RESUMO
This paper presents a novel approach for preload measurement of bolted connections, specifically tailored for offshore wind applications. The proposed method combines robotics, Phased Array Ultrasonic Testing (PAUT), nonlinear acoustoelasticity, and Finite Element Analysis (FEA). Acceptable defects, below a pre-defined size, are shown to have an impact on preload measurement, and therefore conducting simultaneous defect detection and preload measurement is discussed in this paper. The study demonstrates that even slight changes in the orientation of the ultrasonic transducer, the non-automated approach, can introduce a significant error of up to 140 MPa in bolt stress measurement and therefore a robotic approach is employed to achieve consistent and accurate measurements. Additionally, the study emphasises the significance of considering average preload for comparison with ultrasonic data, which is achieved through FEA simulations. The advantages of the proposed robotic PAUT method over single-element approaches are discussed, including the incorporation of nonlinearity, simultaneous defect detection and stress measurement, hardware and software adaptability, and notably, a substantial improvement in measurement accuracy. Based on the findings, the paper strongly recommends the adoption of the robotic PAUT approach for preload measurement, whilst acknowledging the required investment in hardware, software, and skilled personnel.
RESUMO
BACKGROUND AND AIMS: We aimed to develop a computer-aided characterization system that could support the diagnosis of dysplasia in Barrett's esophagus (BE) on magnification endoscopy. METHODS: Videos were collected in high-definition magnification white-light and virtual chromoendoscopy with i-scan (Pentax Hoya, Japan) imaging in patients with dysplastic and nondysplastic BE (NDBE) from 4 centers. We trained a neural network with a Resnet101 architecture to classify frames as dysplastic or nondysplastic. The network was tested on 3 different scenarios: high-quality still images, all available video frames, and a selected sequence within each video. RESULTS: Fifty-seven patients, each with videos of magnification areas of BE (34 dysplasia, 23 NDBE), were included. Performance was evaluated by a leave-1-patient-out cross-validation method. In all, 60,174 (39,347 dysplasia, 20,827 NDBE) magnification video frames were used to train the network. The testing set included 49,726 i-scan-3/optical enhancement magnification frames. On 350 high-quality still images, the network achieved a sensitivity of 94%, specificity of 86%, and area under the receiver operator curve (AUROC) of 96%. On all 49,726 available video frames, the network achieved a sensitivity of 92%, specificity of 82%, and AUROC of 95%. On a selected sequence of frames per case (total of 11,471 frames), we used an exponentially weighted moving average of classifications on consecutive frames to characterize dysplasia. The network achieved a sensitivity of 92%, specificity of 84%, and AUROC of 96%. The mean assessment speed per frame was 0.0135 seconds (SD ± 0.006). CONCLUSION: Our network can characterize BE dysplasia with high accuracy and speed on high-quality magnification images and sequence of video frames, moving it toward real-time automated diagnosis.
Assuntos
Esôfago de Barrett , Neoplasias Esofágicas , Humanos , Esôfago de Barrett/diagnóstico , Neoplasias Esofágicas/diagnóstico por imagem , Esofagoscopia/métodos , Hiperplasia , ComputadoresRESUMO
The increased demand for cost-efficient manufacturing and metrology inspection solutions for complex-shaped components in High-Value Manufacturing (HVM) sectors requires increased production throughput and precision. This drives the integration of automated robotic solutions. However, the current manipulators utilizing traditional programming approaches demand specialized robotic programming knowledge and make it challenging to generate complex paths and adapt easily to unique specifications per component, resulting in an inflexible and cumbersome teaching process. Therefore, this body of work proposes a novel software system to realize kinesthetic guidance for path planning in real-time intervals at 250 Hz, utilizing an external off-the-shelf force-torque (FT) sensor. The proposed work is demonstrated on a 500 mm2 near-net-shaped Wire-Arc Additive Manufacturing (WAAM) complex component with embedded defects by teaching the inspection path for defect detection with a standard industrial robotic manipulator in a collaborative fashion and adaptively generating the kinematics resulting in the uniform coupling of ultrasound inspection. The utilized method proves superior in performance and speed, accelerating the programming time using online and offline approaches by an estimate of 88% to 98%. The proposed work is a unique development, retrofitting current industrial manipulators into collaborative entities, securing human job resources, and achieving flexible production.
RESUMO
The demand for cost-efficient manufacturing of complex metal components has driven research for metal Additive Manufacturing (AM) such as Wire + Arc Additive Manufacturing (WAAM). WAAM enables automated, time- and material-efficient manufacturing of metal parts. To strengthen these benefits, the demand for robotically deployed in-process Non-Destructive Evaluation (NDE) has risen, aiming to replace current manually deployed inspection techniques after completion of the part. This work presents a synchronized multi-robot WAAM and NDE cell aiming to achieve (1) defect detection in-process, (2) enable possible in-process repair and (3) prevent costly scrappage or rework of completed defective builds. The deployment of the NDE during a deposition process is achieved through real-time position control of robots based on sensor input. A novel high-temperature capable, dry-coupled phased array ultrasound transducer (PAUT) roller-probe device is used for the NDE inspection. The dry-coupled sensor is tailored for coupling with an as-built high-temperature WAAM surface at an applied force and speed. The demonstration of the novel ultrasound in-process defect detection approach, presented in this paper, was performed on a titanium WAAM straight sample containing an intentionally embedded tungsten tube reflectors with an internal diameter of 1.0 mm. The ultrasound data were acquired after a pre-specified layer, in-process, employing the Full Matrix Capture (FMC) technique for subsequent post-processing using the adaptive Total Focusing Method (TFM) imaging algorithm assisted by a surface reconstruction algorithm based on the Synthetic Aperture Focusing Technique (SAFT). The presented results show a sufficient signal-to-noise ratio. Therefore, a potential for early defect detection is achieved, directly strengthening the benefits of the AM process by enabling a possible in-process repair.
Assuntos
Procedimentos Cirúrgicos Robóticos , Robótica , Diagnóstico por Imagem , Metais , Procedimentos Cirúrgicos Robóticos/métodos , Robótica/métodos , Ultrassom/métodos , Ultrassonografia/métodosRESUMO
The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs.
RESUMO
Accurate average flow velocity determination is essential for flow measurement in many industries, including automotive, chemical, and oil and gas. The ultrasonic transit-time method is common for average flow velocity measurement, but current limitations restrict measurement accuracy, including fluid dynamic effects from unavoidable phenomena such as turbulence, swirls or vortices, and systematic flow meter errors in calibration or configuration. A new spatial averaging method is proposed, based on flexural ultrasonic array transducer technology, to improve measurement accuracy and reduce the uncertainty of the measurement results. A novel two-dimensional flexural ultrasonic array transducer is developed to validate this measurement method, comprising eight individual elements, each forming distinct paths to a single ultrasonic transducer. These paths are distributed in two chordal planes, symmetric and adjacent to a diametral plane. It is demonstrated that the root-mean-square deviation of the average flow velocity, computed using the spatial averaging method with the array transducer is 2.94%, which is lower compared to that of the individual paths ranging from 3.65% to 8.87% with an average of 6.90%. This is advantageous for improving the accuracy and reducing the uncertainty of classical single-path ultrasonic flow meters, and also for conventional multi-path ultrasonic flow meters through the measurement via each flow plane with reduced uncertainty. This research will drive new developments in ultrasonic flow measurement in a wide range of industrial applications.
RESUMO
The demand for an efficient and reliable ultrasonic phased array imaging system is not unique to a single industry. Today's imaging systems can be enhanced in a number of areas including; improving scanning and processing times, reducing data storage requirements, simplifying hardware and prolonging probe lifespan. In this work, it is shown that by combining the use of Coded Excitation with single-bit data capture, a number of these areas can be improved. Despite using single-bit receive data, resolution can be recovered through the coded excitation pulse compression process, and shown to produce high Signal-to-Noise Ratio (SNR) images of Phase Coherence Imaging (PCI) and Total Focusing Method (TFM) of tip diffraction in a carbon steel sample. Comparison with conventional single-cycle transmission pulses has shown that little imaging performance degradation is seen despite a significant reduction in data resolution and size. This has also been shown to be effective at low excitation voltages with gain compensation due to the obsolescence of signal saturation concerns when considering single-bit receive data. The ability to compute high-resolution ultrasonic images from low-resolution input data at low transmission voltages has important implications for data compression, acquisition & imaging performance, operator safety and hardware simplification for ultrasonic imaging systems across industrial and medical fields.
RESUMO
Lamb wave excitation at high-frequency-thickness products offers a potential solution for high-resolution guided wave testing. The method is attractive for crack imaging and corrosion mapping, especially in hidden locations where direct access is limited. However, multiple modes may propagate, complicating signal interpretation, which is undesirable. In this work, a systematic approach is presented, in an effort to determine the influence of the key parameters related to single higher order Lamb wave mode excitation using a conventional linear array transducer. Specifically, a linear time delay law is used to enhance the targeted mode, while the array's length, pitch and apodisation profile remain to be optimally selected. First, an analytical solution is derived based on modal analysis. This provides a natural decomposition of the amplitude of a guided wave mode into the product of the response of a single element and the excitation spectrum. Then, a key observation is made, associating the excitation spectrum to the directivity function for bulk wave phased array steering. This allows the application of well-established phased array analysis tools to guided wave phased array excitation. In light of this fact, minimisation of the spectrum's bandwidth, elimination of the grating lobes and derivation of an apodisation profile are performed, to enhance the purity of the targeted mode. Finally, experiments conducted on an aluminium plate verify the above theoretical results. The Full Matrix is acquired, and all signals are reconstructed synthetically.
RESUMO
BACKGROUND AND AIMS: Seattle protocol biopsies for Barrett's Esophagus (BE) surveillance are labour intensive with low compliance. Dysplasia detection rates vary, leading to missed lesions. This can potentially be offset with computer aided detection. We have developed convolutional neural networks (CNNs) to identify areas of dysplasia and where to target biopsy. METHODS: 119 Videos were collected in high-definition white light and optical chromoendoscopy with i-scan (Pentax Hoya, Japan) imaging in patients with dysplastic and non-dysplastic BE (NDBE). We trained an indirectly supervised CNN to classify images as dysplastic/non-dysplastic using whole video annotations to minimise selection bias and maximise accuracy. The CNN was trained using 148,936 video frames (31 dysplastic patients, 31 NDBE, two normal esophagus), validated on 25,161 images from 11 patient videos and tested on 264 iscan-1 images from 28 dysplastic and 16 NDBE patients which included expert delineations. To localise targeted biopsies/delineations, a second directly supervised CNN was generated based on expert delineations of 94 dysplastic images from 30 patients. This was tested on 86 i-scan one images from 28 dysplastic patients. FINDINGS: The indirectly supervised CNN achieved a per image sensitivity in the test set of 91%, specificity 79%, area under receiver operator curve of 93% to detect dysplasia. Per-lesion sensitivity was 100%. Mean assessment speed was 48 frames per second (fps). 97% of targeted biopsy predictions matched expert and histological assessment at 56 fps. The artificial intelligence system performed better than six endoscopists. INTERPRETATION: Our CNNs classify and localise dysplastic Barrett's Esophagus potentially supporting endoscopists during surveillance.
Assuntos
Esôfago de Barrett , Neoplasias Esofágicas , Inteligência Artificial , Esôfago de Barrett/diagnóstico por imagem , Esôfago de Barrett/patologia , Biópsia/métodos , Neoplasias Esofágicas/diagnóstico por imagem , Neoplasias Esofágicas/patologia , Humanos , Redes Neurais de ComputaçãoRESUMO
OBJECTIVES: High-energy Proton Beam Therapy (PBT) commenced in England in 2018 and NHS England commissions PBT for 1.5% of patients receiving radical radiotherapy. We sought expert opinion on the level of provision. METHODS: Invitations were sent to 41 colleagues working in PBT, most at one UK centre, to contribute by completing a spreadsheet. 39 responded: 23 (59%) completed the spreadsheet; 16 (41%) declined, arguing that clinical outcome data are lacking, but joined six additional site-specialist oncologists for two consensus meetings. The spreadsheet was pre-populated with incidence data from Cancer Research UK and radiotherapy use data from the National Cancer Registration and Analysis Service. 'Mechanisms of Benefit' of reduced growth impairment, reduced toxicity, dose escalation and reduced second cancer risk were examined. RESULTS: The most reliable figure for percentage of radical radiotherapy patients likely to benefit from PBT was that agreed by 95% of the 23 respondents at 4.3%, slightly larger than current provision. The median was 15% (range 4-92%) and consensus median 13%. The biggest estimated potential benefit was from reducing toxicity, median benefit to 15% (range 4-92%), followed by dose escalation median 3% (range 0 to 47%); consensus values were 12 and 3%. Reduced growth impairment and reduced second cancer risk were calculated to benefit 0.5% and 0.1%. CONCLUSIONS: The most secure estimate of percentage benefit was 4.3% but insufficient clinical outcome data exist for confident estimates. The study supports the NHS approach of using the evidence base and developing it through randomised trials, non-randomised studies and outcomes tracking. ADVANCES IN KNOWLEDGE: Less is known about the percentage of patients who may benefit from PBT than is generally acknowledged. Expert opinion varies widely. Insufficient clinical outcome data exist to provide robust estimates. Considerable further work is needed to address this, including international collaboration; much is already underway but will take time to provide mature data.
Assuntos
Segunda Neoplasia Primária , Terapia com Prótons , Terapia por Raios X , Humanos , Segunda Neoplasia Primária/radioterapiaRESUMO
Ultrasonic testing has been used for many decades, proving itself very efficient for detecting defects in many industrial sectors. The desire to apply ultrasonic testing to geometrically complex structures, and to anisotropic, inhomogeneous materials, together with the advent of more powerful electronics and software, is constantly pushing the applicability of ultrasonic waves to their limits. General ray tracing models, suitable for calculating the proper incident angle of single element probes and the proper time delay of phased array, are currently required. They can support the development of new imaging techniques, as Full Matrix Capture and Total Focusing Method, and the execution of very challenging ultrasonic inspections. This paper introduces a generalized iterative method for the computation of ultrasonic ray paths, when ultrasonic source and target are separated by multiple complex material interfaces in the two dimensional and three dimensional domains. The manuscript starts with a review of the well-known bisection method, and extends the applicability of the method to cases with increasing complexity. An application example, in the field of in-process weld inspection, shows that the introduced generalised bisection method can enable the computation of optimum incidence angles and focal delays for accurate ultrasonic focusing. There is no restriction on the analytical interfaces to be surjective. Interface folding is permitted. It is not necessary to know, a priori, with what sequence the interfaces are crossed by the rays. The presented implementation of the method completes each iteration of the bisection method in 4 ms, for a case with a single interface, and in 960 ms for the case with 52 interfaces.
RESUMO
The aim of this experiment was to determine whether administration of an anti-inflammatory compound to sows prior to farrowing would, via reduced pain and inflammation, increase piglet survival and growth. At day 114 of gestation, multiparous sows were randomly allocated to one of the following treatments: Control (n = 43), which received 10 mL saline, NSAID (n = 55) which received 0.4 mg/kg meloxicam and SAID (n = 54) which received 0.1 mg/kg dexamethasone. Treatments were applied again on day 116 if farrowing had not occurred. There was no treatment effect on piglets born alive or dead from parity two to four sows but in those of parity five and older, NSAID administration reduced the number of piglets born alive and increased the number of piglets born dead (p < 0.05). Sow rectal temperature and incidence of mastitis were unaffected by treatment (p > 0.05). Lactation day two plasma concentrations of cortisol, prostaglandin F2 alpha metabolite and haptoglobin did not differ among treatments (p > 0.05). Treatment effects were not observed in liveborn piglet mortality at any age, or litter weight at day 21 (p > 0.05). Average feed intake during lactation was increased by both NSAID and SAID treatments (p = 0.001). The use of meloxicam prior to farrowing should be avoided as it reduced the number of piglets born alive and did not improve piglet survival and growth.
RESUMO
Piglet movement from one sow to another, or fostering, is required in modern pig farming but there is little available literature on the most effective strategy. In this review, we focus on the behavioural and physiological mechanisms responsible for piglet survival and growth, and have identified six key principles. (1) Colostrum provides piglets with warmth, energy and immunity. It is most accessible during the first 12 h from the birth sow, therefore no piglet should be moved before this; (2) To ensure even intake of birth sow colostrum, techniques such as split suckling prior to piglet movement should be implemented; (3) Udder assessment for functional teats should occur at farrowing, with number of fostered piglets not exceeding teat number; (4) Primiparous sows should receive as many piglets as the udder allows to maximise mammary stimulation, although older parities should be assessed for rearing ability; (5) Piglet fostering should occur between 12 and 24 h and movement kept to a minimum to prevent transfer of disease; Litter outliers should be moved and relocated to a litter of similar size; (6) Piglet movement after 24 h should be minimised. When required, strategies such as nurse usage should be employed. These principles will result in improved farrowing house performance by increasing the litter weight weaned per sow.
RESUMO
This study tested the hypothesis that piglets subjected to intermittent suckling (IS) would show changes in physiological and behavioral indices indicative of compromised welfare in the peri-weaning period. A total of 21 primiparous sows and their litters were allocated to either a control treatment (n = 10) where piglets were weaned conventionally, or an IS treatment (n = 11) where piglets were separated daily from their sows for 8 h starting the week before weaning. Performance, physiological and behavioral measures were taken at various time points during the week before and after weaning. Plasma cortisol levels were higher (p = 0.01) in IS piglets 7 d before weaning. Regardless of treatment, the N:L ratio at 3 d and 7 d after weaning was higher (p < 0.05) than that at 1 d before weaning. The IS piglets ate more creep feed during lactation (p < 0.05), and there was a tendency for the IS piglets to gain more weight between 3 d and 7 d after weaning (p < 0.1). This study showed that, aside from an increase in cortisol at the start of IS, piglets subjected to IS did not display physiological or behavioral changes indicative of compromised welfare.
RESUMO
OBJECTIVE: To assess the efficacy of omeprazole in treating irritable infants with gastroesophageal reflux and/or esophagitis. STUDY DESIGN: Irritable infants (n=30) 3 to 12 months of age met the entry criteria of esophageal acid exposure >5% (n=22) and/or abnormal esophageal histology (n=15). They completed a 4-week, randomized, double-blind, placebo-controlled crossover trial of omeprazole. Cry/fuss diary (minutes/24 hours) and a visual analogue scale of infant irritability as judged by parental impression were obtained at baseline and the end of each 2-week treatment period. RESULTS: The reflux index fell significantly during omeprazole treatment compared with placebo (-8.9%+/-5.6%, -1.9%+/-2.0%, P<.001). Cry/fuss time decreased from baseline (267+/-119), regardless of treatment sequence (period 1, 203+/-99, P<.04; period 2, 188+/-121, P<.008). Visual analogue score decreased from baseline to period 2 (6.8+/-1.6, 4.8+/-2.9, P=.008). There was no significant difference for both outcome measures while taking either omeprazole or placebo. CONCLUSIONS: Compared with placebo, omeprazole significantly reduced esophageal acid exposure but not irritability. Irritability improved with time, regardless of treatment.