Search

This work presents an overlook on a new model that simulates the physical operation in steady state of a multi-effect distillation (MED) plant with parallel-feed (P) configuration. This model includes the consumption of steam with steam ejectors, and its validation was done using data from a real MED industrial plant using a thermal vapor compressor (TVC) operating in Italy, in the Sicilian city of Trapani. Results show that the MED model returns accurate predictions of the plant behavior, very useful for a first analysis on such type of investments. This MED model was also integrated into the system advisor model developed by the US National Renewable Energy Laboratory. Simulations with this new tool were run using the location of Trapani as case study for a concentrating solar power (CSP) plant working in cogeneration with a low-temperature MED-P plant vs. other cooling options available for CSP plants (wet cooling, dry cooling, and a once through seawater cooling circuit). These results were compared with the existing TVC-MED plant, and indicate that CSP+MED has the potential to be economically attractive.

Ultrasound undergoes refraction and reflection at interfaces between media of different acoustic refractive indices. The most common ultrasonic method (pulse-echo) monitors the reflected energy to infer the presence of flaws, whereas the lower amplitude of refracted signals is ignored. When the reflector is orientated normally with respect to the ultrasonic beam, the received echo signal shows the maximum amplitude. The pulse-echo method also relies on monitoring the amplitude of the backwall echo to identify or confirm the presence of defects. This works well for parts with constant thickness and with planar backwalls. Unfortunately, parts with complex backwalls are common to many industrial sectors. For example, applications such as aerospace structures often require parts with complex shapes. Assessing such parts reliably is not trivial and can cause severe downtime in the aerospace manufacturing processes or during in-service inspections. This work aims to improve the ultrasonic inspectability of parts with complex backwalls, through sending ultrasonic beams from the frontwall side. Ultrasonic phased array probes and state-of-the-art instrumentation allow ultrasonic energy to be sent into a part at wide ranges of focusing depths and steering angles. This allows for tracking of the backwall profile, thus hitting it normally and maximising the amplitude of the reflected echo at any point. However, this work has shown that a cross-sectional scan resulting from multiple ultrasonic beams, which are sent at variable incidence angles, can present significant geometrical distortion and cannot be of much use for accurate defect visualisation and sizing. This paper introduces a generalised algorithm developed to remove geometric distortions and the effect that variable refraction coefficients have on the transmitted and received amplitudes. The algorithm was validated through CIVA simulations for two example parts with complex backwalls, considering isotropic materials.

Composite materials are widely used in industry due to their light weight and specific performance. Currently, composite manufacturing mainly relies on manual labour and individual skills, especially in transport and lay-up processes, which are time consuming and prone to errors. As part of a preliminary investigation into the feasibility of deploying autonomous robotics for composite manufacturing, this paper presents a case study that investigates a cooperative mobile robot and manipulator system (Co-MRMS) for material transport and composite lay-up, which mainly comprises a mobile robot, a fixed-base manipulator and a machine vision sub-system. In the proposed system, marker-based and Fourier transform-based machine vision approaches are used to achieve high accuracy capability in localisation and fibre orientation detection respectively. Moreover, a particle-based approach is adopted to model material deformation during manipulation within robotic simulations. As a case study, a vacuum suction-based end-effector model is developed to deal with sagging effects and to quickly evaluate different gripper designs, comprising of an array of multiple suction cups. Comprehensive simulations and physical experiments, conducted with a 6-DOF serial manipulator and a two-wheeled differential drive mobile robot, demonstrate the efficient interaction and high performance of the Co-MRMS for autonomous material transportation, material localisation, fibre orientation detection and grasping of deformable material. Additionally, the experimental results verify that the presented machine vision approach achieves high accuracy in localisation (the root mean square error is 4.04 mm) and fibre orientation detection (the root mean square error is 1.84∘) and enables dealing with uncertainties such as the shape and size of fibre plies.

Composite materials are widely used because of their light weight and high strength properties. They are typically made up of multi-directional layers of high strength fibres, connected by a resin. The manufacturing of composite parts is complex, time-consuming and prone to errors. This work investigates the use of robotics in the field of composite material manufacturing, which has not been well investigated to date (particularly in simulation). Effective autonomous material transportation, accurate localization and limited material deformation during robotic grasping are required for optimum placement and lay-up. In this paper, a simulation of a proposed cooperative robotic system, which integrates an autonomous mobile robot with a fixed-base manipulator, is presented. An approach based on machine vision is adopted to accurately track the position and orientation of the fibre plies. A simulation platform with a built-in physics engine is used to simulate material deformation under gravity and external forces. This allows realistic simulation of robotic manipulation for raw materials. The results demonstrate promising features of the proposed system. A root mean square error of 9.00 mm for the estimation of the raw material position and 0.05 degrees for the fibre orientation detection encourages further research for developing the proposed robotic manufacturing system.

Many industrial sectors face increasing production demands and need to reduce costs, without compromising the quality. Whereas mass production relies on well-established protocols, small production facilities with small lot sizes struggle to update their highly changeable production at reasonable costs. The use of robotics and automation has grown significantly in recent years, but extremely versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are unavoidable differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. This could be avoided by measuring the real-geometry and the position of the specimen, which creates the paradox of having to plan robot paths for surface mapping purposes, before the originally intended robot task can be approached. Previous works have demonstrated the use of robotically manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized to the part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences.

Automated in-process Non-Destructive Testing (NDT) systems are rapidly gaining traction within the manufacturing industry as they reduce manufacturing time and costs. When considering calibration and verification of such systems, creating defects of known geometry and nature during the deposition of a weld can: (I) help examine the capability of the automated system to detect and characterise defects, (II) be used to form a database of signals associated with different defect types to train intelligent defect classification algorithms, and (III) act as a basis for in-process gain calibration during weld inspection at high temperatures, where the ultrasound beam can be skewed as a result of velocity gradients. In view of this, this paper investigates two unique methodologies for introducing: (a) lack of fusion weld defects by embedding tungsten in the weld and (b) creating artificial weld cracks by quenching to imitate the real cracking scenarios. According to the results of Phased Array Ultrasound Testing (PAUT) inspections, the methodologies used for embedding the artificial defects were successful. The validity of inspections was also verified by extracting micrographs from the defective sections of the welds, and model-based simulations were carried out to gain a better understanding of the wave propagation path and interaction with the generated defects.

This investigation introduces two new techniques to quantitatively address the challenging problem of understanding Hydrogen Induced Cracking (HIC) in welding processes. The first technique is a novel procedure to create a known and controlled HIC in a welded sample. The second is an in-process monitoring technique to measure the initial formation and subsequent growth of the HIC in a multi-pass weld whilst being compatible with the high temperatures associated with the welding process. The HIC was initiated using a localised quenching method of the weld and its character was verified using both macrograph and microscopic investigations. During HIC initiation and growth, the sample was monitored every 1–30 min for a total of 96 h using a custom non-destructive testing (NDT) system, mounted on a robot which ensured repeatable inspection positioning. Combining these techniques has therefore allowed for the first time, a detailed understanding of the evolution of HIC in a multi-pass welded sample. Our findings reveal that the HIC was initiated 43 min after the weld ended and that it then grew rapidly for about 15 min and continued growing at a slower rate for around 24 h. No significant growth was observed for the remaining 72 h of the experimental measurement.

The seamless integration of industrial robotic arms with server computers, sensors and actuators can revolutionise the way in which automated non-destructive testing (NDT) is performed and conceived. Achieving effective integration and realising the full potential of robotic systems presents significant challenges, since robots, sensors and end-effector tools are often not necessarily designed to be put together and form a holistic system. This paper presents recent breakthroughs, opening up new scenarios for the inspection of product quality in advanced manufacturing. Many years of research have brought to software platforms the ability to integrate external data acquisition instrumentation with industrial robots to improve the inspection speed, accuracy and repeatability of NDT. Robotic manipulators have typically been operated by predefined tool-paths generated through offline path-planning software applications. Recent developments pave the way to data-driven autonomous robotic inspections, enabling real-time path planning and adaptive control. This paper presents a toolbox with highly efficient algorithms and software functions, developed to be used through high-level programming language platforms (for example MATLAB, LabVIEW and Python) and/ or integrated within low-level language (for example C# and C++) applications. The use of the toolbox can speed up the development and the robust integration of new robotic NDT systems with real-time adaptive capabilities and is compatible with all KUKA robots with six degrees of freedom (DOF), which are equipped with the Robot Sensor Interface (RSI) software add-on. The paper describes the architecture of the toolbox and shows two application examples, where performance results are provided. The concepts described in the paper are aligned with the emerging Industry 4.0 paradigms and have wider applicability beyond NDT.

In this paper, the effect of Welding Residual Stress (WRS) on the size and morphology of hydrogen-induced cracks (HIC) is studied. Four samples were manufactured using a 6-axis welding robot and in two separate batches. The difference between the two batches was the clamping system used, which resulted in different amounts of welding deformation and WRS. The hydrogen cracks were intentionally manufactured in the samples using a localised water-quenching method, where water was sprayed over a specific weld pass in a predetermined position. The Phased-Array Ultrasonic Testing (PAUT) system was implemented during the welding process (high-temperature in-process method), to detect the HIC in real-time. The WRS in both batches was measured using the hole-drilling method, where a difference in transversal residual stress of 78 MPa was found between the two samples. Based upon both the PAUT results and microscopic investigations, the batch with higher WRS resulted in larger size and number of HIC. For the first time, the negative effect of WRS on HIC has been monitored in real-time using high-temperature in-process inspection. This was achieved using an innovative approach, introduced in this paper, to repeatably manufacture high and low WRS samples in order to control the size and location of subsequent HIC.

Environmental and commercial drivers are leading to a circular economy, where systems and components are routinely recycled or remanufactured. Unlike traditional manufacturing, where components typically have a high degree of tolerance, components in the remanufacturing process may have seen decades of wear, resulting in a wider variation of geometries. This makes it difficult to translate existing automation techniques to perform Non-Destructive Testing (NDT) for such components autonomously. The challenge of performing automated inspections, with off-line tool-paths developed from Computer Aided Design (CAD) models, typically arises from the fact that those paths do not have the required level of accuracy. Beside the fact that CAD models are less available for old parts, these parts often differ from their respective virtual models. This paper considers flexible automation by combining part geometry reconstruction with ultrasonic tool-path generation, to perform Ultrasonic NDT. This paper presents an approach to perform custom vision-guided ultrasonic inspection of components, which is achieved through integrating an automated vision system and a purposely developed graphic user interface with a robotic work-cell. The vision system, based on structure from motion, allows creating 3D models of the parts. Also, this work compares four different tool-paths for optimum image capture. The resulting optimum 3D models are used in a virtual twin environment of the robotic inspection cell, to enable the user to select any points of interest for ultrasonic inspection. This removes the need of offline robot path-planning and part orientation for assessing specific locations on a part, which is typically a very time-consuming phase.

In this article, ultrasonic phased arrays are deployed as an imaging tool for industrial process analysis. Such arrays are typically used for sonar, medical diagnosis, and nondestructive testing; however, they have not yet been applied to industrial process analysis. The precise positioning of array elements and high frequencies possible with this technology mean that highly focused images can be generated, which cannot currently be achieved using ultrasound tomography. This article aims to highlight the potential of this technology for the measurement of bubble size distribution (BSD) and to demonstrate its application to both intrusive and noninvasive process measurements. Ultrasound images of bubble reflectors are generated using the total focusing method deployed using a 32-element, 5-MHz linear phased array, and an image processing algorithm for BSD determination is presented and evaluated under stationary and dynamic acquisition conditions. It is found that the sizing accuracy is within 10% for stationary reflectors larger than $4\lambda $ in diameter and that the algorithm is stable across the expected spatial variation of reflectors. The phased array is coupled to a six-axis robotic arm to scan a solid sample containing bubble reflectors at velocities up to 500 mms−1. The sizing accuracy is within 45% for bubbles larger than $4\lambda $ in diameter and at velocities up to 300 mms−1. However, above this velocity, the algorithm breaks down for reflectors smaller than $9\lambda $ in diameter. The ultrasound system is applied to a stream of air bubbles rising through water, which is verified via photographic analysis. Images were generated both intrusive and noninvasive, via a 10-mm Perspex barrier, to the process stream. The high bubble density in the process stream introduced scattering, limiting the measurement repeatability and the sample size in the measured distribution. Notwithstanding, this result demonstrates the potential of this technology to size bubbles for intrusive and noninvasive process analyses.

In multi-pass welding, there is increasing motivation to move towards in-process defect detection to enable real-time repair; thus avoiding deposition of more layers over a defective weld pass. All defect detection techniques require a consistent and repeatable approach to calibration to ensure that measured defect sizing is accurate. Conventional approaches to calibration employ fixed test blocks with known defect sizes, however, this methodology can lead to incorrect sizing when considering complex geometries, materials with challenging microstructure, and the significant thermal gradients present in materials during the inter-pass inspection period. To circumvent these challenges, the authors present a novel approach to calibration and introduce the concept of in-process calibration applied to ultrasonic Non-Destructive Testing (NDT). The new concept is centred around the manufacturing of a second duplication sample, containing intentionally-embedded tungsten inclusions, with identical process parameters as the main sample. Both samples are then inspected using a high-temperature robotic NDT process to allow direct comparative measurements to be established between the real part and the calibration sample. It is demonstrated that in-process weld defect detection using the in-process calibration technique can more reliably identify defects in samples which would otherwise pass the acceptance test using a traditional calibration.

The use of robotics is beginning to play a key role in automating the data collection process in Non Destructive Testing (NDT). Increasing the use of automation quickly leads to the gathering of large quantities of data, which makes it inefficient, perhaps even infeasible, for a human to parse the information contained in them. This paper presents a solution to this problem by making the process of NDT data acquisition an autonomous one as opposed to an automatic one. In order to achieve this, the robotic data acquisition task is treated as an optimisation problem, where one seeks to find locations with the highest indication of damage. The resulting algorithm combines damage detection technology from the field of data-driven Structural Health Monitoring (SHM) with novel ideas in uncertainty quantification which enable the optimisation routine to be probabilistic. The algorithm is sequential; a decision is made at every iteration regarding the next optimal physical location for making an observation. This is achieved by modelling a two-dimensional field of novelty indices across a part/structure which is derived from a robust outlier analysis procedure. The value of this autonomous approach is that the output is not only measured data, but the most desirable information from an NDT inspection – the probability that a component contains damage. Furthermore, the algorithm also minimises the number of observations required, thus minimising the time and cost of data gathering.

Unmanned Aerial Vehicles (UAVs) are receiving increasing attention for use in Non-Destructive Testing due to their ability to access areas where manual inspection is not practical. Contact-based UAV ultrasonic inspections grant the opportunity to remotely monitor the structural health of an industrial asset with enhanced internal integrity information. Ultrasonic inspection is a Non-Destructive Testing (NDT) method conventionally used in corrosion mapping. Surface contacting ultrasonic transducers provide enhanced structural integrity information. However, due to near-surface aerodynamic effects, angular sensitivity of the ultrasound probe and alignment error during autonomous inspections, ultrasonic thickness measurements with low Signal-to-Noise Ratio (SNR) are common. Coded excitation consists of a series of binary bits, whereby the polarity of the voltage is varied following a set excitation sequence to produce desirable signal properties. Here, coded excitation is utilised to increase SNR and thereby reduce measurement uncertainty originating from non-ideal transducer alignment with asset surfaces during inspections. This paper evaluates the performance of two binary code sequences (8-bit Golay, 13-bit Barker) for use in autonomous airborne inspections.

The demand for high-speed ultrasonic scanning of large and complex components is driven by a desire to reduce production bottlenecks during the non-destructive evaluation (NDE) of critical parts. Emerging systems (including robotic inspection) allow for the collection of large volumes of data in short time spans, compared to existing inspection systems. To maximise throughput, it is crucial that the reconstructed inspection datasets are generated and evaluated rapidly without loss of detail. This requires new data visualisation and analysis tools capable of mapping complex geometries while guaranteeing full coverage. This paper presents an entirely new approach for the visualisation of three-dimensional (3D) ultrasonic C-scans, suitable for application to high data throughput ultrasonic phased array inspection of large and complex parts. Existing reconstruction approaches are discussed and compared with the new index-based triangulation (IBT) method presented. The IBT method produces 3D C-scan representation, presented as coloured tessellated surfaces, and the approach is shown to work efficiently, even on challenging geometries. An additional differentiating characteristic of the IBT method is that it allows for easy detection of lack of coverage (an essential feature for ensuring that inspection coverage can be guaranteed on critical components). The results demonstrate that the IBT C-scan generation approach runs over 60 times faster than a C-scan display based on Delaunay triangulation and over 500 times faster than surface reconstruction C-scans. In summary, the main benefits of the new IBT technique include: high-speed generation of C-scans on large ultrasonic datasets (orders of magnitude improvement compared to surface reconstruction C-scans); the ability to operate efficiently on 3D mapped datasets (allowing 3D interpretation of C-scans on complex geometry components); and intrinsic indication of lack of inspection coverage.

Modern tools for designing and manufacturing of large components with complex geometries allow more flexible production with reduced cycle times. This is achieved through a combination of traditional subtractive approaches and new additive manufacturing processes. The problem of generating optimum tool-paths to perform specific actions (e.g. part manufacturing or inspection) on curved surface samples, through numerical control machinery or robotic manipulators, will be increasingly encountered. Part variability often precludes using original design CAD data directly for toolpath generation (especially for composite materials), instead surface mapping software is often used to generate tessellated models. However, such models differ from precise analytical models and are often not suitable to be used in current commercially available path-planning software, since they require formats where the geometrical entities are mathematically represented thus introducing approximation errors which propagate into the generated toolpath. This work adopts a fundamentally different approach to such surface mapping and presents a novel Mesh Following Technique (MFT) for the generation of tool-paths directly from tessellated models. The technique does not introduce any approximation and allows smoother and more accurate surface following tool-paths to be generated. The background mathematics to the new MFT algorithm are introduced and the algorithm is validated by testing through an application example. Comparative metrology experiments were undertaken to assess the tracking performance of the MFT algorithms, compared to tool-paths generated through commercial software. It is shown that the MFT tool-paths produced 40% smaller errors and up to 66% lower dispersion around the mean values. Highlights This work presents a technique for generation of tool-paths from tessellated models. The technique does not introduce approximations to surface following tool-paths. Comparative metrology experiments were carried out to assess the technique. The technique produces smaller errors and lower dispersion around the mean values. The developed method is aligned with the growing use of surface mapping techniques.

Increasing the inspection quality and speed is essential in manufacturing applications, especially for large structures (e.g. modern aircrafts). Traditional ultrasonic manual scanning can be comprehensive, but lacks repeatability and is time-consuming. Several robotic non-destructive testing systems have been developed in recent years. Although high inspection rates have been achieved by the use of robotic arms, there is the need to furtherly increase the inspection speeds, to cope with the current industrial demands. For systems delivering robotic ultrasonic inspection through phased array probes, the current bottleneck is given by the time required to electrically fire all elements of the phased array probes, which limits the maximum scanning speed of the automated manipulators. This paper discusses the development of a multi-aperture beamforming method to focus the beam with multiple focusing points at a single firing. This work investigates this approach and the influence of different aperture excitations on the data quality. Experiments have been carried out using a 5MHz 32-element phased array probe manipulated by a KUKA robot. The results highlight the possibility to significantly improve the speed of automated inspection compared to linear beamforming, without compromising the inspection quality.Increasing the inspection quality and speed is essential in manufacturing applications, especially for large structures (e.g. modern aircrafts). Traditional ultrasonic manual scanning can be comprehensive, but lacks repeatability and is time-consuming. Several robotic non-destructive testing systems have been developed in recent years. Although high inspection rates have been achieved by the use of robotic arms, there is the need to furtherly increase the inspection speeds, to cope with the current industrial demands. For systems delivering robotic ultrasonic inspection through phased array probes, the current bottleneck is given by the time required to electrically fire all elements of the phased array probes, which limits the maximum scanning speed of the automated manipulators. This paper discusses the development of a multi-aperture beamforming method to focus the beam with multiple focusing points at a single firing. This work investigates this approach and the influence of different aperture excitat...

In this study, three aluminium samples produced by wire + arc additive manufacture (WAAM) are inspected using ultrasonic phased array technology. Artificial defects are machined using a centre drill, ø 3 mm, and electrical discharge machining (EDM), ø 0.5-1 mm, in a cylindrical through-hole topology. The samples are first inspected using a single-element wheel probe mounted on a KUKA robot in order to investigate the feasibility of using a conventional ultrasonic transducer approach. Unfortunately, the wheel probe is found to be unsuitable for scanning the WAAM specimens and ultrasonic phased arrays are employed next. The set-up includes 5 MHz and 10 MHz arrays (128 elements) in direct contact with the sample surface using both the conventional and total focusing method (TFM) imaging techniques. Using an FIToolbox (Diagnostic Sonar, UK) as the controller, a phased array aperture of 32 elements is used to perform a focused B-scan with a range of settings for the transmit focal depth. All of the reflectors (including those located near the WAAM top surface) are successfully detected with a combination of conventional phased array and TFM, using a range of settings and set-ups, including bottom surface inspection, application through a plexiglass wedge and variation of the scanning frequency.

Automated inspection systems using industrial robots have been available for several years. The IntACom robot inspection system was developed at TWI Wales and utilizes phased array ultrasonic probes to inspect complex geometries, in particular aerospace composite components. To increase inspection speed and accuracy, off-line path planning is employed to define a series of robotic movements following the surface of a component. To minimize influences of refraction at the component interface and effects of anisotropy, the ultrasonic probe must be kept perpendicular to the surface throughout the inspection. Deviations between the actual component and computer model used for path-planning result in suboptimal alignment and a subsequent reduction in the quality of the ultrasonic echo signal. In this work we demonstrate methods for using the ultrasonic echo signals to adapt a robotic path to achieve a minimal variation in the reflected surface echo. The component surface is imaged using phased array probes to calculate a sparse 3D point cloud with estimated normal directions. This is done through a preliminary alignment path covering approximately 25% of the total surface to minimize the impact on overall inspection time. The data is then compared to the expected geometry and deviations are minimized using least-squares optimization. Compared to manual alignment techniques, this method shows a reduction in surface amplitude variation of up to 32%, indicating that the robot is following the surface of the component more accurately.

Increased demands in performance and production rates require a radical new approach to the design and manufacturing of aircraft wings. Performance of modern robotic manipulators has enabled research and development of fast automated non-destructive testing (NDT) systems for complex geometries. This paper presents recent outcomes of work aimed at removing the bottleneck due to data acquisition rates, to fully exploit the scanning speed of modern 6-DoF manipulators. The geometric assessment of the parts is carried out with a robotised dynamic laser scanner encoded through an absolute laser tracker. This method allows scanning speeds up to 330mm/s at 1mm pitch. State of the art ultrasonic instrumentation has been integrated into a large robot cell to enable fast data acquisition, high scan resolutions and accurate positional encoding. A fibre optic connection between the ultrasonic instrument and the server computer enables data transfer rates up to 1.6 GB/s. The robotic inspection system presented herein is currently being tested for industrial exploitation. The adopted system integration strategies allow traditional ultrasonic phased array scanning as well as full matrix capture (FMC) and other novel scanning approaches (e.g. multi-Tx phased array). Scan results, relative to a 1.2m x 3m carbon fibre sample, are presented. The system shows a reference scanning rate of 25.3m2/hour with an 8Tx/8Rx PA approach and an ultrasonically reachable scanning rate over 100m2/hour with the novel techniques.

The requirement to increase inspection speeds for non-destructive testing (NDT) of composite aerospace parts is common to many manufacturers. The prevalence of complex curved surfaces in the industry provides motivation for the use of 6 axis robots in these inspections. The purpose of this paper is to present work undertaken for the development of a KUKA robot manipulator based automated NDT system. A new software solution is presented that enables flexible trajectory planning to be accomplished for the inspection of complex curved surfaces often encountered in engineering production. The techniques and issues associated with conventional manual inspection techniques and automated systems for the inspection of large complex surfaces were reviewed. This approach has directly influenced the development of a MATLAB toolbox targeted to NDT automation, capable of complex path planning, obstacle avoidance, and external synchronization between robots and associated external NDT systems. This paper highlights the advantages of this software over conventional off-line-programming approaches when applied to NDT measurements. An experimental validation of path trajectory generation, on a large and curved composite aerofoil component, is presented. Comparative metrology experiments were undertaken to evaluate the real path accuracy of the toolbox when inspecting a curved 0.5m2 and a 1.6m2 surface using a KUKA KR16 L6-2 robot. The results have shown that the deviation of the distance between the commanded TCPs and the feedback positions were within 2.7mm. The variance of the standoff between the probe and the scanned surfaces was smaller than the variance obtainable via commercial path-planning software. Tool paths were generated directly on the triangular mesh imported from the CAD models of the inspected components without need for an approximating analytical surface. By implementing full external control of the robotic hardware, it has been possible to synchronise the NDT data collection with positions at all points along the path, and our approach allows for the future development of additional functionality that is specific to NDT inspection problems. For the current NDT application, the deviations from CAD design and the requirements for both coarse and fine inspections, dependent on measured NDT data, demand flexibility in path planning beyond what is currently available from existing off-line robot programming software.

While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illustrated using case studies of composite structure monitoring and will consider the challenges of high-dimensional feature data available from sensing technologies like autonomous robotic ultrasonic inspection. This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.

In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on ma-chine vision, working on the HSV space for color detection in order to deal with changing conditions including non-uniform background, lighting reflections and shadows projection. The proposed machine vision is implemented by an off-board scheme with two low-cost cameras, where the second camera is aimed at solving the problem of vision obstruction when the robot invades the field of view of the main sensor. Real-time performance of the overall system has been experimentally tested, using a KUKA KR90 R3100 robot.

The interior visual inspection of pipelines in the nuclear industry is a safety critical activity conducted during outages to ensure the continued safe and reliable operation of plant. Typically, the video output by a manually deployed probe is viewed by an operator looking to identify and localize surface defects such as corrosion, erosion and pitting. However, it is very challenging to estimate the nature and extent of defects by viewing a large structure through a relatively small field of view. This work describes a new visual inspection system employing photogrammetry using a fisheye camera and a structured light system to map the internal geometry of pipelines by generating a photorealistic, geometrically accurate surface model. The error of the system output was evaluated through comparison to a ground truth laser scan (ATOS GOM Triple Scan) of a nuclear grade split pipe sample (stainless steel 304L, 80mm internal diameter) containing defects representative of the application - the error was found to be submillimeter across the sample.

The performance of modern robotic manipulators has allowed research in recent years, for the development of fast automated non-destructive testing (NDT) of complex geometries. Contemporary robots are well suited for their accuracy and flexibility when adapting to new tasks. Several robotic inspection prototype systems and a number of commercial products have been created around the world. This paper describes the latest progress of a new phase of the research applied to a composite aerospace component of size 1 by 3 metres. A multi robot flexible inspection cell was used to take the fundamental research and the feasibility studies to higher technology readiness levels, all set for future industrial exploitation. The robot cell was equipped with high accuracy and high payload robots, mounted on 7 metre tracks, and an external rotary axis. A robotically delivered photogrammetry technique was first used to assess the position of the components placed within the robot working envelope and their deviation to CAD. Offline programming was used to generate a scan path for phased array ultrasonics testing (PAUT) which was implemented using high data rate acquisition from a conformable wheel probe. Real-time robot path-correction, based on force-torque control (FTC), was deployed to achieve the optimum ultrasonic coupling and repeatable data quality. New communication software was developed that enabled the simultaneous control of the multiple robots performing different tasks and the reception of accurate positional feedback positions. All aspects of the system were controlled through a purposely developed graphic user interface that enabled the flexible use of the unique set of hardware resources, the data acquisition, visualisation and analysis. This work was developed through the VIEWS project (Validation and Integration of Manufacturing Enablers for Future Wing Structures), part funded by the UK’s innovation agency (Innovate UK).

Performance of modern robotic manipulators has enabled research and development of fast automated non-destructive testing (NDT) systems for complex geometries. This paper presents recent outcomes of work aimed at removing the bottleneck due to data acquisition rates, to fully exploit the scanning speed of modern 6-DoF manipulators. State of the art ultrasonic instrumentation has been integrated into a large robot cell to enable fast data acquisition, high scan resolutions and accurate positional encoding. A fibre optic connection between the ultrasonic instrument and the server computer enables data transfer rates up to 1.6GB/s. Multiple data collection methods are compared. Performance of the integrated system allows traditional ultrasonic phased array scanning as well as full matrix capture (FMC). In FMC configuration, linear scan speeds up to 156mm/s with 64 pulses per frame are achieved - this speed is only constrained by the acoustic wave propagation in the component. An 8x increase of the speed (up to 1.25m/s) can be achieved using multiple transmission elements, reaching the physical limits for acceptable acoustic alignment of transmission and reception paths. Scan results, relative to a 1.2m × 3m carbon fibre sample, are presented.

The high-normal blood pressure (also known as prehypertension) is a clinical condition characterized by an increased cardiovascular risk as well as by the presence of target organ damage. This include an increased left ventricular mass, an endothelial dysfunction and an early renal functional and structural damage. Whether this is the case also for alterations of retinal vessels network, which are frequently detectable in established hypertension, is still largey undefined. The present paper, after discussing the main characteristics of the high-normal blood pressure state, will review the different approaches used throughout the years for assessing retinal microcirculatory network. Data collected by our group in subjects with high normal blood pressure will be also discussed, showing that arterial venular ratio values are reduced in this individuals with high-normal blood pressure and more so in established hypertension. These data indicate that retinal microvascular alterations 1) are of early appearance in the clinical course of hypertension and 2) are of frequent detection in the high-normal blood pressure state. The possible hemodynamic and non-hemodynamic mechanisms resposible for these structural alteations of the retinal microcirculation will be also discussed.

This work presents the study of the accuracy of an industrial robot KR5 arc HW, used to perform quality inspections of components with complex shapes. Metrology techniques such as laser tracking and large volume photogrammetry were deployed to quantify both pose and dynamic path accuracies of the robot in accordance with ISO 9283:1998. The overall positioning pose inaccuracy of the robot is found to be almost 1 mm and path inaccuracy at 100% of the robot rated velocity is 4.5 mm. The maximum pose orientation inaccuracy is found to be 14 degrees and the maximum path orientation inaccuracy is 5 degrees. Despite of the significant maximum inaccuracies, uncertainty of a robotic scanning application is estimated to be 0.5mm. Local positional errors manifest pronounced dependence on the position of the robot end effector in the working envelope. The uncertainties of the measurements are discussed and deemed to be caused by the tool center point calibration, the reference coordinate system transformation and the low accuracy of the photogrammetry system.

The external surface of stainless steel containers used for the interim storage of nuclear material may be subject to Atmospherically Induced Stress Corrosion Cracking (AISCC). The inspection of such containers poses a significant challenge due to the large quantities involved; therefore, automating the inspection process is of considerable interest. This paper reports upon a proof-of-concept project concerning the automated NDT of a set of test containers containing artificially generated AISCCs. An Eddy current array probe with a conformable padded surface from Eddyfi was used as the NDT sensor and end effector on a KUKA KR5 arc HW robot. A kinematically valid cylindrical raster scan path was designed using the KUKA|PRC path planning software. Custom software was then written to interface measurement acquisition from the Eddyfi hardware with the motion control of the robot. Preliminary results and analysis are presented from scanning two canisters.

The requirement to increase inspection speeds for the non-destructive testing (NDT) of composite aerospace parts is common to many manufacturers. The prevalence of complex curved surfaces in the industry provides significant motivation for the use of six-axis robots for the deployment of NDT probes in these inspections. The IntACom project, developed by TWI Technology Centre (Wales) and supported by a number of major aerospace partners and the Welsh government, has produced a prototype robotic NDT system. The prototype system is capable of inspecting complex-geometry composite components with great time savings. Two six-axis robotic arms deploy end effectors carrying phased array ultrasonic testing (PAUT) probes. A simple-to-use graphical user interface (GUI) has been developed to control all aspects of the robotic inspection, from initial loading of part data, through scanning of the part to data analysis. The collaboration between TWI and the University of Strathclyde has boosted the establishment of new approaches for robotic tool-path generation, targeted to NDT inspections. Many unique features, such as the real-time B-scan for optimisation of PAUT settings and the external control of the robotic manipulators to allow returning to points of interest, increase the usefulness of the inspection process. This paper presents an overview of the project and of the research outcomes.

The requirement to increase inspection speeds for non-destructive testing (NDT) of composite aerospace parts is common to many manufacturers. The prevalence of complex curved surfaces in the industry provides significant motivation for the use of 6 axis robots for deployment of NDT probes in these inspections. A new system for robot deployed ultrasonic inspection of composite aerospace components is presented. The key novelty of the approach is through the accommodation of flexible robotic trajectory planning, coordinated with the NDT data acquisition. Using a flexible approach in MATLAB, the authors have developed a high level custom toolbox that utilizes external control of an industrial 6 axis manipulator to achieve complex path planning and provide synchronization of the employed ultrasonic phase array inspection system. The developed software maintains a high level approach to the robot programming, in order to ease the programming complexity for an NDT inspection operator. Crucially the approach provides a pathway for a conditional programming approach and the capability for multiple robot control (a significant limitation in many current off-line programming applications). Ultrasonic and experimental data has been collected for the validation of the inspection technique. The path trajectory generation for a large, curved carbon-fiber-reinforced polymer (CFRP) aerofoil component has been proven and is presented. The path error relative to a raster-scan tool-path, suitable for ultrasonic phased array inspection, has been measured to be within + 2mm over the 1.6 m 2 area of the component surface.

Train loads and travel speeds have increased over time, requiring more efficient non-destructive inspection methods. Railway axles are critical elements; despite being designed to last more than 20 years several cases of premature failure have been recorded. Train axles are inspected regularly, but the limits associated to the traditional inspection technologies create a growing interest towards new solutions. Here a novel non-destructive inspection method of in-service axles based on non-contact data collection is presented. The propagation of surface waves, generated by a thermo-elastic laser source, is investigated using a finite element method based on dynamic explicit integration. Coupled thermo-mechanical simulations allow visualization of the ultrasonic field guiding the definition of the optimal NDT setup. The geometry of the axle and of the elements mounted on it is accurately reproduced; moreover the press fit effect caused by the wheel and the bearing rings is implemented. The current NDT techniques for railway axles require removing wheels and other components from the axle. The presented scheme uses non-contact ultrasonic generation and detection allowing non-contact in-service inspection of railway axles at trackside station. The numerical results are promising and encourage us to test the new approach experimentally.

The use of Rayleigh waves enables the solution of several important inspection problems. Propagation of surface waves along straight boundaries has been properly studied but investigations about their propagation on cylindrical surfaces are not sufficient, despite they can be still of interest for NDE applications. It has been proved experimentally that a surface wave pulse suffers a phase shift during its propagation along a cylindrical surface. A numerical approach has been developed to efficiently study these effects for different materials, curvatures and frequencies. This study can help the scientific community to better understand the phenomenon, quite complex and not yet fully explored.

Background: Metabolic syndrome is characterized by a marked sympathetic overactivity. It is unknown, however, whether the neuroadrenergic activation can be ascribed to obstructive sleep apnoea (OSA), OSA exerts potentiating effects on the metabolic syndrome-related sympathetic activation and reflex/metabolic variables (insulin resistance) participate at the phenomenon. Methods and Results: We conducted a cross-sectional study of healthy individuals and metabolic syndrome patients recruited in our outpatient clinic. Fifty-five middle-age men classified according to Adult Treatment Panel III criteria and apnea-hypopnea index (overnight polysomnographic evaluation) as healthy controls without OSA and metabolic syndrome patients without and with OSA were studied. Blood pressure (Finapres), heart rate (ECG) and muscle sympathetic nerve activity (MSNA; microneurography) were measured at rest and during baroreflex manipulation. Compared with controls, patients with metabolic syndrome with and without OSA displayed higher waist-hip ratio, blood pressure, triglycerides and homeostasis model assessment index values but lower high-density lipoprotein cholesterol. MSNA was significantly higher in patients with metabolic syndrome without OSA than in controls (61.9 ± 3.9 vs. 37.7 ± 4.1 bursts/100 heartbeats, respectively, P < 0.01), a further marked increase being detected in patients with metabolic syndrome with OSA (77.1 ± 4.3 bursts/100 heart beats, P < 0.01). Compared with controls, baroreflex control of heart rate and MSNA was markedly impaired in patients with metabolic syndrome with OSA, a further impairment in baroreflex-heart rate modulation being detected in metabolic syndrome with OSA. In the metabolic syndrome group as a whole, at the multivariate analysis, MSNA was significantly related to the apnoea-hypopnoea index but not to other variables. Conclusion: Thus the sympathetic activation of metabolic syndrome occurs independently on OSA. OSA, however, markedly potentiates this neuroadrenergic abnormality via a hypoxic-dependent chemoreflex activation. © 2010 Wolters Kluwer Health | Lippincott Williams & Wilkins.

Ultrasonic Non-Destructive Evaluation using Full Matrix Capture (FMC) and Total Focusing Method (TFM) is used for high resolution imaging as every pixel is in optimal focus. FMC excites one element in turn, so operates with lower transmitted energy compared to phased array beamforming. The energy at a reflector is further reduced by the broad directivity pattern of the single element. The large number of Tx/Rx A-scans that contribute to each pixel recover the Signal-to-Noise Ratio (SNR) in the final TFM image. Maintaining this in the presence of attenuating materials is a challenge because relevant information in each A-scan signal is buried in the thermal noise, and the TFM process assumes no quantization effects in the Analogue-to-Digital Converters (ADCs) in each receiver. In-process inspection during Additive Manufacturing (AM) requires ultrasonic array sensors that can tolerate high temperatures, scan over rough surfaces and leave no residue. Dry-coupled wheel probes are a solution, but the tire rubbers are often highly attenuating, causing a problem for FMC+TFM needed to adapt the focus through the rough surface. Common approaches to maintain the SNR are to drop the frequency or to average over multiple transmissions, but these compromise resolution and acquisition rate respectively. In this paper, the application of coded excitation to maintain the SNR in the presence of high signal attenuation is explored.

Remanufactured products can save up to 80% of production and energy costs whilst generating lower CO2 emissions. The key success factors for remanufacturing are quality, lead-time and cost. Extensive work within the industry and the detailed analysis of the remanufacturing process has shown that component inspection has significant bearing on overall productivity. Remanufacturing lacks automation because activities are predominantly manual. Automation of remanufacturing process will not only decrease the number of non-remanufacturable components, through decreasing cost and increasing consistency in quality, but also attract industries to design for remanufacture. A digital model of the component is required to automate the disassembly process and move towards industry 4.0 and cyber physical systems. There are several expensive techniques to create a digital model, which are not feasible for the remanufacturing industry. The research paper aims to check feasibility of using Visual Structure for Motion (VFM), a relatively low cost method, to develop a 3D digital model, for automation of the automotive engine (in as received condition) disassembly process using industrial robots. These initial experiments assess the feasibility of using Videogrammetry to acquire pre-disassembly 3D model of the engine. Multiple 2D images were acquired and processed to find matching common features. The location of the camera was calculated through the matching features, producing a three-dimensional digital representation of the captured volume. A sparse point cloud was initially created which and was then converted into a dense 3D point cloud. The 3D point cloud was converted into a meshed model. 2D images are stitched together to create a virtual model of the engine with surface texture and colour. Small features of a few couple of millimetres in size are clearly visible in the 3D model.

This paper presents an approach for estimation of ultrasonic time-of-flight (TOF) within a Non Destructive Testing (NDT) and Structural Health Monitoring (SHM) context. The presented method leverages recent advances in the field of Compressive Sensing (CS), which makes use of sparsity in a transform domain of a signal in order to reduce the number of samples required to store it. CS achieves this through a two key ideas: random matrix projections, and l1-penalised linear regression. In this case, sparsity arises from the observation that in a pulse-echo ultrasound test, the number of echoes is relatively small compared to the number of measurement points in a waveform. This sparsity is evident in the autocorrelation of ultrasound waveforms. A method is suggested in this paper for building suitable basis functions, based on Hankel matrices, which transform a signal into its autocorrelation domain. It is shown how this can be combined with standard CS techniques in order to achieve a very low error in TOF estimates with up to one-tenth of the original ultrasound samples.

Automated robotic inspection systems allow the collection of large data volumes, compared to existing inspection systems. To maximize the throughput associated with the non-destructive evaluation phase, it is crucial that the reconstructed inspection data sets are generated and examined rapidly without a loss of detail. Data analysis often becomes the bottleneck of automated inspections. Therefore, new data visualization tools, suitable to screen the NDT information obtained through robotic systems, are urgently required. This paper presents a new approach, for the generation of three-dimensional ultrasonic C-scans of large and complex parts, suitable for application to high data throughput ultrasonic phased array inspection. This approach produces 3D C-scan presented as colored tessellated surfaces and the approach works efficiently on challenging geometry, with concave and convex regions. Qualitative and quantitative results show that the approach runs up to 500 times faster than other C-scan visualization techniques.