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Статті в журналах з теми "Defect size estimation"
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Moskovchenko, Alexey, Michal Švantner, Vladimir Vavilov, and Arsenii Chulkov. "Characterizing Depth of Defects with Low Size/Depth Aspect Ratio and Low Thermal Reflection by Using Pulsed IR Thermography." Materials 14, no. 8 (April 10, 2021): 1886. http://dx.doi.org/10.3390/ma14081886.
Повний текст джерелаАнотація:
This study is focused on the quantitative estimation of defect depth by applying pulsed thermal nondestructive testing. The majority of known defect characterization techniques are based on 1D heat conduction solutions, thus being inappropriate for evaluating defects with low aspect ratios. A novel method for estimating defect depth is proposed by taking into account the phenomenon of 3D heat diffusion, finite lateral size of defects and the thermal reflection coefficient at the boundary between a host material and defects. The method is based on the combination of a known analytical model and a non-linear fitting (NLF) procedure. The algorithm was verified both numerically and experimentally on 3D-printed polylactic acid plastic samples. The accuracy of depth prediction using the proposed method was compared with the reference characterization technique based on thermographic signal reconstruction to demonstrate the efficiency of the proposed NLF method.
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Damaskinskaya, E. E., V. L. Hilarov, I. A. Panteleev, D. V. Korost, and K. A. Damaskinskii. "In-situ estimation of defect volume from parameters of acoustic emission signals." Journal of Physics: Conference Series 2103, no. 1 (November 1, 2021): 012066. http://dx.doi.org/10.1088/1742-6596/2103/1/012066.
Повний текст джерелаАнотація:
Abstract By using two methods of nondestructive testing, i.e., acoustic emission (AE) measurements and X-ray computed microtomography (CT), an experimental study of defect accumulation during a uniaxial compression of a natural heterogeneous material was carried out. A joint analysis of the AE and CT data revealed a correspondence between energy characteristics of the acoustic emission accompanying defect formation and volume of defects. It is shown that the dependence of the total energy of AE signals on the defect volume is linear, which is consistent with the phenomenological dependences for earthquake focuses obtained earlier. The linear dependence was used to estimate the average defect size. It is shown that, regardless of the assumed defect shape, its average linear size does not exceed 100 μm.
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Al-Ghamdi, A. M., P. Cole, R. Such, and D. Mba. "Estimation of bearing defect size with acoustic emission." Insight - Non-Destructive Testing and Condition Monitoring 46, no. 12 (December 1, 2004): 758–61. http://dx.doi.org/10.1784/insi.46.12.758.54491.
Повний текст джерела
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Shim, Won Heum, Sejoong Rim, Sang Wook Lim, June Kwan, Jong Won Ha, Moon Hyoung Lee, Namsik Chung, Seung Yun Cho, and Sung Soon Kim. "Estimation of Size of Adult Atrial Septal Defect." Korean Circulation Journal 26, no. 3 (1996): 631. http://dx.doi.org/10.4070/kcj.1996.26.3.631.
Повний текст джерела
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Wang, Hong'an, and Guoming Chen. "Defect size estimation method for magnetic flux leakage signals using convolutional neural networks." Insight - Non-Destructive Testing and Condition Monitoring 62, no. 2 (February 1, 2020): 86–90. http://dx.doi.org/10.1784/insi.2020.62.2.86.
Повний текст джерелаАнотація:
A method for defect size estimation of magnetic flux leakage (MFL) signals using convolutional neural networks (CNNs) is proposed to overcome the problem of quantitative identification of pipeline MFL testing. The model mainly includes two modules: defect classification and defect size regression. The former is used to realise data fusion, feature extraction and tasks of three components (axial, circumferential and radial) of the MFL defect signal. The defect size regression module includes seven CNNs, which realise the size estimation of different types of defect. The input is a different type of defect in the defect classification module and the output is the length, width and depth information of the defect. Finally, the training and prediction are conducted using a defect dataset. The results show that the proposed method can effectively identify the MFL defect size of the pipeline.
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Nabhan, Ahmed, and Ahmed Rashed. "Experimental and numerical investigation of defect-size estimation in taper roller bearing." Noise & Vibration Worldwide 49, no. 11 (September 26, 2018): 345–54. http://dx.doi.org/10.1177/0957456518801141.
Повний текст джерелаАнотація:
In this article, the estimation of different defect sizes present on the outer race of taper roller bearing confirms the effectiveness of the applied method for different vibration signals. Experiments and numerical model conducted for three primary conditions of bearing setting, which are positive, negative, and zero clearance. The outer race is installed in five different positions so that the defect located at 0°, 45°, 90°, 135°, and 180°. The output of the numerical model finds close correlation with the vibration signal pattern–obtained experiments. From the results, it is clear that defect-size estimation is more precise when the defect is introduced in the unloading area, and the contact time depends directly on the size of the defect, through which it is easy to calculate its value of the defect.
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Ciecieląg, Krzysztof, Krzysztof Kecik, and Kazimierz Zaleski. "Defects detection from time series of cutting force in composite milling process by recurrence analysis." Journal of Reinforced Plastics and Composites 39, no. 23-24 (June 20, 2020): 890–901. http://dx.doi.org/10.1177/0731684420935985.
Повний текст джерелаАнотація:
The article presents possibility of defects detection from milling time series using nonlinear methods: recurrence plots and recurrence quantifications. The defects are modeled as the holes with different diameters and depths. This allows estimation of the minimal size of defect possible to detect. Based on the conducted research, it has been shown that some of the recurrence indicators enable detection of defects. These recurrence indicators have been tested on the reals damage. Additionally, we show influence of the defect depth on the recurrence indicator values.
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Wermers, Jens, Benedikt Schliemann, Michael J. Raschke, Philipp A. Michel, Lukas F. Heilmann, Felix Dyrna, Julia Sußiek, Andre Frank, and J. Christoph Katthagen. "Glenoid concavity has a higher impact on shoulder stability than the size of a bony defect." Knee Surgery, Sports Traumatology, Arthroscopy 29, no. 8 (April 11, 2021): 2631–39. http://dx.doi.org/10.1007/s00167-021-06562-3.
Повний текст джерелаАнотація:
Abstract Purpose Surgical treatment of shoulder instability caused by anterior glenoid bone loss is based on a critical threshold of the defect size. Recent studies indicate that the glenoid concavity is essential for glenohumeral stability. However, biomechanical proof of this principle is lacking. The aim of this study was to evaluate whether glenoid concavity allows a more precise assessment of glenohumeral stability than the defect size alone. Methods The stability ratio (SR) is a biomechanical estimate of glenohumeral stability. It is defined as the maximum dislocating force the joint can resist related to a medial compression force. This ratio was determined for 17 human cadaveric glenoids in a robotic test setup depending on osteochondral concavity and anterior defect size. Bony defects were created gradually, and a 3D measuring arm was used for morphometric measurements. The influence of defect size and concavity on the SR was examined using linear models. In addition, the morphometrical-based bony shoulder stability ratio (BSSR) was evaluated to prove its suitability for estimation of glenohumeral stability independent of defect size. Results Glenoid concavity is a significant predictor for the SR, while the defect size provides minor informative value. The linear model featured a high goodness of fit with a determination coefficient of R2 = 0.98, indicating that 98% of the SR is predictable by concavity and defect size. The low mean squared error (MSE) of 4.2% proved a precise estimation of the SR. Defect size as an exclusive predictor in the linear model reduced R2 to 0.9 and increased the MSE to 25.7%. Furthermore, the loss of SR with increasing defect size was shown to be significantly dependent on the initial concavity. The BSSR as a single predictor for glenohumeral stability led to highest precision with MSE = 3.4%. Conclusion Glenoid concavity is a crucial factor for the SR. Independent of the defect size, the computable BSSR is a precise biomechanical estimate of the measured SR. The inclusion of glenoid concavity has the potential to influence clinical decision-making for an improved and personalised treatment of glenohumeral instability with anterior glenoid bone loss.
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Chen, Aoyu, and Thomas R. Kurfess. "A new model for rolling element bearing defect size estimation." Measurement 114 (January 2018): 144–49. http://dx.doi.org/10.1016/j.measurement.2017.09.018.
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Vasseur, Julien, Dmytro Vasiukov, Salim Chaki, Isabel Huther, Michel Marzin, Fabien Lefebvre, Benoît Dupont, and Nicolas Leymarie. "Fracture and determination of a lifetime of in-service mechanical components with porosity cluster in an aluminium alloy." MATEC Web of Conferences 300 (2019): 04001. http://dx.doi.org/10.1051/matecconf/201930004001.
Повний текст джерелаАнотація:
This paper focuses on the fatigue lifetime estimation of metallic components containing group of porosities as manufacturing defects. In order to represent these defects, six test specimens with different Side Drilled Holes (SDH) clusters, have been made of 7075-T6 aluminium alloy. Main characteristics of such defect (elementary size of porosities, spatial density or gradient of elementary sizes) have been studied by taking it into account in a FEM modelling in fatigue to determine their influence on the lifetime. Experimental tensile fatigue tests have been performed on all SDH samples with load ratio R=0.1. Semi-elliptical surfaces with a size of a typical Mg2Si particle of the studied alloy have been chosen as initial cracks for multiple crack propagation. Indeed, such a particle is often responsible for the initiation of a crack in this type of material. For crack growth, Paris’ type propagation law has been used. Local stress redistribution due to presence of the SDH implies mix-mode behaviour which has been considered by using G-theta method. Simulations results allowed realistic lifetime estimation according to the experimental ones. Moreover, a strong dependency of the crack paths and fatigue lifetime on the defect characteristics has been proved and quantified.
Дисертації з теми "Defect size estimation"
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Boyers, Albert S. "SPECT myocardial perfusion scans : a left ventricular defect size estimation algorithm and a three dimensional computer simulation." Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/14879.
Повний текст джерела
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Bin, Muhd Noor Nik Nooruhafidzi. "Statistical modelling of ECDA data for the prioritisation of defects on buried pipelines." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/16392.
Повний текст джерелаАнотація:
Buried pipelines are vulnerable to the threat of corrosion. Hence, they are normally coated with a protective coating to isolate the metal substrate from the surrounding environment with the addition of CP current being applied to the pipeline surface to halt any corrosion activity that might be taking place. With time, this barrier will deteriorate which could potentially lead to corrosion of the pipe. The External Corrosion Direct Assessment (ECDA) methodology was developed with the intention of upholding the structural integrity of pipelines. Above ground indirect inspection techniques such as the DCVG which is an essential part of an ECDA, is commonly used to determine coating defect locations and measure the defect's severity. This is followed by excavation of the identified location for further examination on the extent of pipeline damage. Any coating or corrosion defect found at this stage is repaired and remediated. The location of such excavations is determined by the measurements obtained from the DCVG examination in the form of %IR and subjective inputs from experts which bases their justification on the environment and the physical characteristics of the pipeline. Whilst this seems to be a straight forward process, the factors that comes into play which gave rise to the initial %IR is not fully understood. The lack of understanding with the additional subjective inputs from the assessors has led to unnecessary excavations being conducted which has put tremendous financial strain on pipeline operators. Additionally, the threat of undiscovered defects due to the erroneous nature of the current method has the potential to severely compromise the pipeline's safe continual operation. Accurately predicting the coating defect size (TCDA) and interpretation of the indication signal (%IR) from an ECDA is important for pipeline operators to promote safety while keeping operating cost at a minimum. Furthermore, with better estimates, the uncertainty from the DCVG indication is reduced and the decisions made on the locations of excavation is better informed. However, ensuring the accuracy of these estimates does not come without challenges. These challenges include (1) the need of proper methods for large data analysis from indirect assessment and (2) uncertainty about the probability distribution of quantities. Standard mean regression models e.g. the OLS, were used but fail to take the skewness of the distributions involved into account. The aim of this thesis is thus, to come up with statistical models to better predict TCDA and to interpret the %IR from the indirect assessment of an ECDA more precisely. The pipeline data used for the analyses is based on a recent ECDA project conducted by TWI Ltd. for the Middle Eastern Oil Company (MEOC). To address the challenges highlighted above, Quantile Regression (QR) was used to comprehensively characterise the underlying distribution of the dependent variable. This can be effective for example, when determining the different effect of contributing variables towards different sizes of TCDA (different quantiles). Another useful advantage is that the technique is robust to outliers due to its reliance on absolute errors. With the traditional mean regression, the effect of contributing variables towards other quantiles of the dependent variable is ignored. Furthermore, the OLS involves the squaring of errors which makes it less robust to outliers. Other forms of QR such as the Bayesian Quantile Regression (BQR) which has the advantage of supplementing future inspection projects with prior data and the Logistic Quantile Regression (LQR) which ensures the prediction of the dependent variable is within its specified bounds was applied to the MEOC dataset. The novelty of research lies in the approaches (methods) taken by the author in producing the models highlighted above. The summary of such novelty includes: * The use of non-linear Quantile Regression (QR) with interacting variables for TCDA prediction. * The application of a regularisation procedure (LASSO) for the generalisation of the TCDA prediction model.* The usage of the Bayesian Quantile Regression (BQR) technique to estimate the %IR and TCDA. * The use of Logistic Regression as a guideline towards the probability of excavation * And finally, the use of Logistic Quantile Regression (LQR) in ensuring the predicted values are within bounds for the prediction of the %IR and POPD. Novel findings from this thesis includes: * Some degree of relationship between the DCVG technique (%IR readings) and corrosion dimension. The results of the relationship between TCDA and POPD highlights a negative trend which further supports the idea that %IR has some relation to corrosion. * Based on the findings from Chapter 4, 5 and 6 suggests that corrosion activity rate is more prominent than the growth of TCDA at its median depth. It is therefore suggested that for this set of pipelines (those belonging to MEOC) repair of coating defects should be done before the coating defect has reached its median size. To the best of the Author's knowledge, the process of employing such approaches has never been applied before towards any ECDA data. The findings from this thesis also shed some light into the stochastic nature of the evolution of corrosion pits. This was not known before and is only made possible by the usage of the approaches highlighted above. The resulting models are also of novelty since no previous model has ever been developed based on the said methods. The contribution to knowledge from this research is therefore the greater understanding of relationship between variables stated above (TCDA, %IR and POPD). With this new knowledge, one has the potential to better prioritise location of excavation and better interpret DCVG indications. With the availability of ECDA data, it is also possible to predict the magnitude of corrosion activity by using the models developed in this thesis. Furthermore, the knowledge gained here has the potential to translate into cost saving measures for pipeline operators while ensuring safety is properly addressed.
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Dworak, Jennifer Lynn. "Modeling defective part level due to static and dynamic defects based upon site observation and excitation balance." Diss., Texas A&M University, 2004. http://hdl.handle.net/1969.1/323.
Повний текст джерелаАнотація:
Manufacture testing of digital integrated circuits is essential for high quality. However, exhaustive testing is impractical, and only a small subset of all possible test patterns (or test pattern pairs) may be applied. Thus, it is crucial to choose a subset that detects a high percentage of the defective parts and produces a low defective part level. Historically, test pattern generation has often been seen as a deterministic endeavor. Test sets are generated to deterministically ensure that a large percentage of the targeted faults are detected. However, many real defects do not behave like these faults, and a test set that detects them all may still miss many defects. Unfortunately, modeling all possible defects as faults is impractical. Thus, it is important to fortuitously detect unmodeled defects using high quality test sets. To maximize fortuitous detection, we do not assume a high correlation between faults and actual defects. Instead, we look at the common requirements for all defect detection. We deterministically maximize the observations of the leastobserved sites while randomly exciting the defects that may be present. The resulting decrease in defective part level is estimated using the MPGD model. This dissertation describes the MPGD defective part level model and shows how it can be used to predict defective part levels resulting from static defect detection. Unlike many other predictors, its predictions are a function of site observations, not fault coverage, and thus it is generally more accurate at high fault coverages. Furthermore, its components model the physical realities of site observation and defect excitation, and thus it can be used to give insight into better test generation strategies. Next, we investigate the effect of additional constraints on the fortuitous detection of defects-specifically, as we focus on detecting dynamic defects instead of static ones. We show that the quality of the randomness of excitation becomes increasingly important as defect complexity increases. We introduce a new metric, called excitation balance, to estimate the quality of the excitation, and we show how excitation balance relates to the constant τ in the MPGD model.
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Moazen-ahmadi, Alireza. "Vibration signatures of defective bearings and defect size estimation methods." Thesis, 2016. http://hdl.handle.net/2440/112971.
Повний текст джерелаАнотація:
Rolling element bearings are widely used in rotary machinery, often with extremely
demanding performance criteria. The failure of bearings is the most common reason for
machine breakdowns. Machine failures can be catastrophic, resulting in costly downtime
and sometimes in human casualties. The implementation of condition monitoring systems,
which use data from various sources to determine the state of bearings, is commonly used
to predict bearing failure. Hence, a considerable amount of attention has been devoted to
bearing failure modes, fault detection, fault development and life expectations of bearings.
The focus of this research is on the fault detection and defect size estimations of ball and
cylindrical rolling element bearings with outer race defects.
In classic bearing vibration condition monitoring methods, the trend of vibration
amplitudes is often used to determine when a bearing should be replaced. As a defect on
the surface of a bearing raceway enlarges, the changes in the size and shape of the defect
due to successive passes of the rolling elements can result in a fluctuation of the averaged
measured values of the vibration amplitude. As an alternative to studying measures of
vibration severity in order to determine the size of the defect indirectly, the actual
geometric arc length of a bearing defect can be determined from the vibration signal and
used to decide when to replace the bearing. The research in this project provides an insight
into both the stiffness behaviour of a defective bearing assembly, with ball and cylindrical
rolling elements, and the characteristics of the vibration signature in defective bearings in
order to identify the vibration features associated with the entry and exit events of bearing
defect. The ultimate aim of this research is to develop methods to accurately estimate the
size of a defect on the outer raceway of a bearing, which are not dependent on the magnitude of the vibration response, but instead use these features for tracking defect size
in bearings.
In the research conducted here, the vibration excitation of a bearing associated with linespall
defects is studied both experimentally and analytically. An improved nonlinear
dynamic model of the contact forces and vibration responses generated in defective rolling
element bearings is proposed to study the vibration characteristics in defective bearings. It
is demonstrated that previous models are not able to predict these events accurately
without making significant assumptions about the path of rolling elements in the defect
zone. Similar to the results of the analytical modelling, the experimental results show that
there are discrepancies in previous theories describing the path of the rolling elements in
the defect zone that have led to poor results in simulating the vibration response and the
existing defect size estimation methods. The parametric study presented here shows that
the relative angular extents between the entry and exit events on the vibration results
decrease with increasing load. Significant speed dependency of these angular extents is
shown by simulation and experimental measurements of defective bearings as the
operational speed increases. The sources of inaccuracy in the previously proposed defect
size estimation algorithms are identified and explained. A complete defect size estimation
algorithm is proposed that is more accurate and less biased by shaft speed when compared
with existing methods.
A method is presented for calculating and analysing the quasi-static load distribution and
varying stiffness of a bearing assembly with a raceway defect of varying load, depth,
length, and surface roughness. It has been found that as the shaft and rollers in a defective
bearing rotate, it causes the stiffness of the bearing assembly to vary, which cause
parametric vibration excitations of the bearing assembly. It is shown that when the defect size is greater than one angular roller spacing, signal aliasing occurs and the vibration
signature is similar to when the defect size is less than one angular roller spacing. Using
the results from simulations and experimental testing, signal processing techniques are
developed to distinguish defect sizes that are less than or greater than one angular roller
spacing.
The results of this study provide an improved hypothesis for the path of a rolling element
as it travels through a defect and its relationship to the vibration signature in a bearing.Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Mechanical Engineering, 2016
Книги з теми "Defect size estimation"
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Schreuder, Michiel F. Renal hypoplasia. Edited by Adrian Woolf. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199592548.003.0348.
Повний текст джерелаАнотація:
In true renal hypoplasia, normal nephrons are formed but with a deficit in total numbers. As nephron number estimation is not possible in vivo, renal size is used as a marker. A widely used definition of renal hypoplasia is kidneys with a normal appearance on ultrasound but with a size less than two standard deviations below the mean for gender, age, and body size. A distinct and severe form of renal hypoplasia is called (congenital) oligomeganephronia, which is characterized by small but normal-shaped kidneys with a marked reduction in nephron numbers (to as low as 10–20% of normal), a distinct enlargement of glomeruli, and a reduced renal function. In many cases, the small kidney also shows signs of dysplasia on ultrasound, leading to the diagnosis of renal hypodysplasia. Based on the hyperfiltration hypothesis and clinical studies, glomerular hyperfiltration can be expected, resulting in hypertension, albuminuria, and renal injury, for which long-term follow-up of all patients with renal hypoplasia is desirable.
Частини книг з теми "Defect size estimation"
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Singhal, Shyam, Beulah Moses, and Veena Jadhav. "Generalizing Software Defect Estimation Using Size and Two Interaction Variables." In Handbook on Artificial Intelligence-Empowered Applied Software Engineering, 55–74. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08202-3_4.
Повний текст джерела
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Light, Paul C. "A Warning Renewed." In The Government-Industrial Complex, 1–33. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190851798.003.0001.
Повний текст джерелаАнотація:
Chapter 1 provides a broad history of Dwight D. Eisenhower’s 1961 farewell address and the author’s methodology for estimating the true size of the government-industrial complex workforce. The chapter begins with Eisenhower’s decision to deliver a nationally televised speech warning the nation of the grave threats created by the conjunction of an imperative, but immense military and armaments industry. The chapter explores the history of the speech and the president’s chosen words for characterizing the military-industrial complex. The chapter continues with a discussion of the method used for estimating the true size of the federal, contract, and grant workforces. The method converts federal spending into estimates of the full-time-equivalent contract and grant employment for use in side-by-side comparisons to the federal workforce. The chapter ends with a discussion of the data deficit surrounding the government-industrial complex and warns readers that all data have expiration dates, including the data used in the book.
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Rosell, Frank, and Róisín Campbell-Palmer. "Territoriality, communication, and populations." In Beavers, 221–60. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780198835042.003.0007.
Повний текст джерелаАнотація:
Beavers are highly territorial and actively defend a territory that includes nutritional resources, one or more rest sites, a family overwintering site, and a reproduction site. New territories are normally established during early autumn when dispersing subadults settle down in a new area of their own, but this can vary considerably. Each family group scent marks its territories with castoreum and/or anal gland secretion. Territory size is generally measured as the length of shoreline but can also be expressed as a combination of terrestrial and aquatic patches used by the beavers in a two-dimensional space. The territorial size depends on many factors such as habitat quality and quantity, habitat type (stream, river, or pond), density of beavers, social factors (sex and age), time of year (season), and settlement pattern. Beavers patrol their territory to look out for intruders and potential predators and scent mark their territory with fluid from their castor sacs and/or secretions from their anal glands. Territorial defence can include direct fighting or even more unusual warning behaviours such as boundary stick displays. The duration of territory occupancy and its importance for the fitness of beavers are also discussed. Further, this chapter explores beaver communication using odours, sounds, tail slapping, poses, and other movements. Beavers predominantly communicate via odours, but the importance of all these modalities is explored. Lastly, population estimations, growth, fluctuations, and densities of beaver populations are discussed.
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Pon Bharathi, A., Allan J. Wilson, S. Arun, and V. Ramanathan. "A Compact Disc Shaped Microstrip Patch Antenna Using Inset Fed at 5GHz for Satellite Communications." In Recent Trends in Intensive Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210181.
Повний текст джерелаАнотація:
This examination work is focused around planning and simulating another kind of inset feed Disc Shaped Microstrip Patch Antenna (DSMPA) with Inset feed and Defected ground plane (DGP). By presenting a round space at the focal point of the ground plane, improved attributes of Microstrip patch antenna can be accomplished. The proposed Disc Shaped Microstrip patch antenna is reverberating at 5 GHz. Simulation has been finished by utilizing reenactment programming HFSS version15. From recreation results, it discovers that our examined Disc Shaped Microstrip patch antenna yields better return loss of - 25.1 dB & VSWR estimation of 0.96 dB. The examined DSMPA is yielding a higher radiation efficiency of 77.20 %. The minimized size and higher radiation efficiency contrasted with rectangular Microstrip patch antenna makes it all the more generally helpful for satellite communications.
Тези доповідей конференцій з теми "Defect size estimation"
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Murthy, Aravind N., Karl A. Flechsig, Wes Hillman, Keith Conard, and Remmelt Pit. "Thermal Fly-Height Controlled Glide for Disk Defect Detection and In-Situ Defect Size Estimation for Disk Drives." In ASME 2013 Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/isps2013-2805.
Повний текст джерелаАнотація:
Current hard disk drives (HDD’s) use thermal fly-height control (TFC) during read/write operations. In this study, we use TFC technology during the disk glide process to determine sub-5nm height defects. We also utilize TFC to measure the height of the defect during glide operation. Addtionally, we magnetically mark the disk locations where defects are detected for further post-processing of the defects using optical surface analysis (OSA), atomic force microscopy (AFM), and scanning electron microscopy (SEM). The defect height estimation during the glide was confirmed to be accurate by AFM and SEM analysis. Finally, we will present the TFC glide sensitivity showing capability of detecting smaller defects than conventional non-TFC glide technologies.
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Revel, Gian Marco, Giuseppe Pandarese, and Gloria Allevi. "Quantitative defect size estimation in shearography inspection by wavelet transform and shear correction." In 2017 IEEE International Workshop on Metrology for AeroSpace (MetroAeroSpace). IEEE, 2017. http://dx.doi.org/10.1109/metroaerospace.2017.7999631.
Повний текст джерела
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Chen, Jenny Jing, Stephen Westwood, and David Heaney. "A Feature-Specific Probabilistic Assessment of Pipeline Defect Size From ILI MFL Signal Using Convolutional Neural Network." In 2020 13th International Pipeline Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/ipc2020-9331.
Повний текст джерелаАнотація:
Abstract When estimating pipeline burst pressure, one of the prevalent sources of uncertainty that needs to be factored into the calculation is the model error in the estimation of feature depth and length from the in-line inspection tool. Due to modeling technique limitation, as of today many ILI vendors have feature specific error bounds depending on the morphologies of the corrosion, this error can only be reported to operators as an overall error known as the ILI tool tolerance which is usually obtained from samples of excavation data or pull test data. At the most, the error is reported by classes based on corrosion morphologies specified by Pipeline Operators Forum. For example, a commonly reported corrosion depth sizing specification is ±10% of pipe wall thickness at 80% confidence for the General type of corrosion. This can be interpreted as that the error of each reported depth estimations is assumed to fall in a normal distribution with a mean equal to 0 and standard deviation equal to 7.8% of wall thickness. The shape of the distribution, the mean and standard deviation will then be used as constants to factor in the burst pressure calculation. However, these factors are never constant for a sample of defects in reality. In fact, they ought to be variables on an individual feature basis. An example of such an approach would be a feature specific error tolerance, this could be that the estimated depth of a feature is 36%wt in an interval of [30%, 48%] of wall thickness with 80% confidence. This is believed to greatly reduce the level of uncertainty when it comes to failure pressure estimation or other type of pipeline risk assessment. The advancement in Machine Learning today, deep learning with deep neural networks, allows feature-specific error tolerance to be obtained after analyzing visual imagery of MFL signal. In this paper we will describe a novel approach to predict the size of metal loss defects and more importantly the distribution associated with each prediction. We will then discuss the benefits of this approach has with respect to risk assessment such as failure pressure estimation.
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Gautier, S., and L. Cha˜tellier. "A Help for Lifetime Management: Defect Characterisation Through Signal Processing of Ultrasonic Data." In ASME 2003 Pressure Vessels and Piping Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/pvp2003-2159.
Повний текст джерелаАнотація:
So as to detect and to characterize potential defects on cast components, a program of in-service inspections is carried out for the non destructive evaluation (NDE) of the component. A first step of inspection usually consists in detection. Still, should a defect be detected, one can be asked to prove the component still stands the mechanical constraints. Then, it is very important to be able to characterize precisely the size and the position of the defect. In the studied case, we concentrate on planar defects which are to be characterized from ultrasonic. The estimation of the height consists in measuring the time of flight between two reflectors: the diffraction and the corner echoes. But in case of small defects, the two echoes overlap and it is very difficult to give a height estimation of the defect. Then, the core of our contribution deals with the signal processing method we developed for the estimation of the height of planar defects. The use of our so-called deconvolution process now enables to obtain the height estimation of the defect, when it was impossible without processing. Processing results of real data sets are given for the inspection of representative mock-ups of homogeneous austenitic welds. In conclusion, the signal processing step turns out to be an important step in the characterization of defects and can thus contributes to maintain some components in service.
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Feng, Tie, Cunlin Zhang, and Lichun Feng. "The effect of depth on the quantitative estimation of defect size using pulsed thermography." In International Symposium on Photoelectronic Detection and Imaging 2011. SPIE, 2011. http://dx.doi.org/10.1117/12.900752.
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Yoshikawa, Takao, Masahiro Maeda, and Hideyuki Hirasawa. "A Study on Construction of Evaluation Method for Defect Sizing Utilizing Numerical Simulation." In ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-49349.
Повний текст джерелаАнотація:
To prevent the brittle fracture of the extremely thick plate which is used in the deck plate and the hatch side coaming of the large container ships, it is important to detect surely and repair the inner defects, which are possible to lead the brittle fracture at an early stage. Now Ultrasonic Testing is used in order to inspect the inner defect in a thick plate, and it is necessary to select adequately the probe size and oscillating frequency to evaluate the defect size accurately. The estimation of the defect size in vertical direction to plate surface is important from the viewpoint of fatigue strength. But the vertical flaw length and also the inclined flaw length are hardly to be estimated accurately. In this study, to clarify the characteristics of reflected ultrasonic wave from the defect, the wave propagation behavior is simulated with the numerical simulation program by FEM which is developed by the authors. In this program, the governing equation of elastic wave propagation is calculated in time domain with explicit method utilizing the central-difference scheme. First, the effect of the probe size and oscillating frequency on the accuracy of defect sizing are investigated utilizing the developed program. The numerical simulation is performed for imaging to examine the length of flaw which is parallel to plate surface by normal beam technique. And, the applicability of 6dB method, which is one of the methods for estimating flaw length, is examined. Moreover, a new method for estimating flaw length which cannot be estimated by 6dB method is proposed. Secondly, in order to examine the inclined flaw length, the angel beam test is performed. The accuracy of numerical simulation for angle beam technique is confirmed by comparing experimental result. And, it is examined how the inclined angle of flaw affects the echo height, and it is shown that 6dB method and L level method are useful for the defect which is perpendicular to wave beam and the tip echo method is useful for the defect which is inclined to wave beam. The actual structure usually has a paint film. Therefore, the echo height level will be affected by paint thickness, and the paint film effects on the accuracy of defect sizing. Thirdly, the effects on echo height by film thickness are clarified by experiments and numerical simulations.
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Mu, Rangke, and Chun-sheng Zhao. "A New Method for the Pile Quality Detection: Estimation of the Shape of a Pile." In ASME 1991 Design Technical Conferences. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/detc1991-0373.
Повний текст джерелаАнотація:
Abstract In this paper, a new method for the pile quality detection is developed, which is the Estimation of the Shape of a pile (also called the ESP method). It has considered many defects and their high time reflections in a pile by using echo technique. At this we have carried out the computer simulation and the field tests by transient impact excitation on the head of the pile. It is proved that the ESP method is feasible for the pile quality detection, and the size, type, and site of a defect in a pile can be accurately determined by using it.
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Fazeli, Hamid, Masoud Mirzaei, and Pourya Forooghi. "Estimation of Location and Size of Defects in a Solid Body via Inverse Heat Conduction Problem." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-23075.
Повний текст джерелаАнотація:
In the present paper, geometry specification in the inverse heat conduction problems (IHCP) is applied to detect the location and size of defect in a solid body. A crack or cavity is modeled as a supper-elliptic geometry whose parameters are estimated with inverse heat conduction problems. Both inverse analysis and gradient-based optimization method have been applied to an inverse algorithm that iteratively estimates the defect shape parameters. The inverse analysis is based on recording temperatures data on outer surface of solid domain that determines the objective function in the inverse algorithm with estimated and calculated temperatures. The employed gradient-based optimization method is constructed with the adjoint and sensitivity equations that are used to calculate the gradient of the objective function and the search step size, respectively. An unstructured grid is used and the computational domain is discretized with triangular elements. The finite element method (FEM) is employed to discretize the equations in analysis plus sensitivity and adjoint equations. The effects of different Biot numbers and noisy temperature data are investigated on inverse algorithm and the size and location of crack and complex cavity are calculated. Results show that the estimated shape has good agreement with exact shape of defect. The decrease of noisy data has improve the convergence rate and the increase of Biot numbers causes the estimated shape has the best accuracy in all cases.
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Manohar, Arun, and Francesco Lanza di Scalea. "Modeling Heat Flow Interaction With Defects in Composite Materials Using Virtual Heat Sources in Pulsed Thermography." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-62568.
Повний текст джерелаАнотація:
Quantitative defect detection in composite structures is an important problem as the aerospace and wind energy industries are increasingly using composites due to their attractive properties. Newer aircraft contain over 50% composites, while the wind turbine blades contain over 95% composites. Quantitative estimation of defect parameters is relevant to perform repairs and assess the integrity of these structures. Previous studies are based on simple 1D heat conduction models, which are inadequate in predicting heat flow around defects, especially in composites where the ratio of longitudinal to transverse thermal conductivity is about 100. In this study, a novel heat conduction model is proposed to model heat flow around defects accounting for 3D heat conduction in quasi-isotropic composites. The validity of the proposed methodology is established using experiments performed on a CFRP panel containing defects of different dimensions at different depths. The inverse problem could be used to quantitatively determine the defect depth and size.
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Orynyak, Igor, Maksym Zarazovskii, and Mykhaylo Borodii. "The Method for Structural Reliability Estimation of the Heat Exchanger Tubes of Steam Generator of WWER NPPs." In ASME 2016 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/pvp2016-63710.
Повний текст джерелаАнотація:
After the replacement due to the well known problem of weld seam #111 the steam generators (SG) of the Ukrainian WWER-1000 type nuclear power plants (NPP) have been in operation for almost 25 years. So now, the main practical problem related to the SG is the leakage/breaking of heat exchanger tubes (HET). If the leakage criterion is not satisfied the NPP Unit has to be stopped until the corresponding HET is plugged, which leads to unexpected huge financial losses. Every year at least 12.5% of the SG HETs are controlled by eddy current inspection, after which some of the HETs are plugged according to the appropriate plugging criteria (in most cases – 65% loss of tube wall thickness). Thus, every SG has its own statistics of plugging. From the practical point of view the Utility is interested in the following questions: whether the failure of the HET happens during the normal operation mode (NOM) up to the next NPP stop or not; what is the probability of this event; what is the defect growth rate? Answers on these questions could give us the opportunity to increase the effectiveness of the HET in-service inspection and to improve the plugging criterion. A simple statistically-based method for HET integrity assessment is proposed. The method based on an exponent distribution law and HET plugging statistics of specific SG, taking into account defect growth. Based on the history of the tubes plugging (year of operation versus quantity of pluggings) the three statistical parameters inherent to this specific SG have to be found: initial number of defects, parameter of the exponential distribution (initial defect size) and the defect growth rate. The developed method was used for the prediction of HET leak/break number for all Ukrainian WWER-1000 SG. It is shown that for those SG which has less than 2% HET pluggings the accumulated pluggings as of the end of the next year of NOM will not exceed this value. Based on the Ukrainian history of WWER-1000 SG operation the database of HET plugging is presented. This method is also used for justification of pressure reduction of periodic hydrostatic test (HT) for primary circuit of WWER-1000 and WWER-440 NPPs from 24.5 MPa to 20.3 MPa and from 19.1 MPa to 15.7 MPa, correspondingly. To justify a reduction of the HT pressure, a quantitative, risk-informed assessment of HT effectiveness has been performed with taking into account the HT pressures change. The HET failure probability is calculated as the proportion of defects which exceed critical sizes for NOM and HT. Limit load models are used for the determination of the critical defects size. The variation of reliability is calculated as the difference between fracture probability during NOM after HT at routine and reduced pressures. It is shown that HT pressure reduction does not practically increase the fracture probability during operation, and satisfies the criteria of risk change.
Звіти організацій з теми "Defect size estimation"
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
Повний текст джерелаАнотація:
The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
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Financial Stability Report - September 2015. Banco de la República, August 2021. http://dx.doi.org/10.32468/rept-estab-fin.sem2.eng-2015.
Повний текст джерелаАнотація:
From this edition, the Financial Stability Report will have fewer pages with some changes in its structure. The purpose of this change is to present the most relevant facts of the financial system and their implications on the financial stability. This allows displaying the analysis more concisely and clearly, as it will focus on describing the evolution of the variables that have the greatest impact on the performance of the financial system, for estimating then the effect of a possible materialization of these risks on the financial health of the institutions. The changing dynamics of the risks faced by the financial system implies that the content of the Report adopts this new structure; therefore, some analyses and series that were regularly included will not necessarily be in each issue. However, the statistical annex that accompanies the publication of the Report will continue to present the series that were traditionally included, regardless of whether or not they are part of the content of the Report. In this way we expect to contribute in a more comprehensive way to the study and analysis of the stability of the Colombian financial system. Executive Summary During the first half of 2015, the main advanced economies showed a slow recovery on their growth, while emerging economies continued with their slowdown trend. Domestic demand in the United States allowed for stabilization on its average growth for the first half of the year, while other developed economies such as the United Kingdom, the euro zone, and Japan showed a more gradual recovery. On the other hand, the Chinese economy exhibited the lowest growth rate in five years, which has resulted in lower global dynamism. This has led to a fall in prices of the main export goods of some Latin American economies, especially oil, whose price has also responded to a larger global supply. The decrease in the terms of trade of the Latin American economies has had an impact on national income, domestic demand, and growth. This scenario has been reflected in increases in sovereign risk spreads, devaluations of stock indices, and depreciation of the exchange rates of most countries in the region. For Colombia, the fall in oil prices has also led to a decline in the terms of trade, resulting in pressure on the dynamics of national income. Additionally, the lower demand for exports helped to widen the current account deficit. This affected the prospects and economic growth of the country during the first half of 2015. This economic context could have an impact on the payment capacity of debtors and on the valuation of investments, affecting the soundness of the financial system. However, the results of the analysis featured in this edition of the Report show that, facing an adverse scenario, the vulnerability of the financial system in terms of solvency and liquidity is low. The analysis of the current situation of credit institutions (CI) shows that growth of the gross loan portfolio remained relatively stable, as well as the loan portfolio quality indicators, except for microcredit, which showed a decrease in these indicators. Regarding liabilities, traditional sources of funding have lost market share versus non-traditional ones (bonds, money market operations and in the interbank market), but still represent more than 70%. Moreover, the solvency indicator remained relatively stable. As for non-banking financial institutions (NBFI), the slowdown observed during the first six months of 2015 in the real annual growth of the assets total, both in the proprietary and third party position, stands out. The analysis of the main debtors of the financial system shows that indebtedness of the private corporate sector has increased in the last year, mostly driven by an increase in the debt balance with domestic and foreign financial institutions. However, the increase in this latter source of funding has been influenced by the depreciation of the Colombian peso vis-à-vis the US dollar since mid-2014. The financial indicators reflected a favorable behavior with respect to the historical average, except for the profitability indicators; although they were below the average, they have shown improvement in the last year. By economic sector, it is noted that the firms focused on farming, mining and transportation activities recorded the highest levels of risk perception by credit institutions, and the largest increases in default levels with respect to those observed in December 2014. Meanwhile, households have shown an increase in the financial burden, mainly due to growth in the consumer loan portfolio, in which the modalities of credit card, payroll deductible loan, revolving and vehicle loan are those that have reported greater increases in risk indicators. On the side of investments that could be affected by the devaluation in the portfolio of credit institutions and non-banking financial institutions (NBFI), the largest share of public debt securities, variable-yield securities and domestic private debt securities is highlighted. The value of these portfolios fell between February and August 2015, driven by the devaluation in the market of these investments throughout the year. Furthermore, the analysis of the liquidity risk indicator (LRI) shows that all intermediaries showed adequate levels and exhibit a stable behavior. Likewise, the fragility analysis of the financial system associated with the increase in the use of non-traditional funding sources does not evidence a greater exposure to liquidity risk. Stress tests assess the impact of the possible joint materialization of credit and market risks, and reveal that neither the aggregate solvency indicator, nor the liquidity risk indicator (LRI) of the system would be below the established legal limits. The entities that result more individually affected have a low share in the total assets of the credit institutions; therefore, a risk to the financial system as a whole is not observed. José Darío Uribe Governor