnetic and thermoelectric materials characterisation and offers a feasibility assessment of these non-destructive methods through a couple of representative examples of broad interest.
Abstract: Electromagnetic, thermoelectric and other non-destructive evaluation methods offer unique opportunities for materials’ state awareness monitoring. A variety of sensors can be built based on these principles to detect and quantitatively characterise subtle environmentally-assisted and/or service-related changes in the state of metals, such as microstructural evolution, phase transformation, plastic deformation, hardening, residual stress relaxation, increasing dislocation density, etc. In most cases, the detection sensitivity is sufficiently high for the purposes of materials’ state awareness monitoring and the feasibility of the sensing method is mainly determined by its selectivity, or the lack of it, to a particular type of damage mechanism. This paper reviews recent developments in electromagnetic and thermoelectric materials characterisation and offers a feasibility assessment of these non-destructive methods through a couple of representative examples of broad interest.
TL;DR: Techniques for the SoS attribute combination modeling within the Multi-Attribute Tradespace Exploration method when considering SoS with heterogeneous component systems are introduced.
Abstract: One of the principal value propositions for the creation of Systems of Systems (SoS) is the ability to generate stakeholder value beyond that which can be delivered by a single system or even a collection of systems. The dynamic interactions among the component systems in a SoS make conceptual design decisions for SoS more complex compared to traditional system design. There are several heuristics and qualitative guidelines for designing SoS in the literature, but there is a lack of practical quantitative methods for SoS concept exploration. Development of quantitative methods for SoS conceptual design will greatly improve the ability of decision makers to select SoS designs in the concept design phase that will be value robust over time, by allowing them to consider a larger and more complete set of possible alternative SoS designs than is possible with qualitative methods alone. Multi-Attribute Tradespace Exploration has been used in the past to compare large numbers of system alternatives on a common cost-utility basis. In this method, the designer elicits the decision maker’s needs and formulates these as quantified attributes. The systems are then analyzed in terms of their ability to achieve the desired levels of attribute metrics. SoS-level attribute calculations must reflect component system interactions and emergent SoS-level value, as well as the added costs and benefits in the SoS as compared to that of the component systems operating alone. This paper introduces techniques for the SoS attribute combination modeling within the Multi-Attribute Tradespace Exploration method when considering SoS with heterogeneous component systems. Combining the attributes for the SoS-level must take into account the nature of the attributes provided by the component systems as well as the concept of operations for SoS. The techniques used for SoS attribute combination are classified according to the level of coordination between the component systems in the SoS. Using the information about the complexity of the method required along with knowledge about the control structure in the SoS, the SoS architect can estimate the added SoS integration costs. The ability to combine attributes contributes an essential constituent for the extension of the tradespace exploration methodology from the single system to the SoS level, allowing for the comparison of many SoS alternatives on a common cost-utility basis.
TL;DR: This paper starts with positioning reference architectures relative to architecture frameworks, architecting methods and techniques, and tools, and focuses on attempts to mine information from past architectures by studying produced artefacts as well as by interacting with the people involved.
Abstract: Reference architectures are seen as one of the means to cope with increased organization size, distributed development, increased integration, increased performance and functionality, and ever faster changes in the market. Our research project Darwin is aimed at evolvability of product families, where reference architecture is one of the research subjects. In this paper we start with positioning reference architectures relative to architecture frameworks, architecting methods and techniques, and tools. Then we focus on our attempts to mine information from past architectures by studying produced artefacts as well as by interacting with the people involved. We explain that it is a long way from detailed facts found in the artefacts to conceptual diagrams that capture the domain essence and that could guide future architectural developments. We illustrate this by discussing two of the smaller research projects in some more detail.
TL;DR: In this paper, the authors used Comsol multiphysics to model metal-coated samples and verified the model with experiments with metal-collected samples, showing that accuracy of sizing is decreased, depending on coating thickness and whether the crack penetrates through the conductive coating or not.
Abstract: ACFM is an electromagnetic NDT technique used to inspect metal structures for surface-breaking cracks, through a variety of non-conductive coatings. However, if the coating is conductive, such as flame-sprayed aluminium or zinc galvanising, the electromagnetic surface properties of the structure are altered. These metallic coatings were modelled using Comsol multiphysics, and the model verified by experiments with metal-coated samples. The results show that accuracy of sizing is decreased, depending on coating thickness and whether the crack penetrates through the conductive coating or not. If the metal coating thickness is too thick, then defects may be completely masked.
TL;DR: In this paper, the authors present an experimental evidence that hardness of rolled martensitic steel can be evaluated based on the measurements of ultrasonic wave velocity and limited information of its chemical composition.
Abstract: Material properties such as strength, toughness or hardness are usually determined by destructive tests. However, continuous destructive measurements are generally difficult to perform during the production process, which creates a need for a fast and easy non-destructive method of material characterisation. Material elastic parameters, such as Young’s modulus, bulk modulus etc, can be directly evaluated using non-destructive methods based on the measurements of ultrasonic wave velocity (shear and longitudinal). However, strength or hardness cannot be determined directly from those parameters since they also depend on material microstructure, such as grain size and orientation, as well as other factors. This paper presents an experimental evidence that hardness of rolled martensitic steel can be evaluated based on the measurements of ultrasonic wave velocity and limited information of its chemical composition.
TL;DR: The use of probability of detection curves to quantify NDT reliability is common in the aeronautical industry, but relatively less so in the nuclear industry, at least in European countries as discussed by the authors.
Abstract: The use of probability of detection curves to quantify NDT reliability is common in the aeronautical industry, but relatively less so in the nuclear industry, at least in European countries. The main reason for this lies in the very nature of the components being inspected. Sample sizes of inspected flaws tend to be much lower and it is often very difficult to procure or manufacture representative flaws in test-pieces in a high enough number to draw statistical conclusions on the reliability of the NDT system being investigated. Similar considerations led to the development of the ENIQ inspection qualification methodology, based on the idea of the technical justification, ie a document assembling evidence and reasoning providing assurance that the NDT system is indeed capable of finding the flaws which it is designed to detect. The ENIQ methodology has become widely used in many European countries and is gaining appreciation outside Europe as well, but the assurance it provides is usually of a qualitative nature. The need to quantify the output of inspection qualification has become more and more important, especially as structural reliability modelling and quantitative risk-informed in-service inspection methodologies become more widely used. To credit the inspections in structural reliability evaluations, a measure of the NDT reliability is necessary. A probability of detection (POD) curve provides such metric. The purpose of this paper is to briefly review the statistical models proposed to quantify NDT reliability, to highlight the potential problems that can arise if the main underlying assumptions and requirements are not verified and to clarify the confusion that can arise over the nature of the POD curve and associated confidence bounds.
TL;DR: In this article, a wavelet diagnostic technology is applied and validated for early detection/diagnosis of local tooth damage in a back-to-back gearbox and an advanced automatic decision-making technique based on the likelihood ratio is used for damage diagnosis.
Abstract: Novel wavelet diagnostic technology is applied and validated for early detection/diagnosis of local tooth damage in a back-to-back gearbox. An advanced automatic decision-making technique based on the likelihood ratio is used for damage diagnosis. Novel results in worldwide terms have been achieved: an early effective detection/diagnosis of micro-pitting in gears with relative pitting size 0.3 ― 0.7%.
TL;DR: In this article, a case-hardened steel was used to simulate the heat generation during grinding between the grinding wheel and the workpiece, and the results showed that laser processing had a clear effect on the BN features and residual stresses.
Abstract: Barkhausen noise (BN) is widely used as a quality control method for grinding burn detection in ferromagnetic materials such as the case-hardened steels used in gears. The study of grinding burns with BN equipment requires, however, a calibration reference sample with a known BN response. The demand for better calibration samples is well recognised. In this study, artificial grinding burns with laser processing were produced in case-hardened steel. The laser was selected because it is a surface-sensitive heating method and it accurately simulates the heat generation during grinding between the grinding wheel and work-piece. A test series was made by changing the laser input power and traverse rate to process the surface of a ground gear wheel sample. The laser-processing parameters were optimised experimentally. The BN measurement data was used in the modelling of selected quality measures: hardness and residual stress (RS). The BN measurement device provided some features from the time-domain analysis of the signal and a new feature, BN entropy, was also used. The modelling was done with Matlab® using linear regression. The results showed that laser processing had a clear effect on the BN features and residual stresses.
TL;DR: In this article, an advanced non-destructive evaluation technique based on a thermal method and lock-in principles, known as thermoelastic stress analysis (TSA), is proposed for accurate stress measurements.
Abstract: An advanced non-destructive evaluation technique based on a thermal method and lock-in principles, known as thermoelastic stress analysis (TSA), is proposed for accurate stress measurements. Traditionally, strain gauges mounted on components of interest are used to measure stresses indirectly. In this paper, we describe the application of a thermoelastic stress analysis technique to a carbon-epoxy composite sample under dynamic loading to measure stresses. The advantages of this technique over strain gauges are described. The paper also describes methods for mapping of TSA results on CAD models and comparing the stresses with results obtained through finite element modelling.
TL;DR: In this paper, a model of wave propagation in anisotropic media is used to correct an ultrasonic imaging algorithm to enable the reliable volumetric inspection of single-crystal aerospace components.
Abstract: Two-dimensional (2D) ultrasonic arrays for non-destructive evaluation will enable the detection and characterisation of sub-surface defects in three-dimensions (3D). This type of volumetric inspection is desirable when testing engineering components that have an inherent 3D internal structure or may contain defects orientated at a range of angles. One potential industrial application for this technology is the in-situ inspection of jet-engine turbine blades for root cracking. However, modern turbine blades are manufactured from single crystals of nickel-based superalloys for the excellent mechanical properties these materials exhibit at elevated temperatures. Single-crystal materials are elastically anisotropic, which causes ultrasonic waves to propagate with different velocities depending on the direction of the wave. If unaddressed, this significantly reduces the quality of the inspection and the 3D images that can be produced with an ultrasonic array. In this paper, a model of wave propagation in anisotropic media is used to correct an ultrasonic imaging algorithm to enable the reliable volumetric inspection of single-crystal aerospace components.
TL;DR: A number of Research Grand Challenges in systems engineering are proposed in order to inspire a research agenda for systems engineering and show the need for optimal integration of people, processes and technologies.
Abstract: Systems engineering is rapidly becoming recognised as a key discipline in a number of sectors including Aerospace & Defence, Automotive, Construction, Energy, Transportation, Consumer Electronics, IT, Pharmaceutical & Healthcare and Telecommunications. This trend is driven by growing system complexity and the need for optimal integration of people, processes and technologies. Consequently, the shear scale of future system complexity is likely to exceed our current understanding of systems engineering and the associated tools/techniques we employ. The number of overall system parameters to be controlled as part of the overall design process (as various system optimisations are undertaken) is likely to be overwhelming. Whilst systems engineers will be expected to manage system complexity the underpinning understanding of systems science, technology and tools must evolve to take account of the increasing systems complexity. Unless enabling research is undertaken there is a growing risk that available tools will be inadequate for the future. This paper builds on feedback from numerous research presentations, industry discussions (across different sectors) and various subject matter expert data collection exercises. From this work it has been possible to propose a number of Research Grand Challenges in systems engineering in order to inspire a research agenda for systems engineering. In this context, a Research Grand Challenge pursues a series of goals that are recognised as being one or two decades in advance; their achievements are regarded as major milestones or breakthroughs in the advancement of knowledge or technology.
TL;DR: In this paper, a modified impulse-echo approach is used to detect and assess the level of wood decay in glulam beams using a beam retired from the field and without visible indications of decay.
Abstract: Afeasibility study to evaluate the use of a modified impulse-echo approach to detect and assess the level of wood decay in glulam beams is presented using a beam retired from the field and without visible indications of decay. The modified impulse-echo approach is based on observing the dynamic response of each of the glulam beam laminae to the drop of a steel sphere onto a steel plate coupled to the glulam beam lamina, and upon a decay rate analysis of the corresponding time domain signal in a frequency band of interest. X-ray computer tomography was used to evaluate the level of deterioration, ie mass loss, caused by decay in each of the laminae of the beam and to validate the results obtained using the modified impulse-echo. It was observed that the impulse-echo decay rate approach leads to an overall rate of false calls of 7.2%. Considering the variability that exists in wood, including the presence of splits, orientation and thickness of growth rings, and humidity, this relative low rate of false calls makes this approach very attractive.
TL;DR: In this paper, the authors compared the defect detection capabilities of transient thermography and shearography using optimum excitation methods for each technique: short pulse heating for thermography, and vibration excitation using a piezoelectric transducer for shearograph.
Abstract: The defect detection capabilities of transient thermography and shearography have been compared using optimum excitation methods for each technique: short pulse heating for thermography and vibration excitation using a piezoelectric transducer for shearography. A signal-to-noise ratio and limit of detection analysis has been performed on defect images obtained by the two techniques using the different excitation methods. Test samples considered in this paper are flat-plate samples made from aluminium, mild steel, stainless steel, CFRP and thermoplastic, containing flat-bottomed hole artificial defects of 20mm diameter at depths ranging from 0.5mm to 3.0mm. The technique of flash thermography involves using a short duration (~1ms) high intensity flash of light to heat the surface of a test piece. The test piece surface temperature is recorded by an infrared camera and computer system as it decays due to heat being conducted into the part after its deposition on the surface. Sub- surface defects reduce the conduction of heat away from the surface and therefore reduce the surface cooling rate compared to that occurring over non-defective regions. Consequently, a surface temperature contrast develops over a defect that can be used to detect a defective region. Shearography, otherwise known as shearing speckle interferometry, is a technique that uses interferometry to measure the out of plane displacement gradient of a sample's surface. The presence of defects will alter the way in which a sample reacts to an applied stress (in this case created by vibrating the test sample) and this change can be observed using shearography thereby inferring the presence of the defect. In shearography a speckle pattern is applied to the surface of the test sample and the sample is illuminated using expanded collimated (i.e. laser) light. The light is reflected diffusely from the surface of the sample and passes through a lens and shearing device to be recorded by a video camera and processed. The shearing device acts to slightly change the path of half of the rays of light reflected by the speckles, causing the reflected light from neighbouring speckles to overlap and produce an image sheared in the shearing direction. A reference sheared image is stored with the sample in an unstressed condition and the sample is then stressed. The stressing can take many forms, mechanical strain (e.g. with a vacuum hood or by applying a bending load with a clamp), thermal stress (generated by heating or cooling the sample), or vibration excitation (using a piezoelectric transducer as is the case in this testing). A second sheared image is recorded with the sample in the stressed state, and the interferometric superposition of these two images creates an interferogram that represents the phase difference of neighbouring speckle sources. From this phase difference the gradient of the surface displacement can be calculated.
TL;DR: In this paper, the authors present techniques developed for the automatic sizing and positioning of weld flaws in TOFD data as an essential stage in a comprehensive TOFD inspection and interpretation system to aid the operator by automating the processing and interpretation.
Abstract: Despite the recent popularity of ultrasonic time-of-flight diffraction (TOFD) as a reliable non-destructive testing technique for the inspection of weld defects in steel structures, the critical stages of data processing and interpretation are still performed offline manually. This depends heavily on the skill, experience, alertness and consistency of a trained operator. The TOFD data acquisition and display configurations themselves may introduce a host of errors that cannot be accounted for by manual interpretation. This paper presents techniques developed for the automatic sizing and positioning of weld flaws in TOFD data as an essential stage in a comprehensive TOFD inspection and interpretation system to aid the operator by automating the processing and interpretation. Data manipulation and post-processing techniques have been specifically developed for the automatic detection and sizing of weld defects in TOFD data, significantly reducing the sizing and positioning errors. The system is designed to function autonomously without the need for user intervention, relying instead on information derived from the raw data and the data acquisition parameters. This defect sizing process generates, in near real-time, a quality appraisal of a scanned weld, detailing the location and dimensions of all detected flaws. The results achieved so far have been promising in terms of accuracy, consistency and reliability.
TL;DR: In this article, a thin-film low-profile sensors for ultrasonic condition monitoring is presented. But the sensors are made by growing a thin film of aluminium nitride onto the component to be monitored, and the transducers can operate in passive or active mode from 200 kHz to 400 MHz.
Abstract: Thin-film low-profile sensors have been investigated for ultrasonic condition monitoring. The sensors are made by growing a thin film of aluminium nitride onto the component to be monitored. The transducers can be engineered to operate in passive or active mode from 200 kHz to 400 MHz. New or existing applications based on ultrasonic pulse-echo techniques or acoustic emission testing can make use of the sensors, including monitoring of high-temperature plant or machinery. The sensors have been demonstrated on various component materials such as stainless steel, ferritic steel, aluminium, titanium and silicon carbide. The piezoelectric material used, aluminium nitride, has a very high Curie temperature so the devices can be used up to 600°C. Examples are presented of devices operating in pulseecho and passive detection modes, which could be used for permanent monitoring of parts which would normally require maintenance outage in order to be inspected. In addition, because the typical thin-film transducers are only 8-40 µm thick, sensors can be placed in locations previously impossible to access. The operating frequency of the thinfilm devices has been investigated by simulation using an equivalent circuit model.
TL;DR: In this article, the performance of existing ultrasonic and magnetic flux leakage techniques in detecting rail surface-breaking defects such as head checks and gauge corner cracking is inadequate during high-speed inspection, while eddy current sensors suffer from lift-off effects.
Abstract: The performance of existing ultrasonic and magnetic flux leakage techniques in detecting rail surface-breaking defects such as head checks and gauge corner cracking is inadequate during high-speed inspection, while eddy current sensors suffer from lift-off effects. Early detection of such rail defects is of paramount importance since a single crack can potentially lead to fatigue failure. The results obtained through rail inspection experiments under simulated conditions using an alternating current field measurement (ACFM) micro-pencil probe suggest that this technique can be applied for the accurate and reliable detection of surface-breaking defects at high inspection speeds.