scholarly journals Detection and Positioning of Pipes and Columns with Autonomous Multicopter Drones

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Edmundo Guerra ◽  
Rodrigo Munguía ◽  
Yolanda Bolea ◽  
Antoni Grau
Keyword(s):  
Experimental Data ◽  
Multiple Solutions ◽  
Parametric Method ◽  
Vision Sensors ◽  
Pose Recovery ◽  
Combined Solution ◽  
Real Experimental Data

A multimodal sensory array to accurately position aerial multicopter drones with respect to pipes has been studied, and a solution exploiting both LiDAR and vision sensors has been proposed. Several challenges, including detection of pipes and other cylindrical elements in sensor space and validation of the elements detected, have been studied. A probabilistic parametric method has been applied to segment and position cylinders with LIDAR, while several vision-based techniques have been tested to find the contours of the pipe, combined with conic estimation cylinder pose recovery. Multiple solutions have been studied and analyzed, evaluating their results. This allowed proposing an approach that combines both LiDAR and vision to produce robust and accurate pipe detection. This combined solution is validated with real experimental data.

scholarly journals Exact Solution for Viscoelastic Flow in Pipe and Experimental Validation

Polymers ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 334
Author(s):  
Ekaterina Vachagina ◽  
Nikolay Dushin ◽  
Elvira Kutuzova ◽  
Aidar Kadyirov
Keyword(s):  
Experimental Data ◽  
Exact Solution ◽  
Analytical Methods ◽  
Experimental Validation ◽  
Parametric Method ◽  
Fluid Flows ◽  
Parametric Representation ◽  
Viscoelastic Flow ◽  
Exponential Form ◽  
Image Velocimetry

The development of analytical methods for viscoelastic fluid flows is challenging. Currently, this problem has been solved for particular cases of multimode differential rheological equations of media state (Giesekus, the exponential form of Phan-Tien-Tanner, eXtended Pom-Pom). We propose a parametric method that yields solutions without additional assumptions. The method is based on the parametric representation of the unknown velocity functions and the stress tensor components as a function of coordinate. Experimental flow visualization based on the SIV (smoke image velocimetry) method was carried out to confirm the obtained results. Compared to the Giesekus model, the experimental data are best predicted by the eXtended Pom-Pom model.

scholarly journals Semi-analytical solution for the problem of extended Pom-Pom fluid flow in a round pipe

2021 ◽  
Vol 2057 (1) ◽  
pp. 012007
Author(s):  
A I Kadyirov ◽  
E K Vachagina
Keyword(s):  
Experimental Data ◽  
Fluid Flow ◽  
Analytical Solution ◽  
Solution Method ◽  
Parametric Method ◽  
Single Equation ◽  
Weissenberg Number ◽  
Normal Stresses ◽  
Rheological Equation ◽  
Rheological Equation Of State

Abstract A semi-analytical solution to the problem of the steady flow of viscoelastic single equation eXended Pom-Pom (XPP) fluid in a round pipe using the four-mode rheological equation of state of XPP is presented. An original parametric method for solving the set problem is used. The resulting method is applicable for solving a similar problem in a flat slit. The developed solution method is tested by comparing it with numerical results and experimental data. Using a polyacrylamide solution as an example, the influence of the Weissenberg number on the axial velocity profiles and the components of normal stresses is studied.

How to prevent undesired oscillation in NC rotary table

2015 ◽  
Vol 23 (20) ◽  
pp. 3490-3503
Author(s):  
Ali Ghaffari ◽  
Ebrahim Mohammadiasl
Keyword(s):  
Experimental Data ◽  
Limit Cycle ◽  
Operating Conditions ◽  
Rotary Table ◽  
Describing Function ◽  
Rotary Axis ◽  
Milling Operations ◽  
Complete Set ◽  
Simulation Results ◽  
Real Experimental Data

Heavy lathe-mill and turn-mill machine tools with both turning and milling operations are usually equipped with a frictional brake system to mitigate the effect of the mechanical backlash on the gear driven rotary table. In this paper the simultaneous effects of the coupled nonlinear frictions and backlashes on the positioning of the rotary axis have been investigated theoretically and empirically. Using the describing function method, it is shown that the undesired oscillations of the system are due to the existence of a limit cycle in the nonlinear closed-loop trajectory pattern of the rotary axis. Some simple practical rules are proposed for parameters adjustment of the rotary table, to assure that limit cycle is not created, and the multi-function machine does not oscillate improperly. The proposed rules can be used both at the designing stage and also during the maintenance of the machine. In order to verify the simulation results, a complete set of experimental data in a heavy lathe-mill machine has been utilized. It is shown that the deviation between the simulation results and the real experimental data at different operating conditions are quite small.

Clustering and Local Magnification Effects in Atom Probe Tomography: A Statistical Approach

2010 ◽  
Vol 16 (5) ◽  
pp. 643-648 ◽  
Author(s):  
Thomas Philippe ◽  
Maria Gruber ◽  
François Vurpillot ◽  
D. Blavette
Keyword(s):  
Experimental Data ◽  
Atom Probe Tomography ◽  
Statistical Approach ◽  
Nearest Neighbor ◽  
Three Dimensional ◽  
Atom Probe ◽  
Quantitative Composition ◽  
Second Phase ◽  
Real Experimental Data ◽  
Open Issues

AbstractLocal magnification effects and trajectory overlaps related to the presence of a second phase (clusters) are key problems and still open issues in the assessment of quantitative composition data in three-dimensional atom probe tomography (APT) particularly for tiny solute-enriched clusters. A model based on the distribution of distance of first nearest neighbor atoms has been developed to exhibit the variations in the apparent atomic density in reconstructed volumes and to correct compositions that are biased by local magnification effects. This model was applied to both simulated APT reconstructions and real experimental data and shows an excellent agreement with the expected composition of clusters.

scholarly journals Posture similarity index: A method to compare hand postures in synergy space

2018 ◽  
Author(s):  
Nayan Bhatt ◽  
Varadhan SKM
Keyword(s):  
Experimental Data ◽  
Synthetic Data ◽  
Similarity Index ◽  
Principal Component ◽  
Synthetic Dataset ◽  
Human Hand ◽  
Joint Angles ◽  
Task Requirements ◽  
Kinematic Synergies ◽  
Real Experimental Data

Background The Human hand can perform a range of manipulation tasks, from holding a pen to holding a hammer. Central Nervous System (CNS) uses different strategies in different manipulation tasks based on task requirements. Several attempts to compare postures of the hand have been made. Some of these have been developed for use in Robotics and animation industries. In this study, we develop an index to quantify the similarity between two human hand postures, the posture similarity index. Methods Twelve right-handed volunteers performed 70 postures and lifted and held 30 objects (total of 100 different postures, each performed 5 times). Kinematics of individual finger phalanges (segments) were captured by using a 16-sensor electromagnetic tracking sensor system. The hand was modelled as a 21-DoF system and the corresponding joint angles were computed. We used principal component analysis to extract kinematic synergies from this 21-DoF data. We developed a posture similarity index (PSI), that represents similarity between posture in the synergy (Principal component) space. First, performance of this index was tested using a synthetic dataset. After confirming that it performs well with synthetic dataset, we used it to analyse experimental data. Further, we used PSI to identify postures that are representative in the sense that they have a greater overlap (in synergy space) with a large number of postures. Results Using synthetic data and real experimental data, it was found that PSI was a relatively accurate index of similarity in synergy space. Also, it was found that more special postures than common postures were found among “representative” postures. Conclusion An index for comparing posture similarity in synergy space has been developed and its use has been demonstrated using synthetic dataset and experimental dataset. In addition, we found that special postures are actually special in the sense that there are more of them in the “representative” postures as identified by our posture similarity index.

Research on Beam Emission Spectroscopy Combined HL-2A Tokamak Real Experimental Data With Spectra Simulation Code

2019 ◽  
Vol 47 (1) ◽  
pp. 457-461 ◽  
Author(s):  
J. Wu ◽  
Y. C. Chen ◽  
P. Chen ◽  
Y. J. Chen ◽  
L. M. Yao ◽  
...  
Keyword(s):  
Experimental Data ◽  
Emission Spectroscopy ◽  
Simulation Code ◽  
Real Experimental Data

scholarly journals A Systematic Grey-Box Modeling Methodology via Data Reconciliation and SOS Constrained Regression

Processes ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 170 ◽  
Author(s):  
José Pitarch ◽  
Antonio Sala ◽  
César de Prada
Keyword(s):  
Experimental Data ◽  
Data Reconciliation ◽  
Process Systems ◽  
Optimization Framework ◽  
Constrained Regression ◽  
Modeling Methodology ◽  
Advanced Control ◽  
Systematic Methodology ◽  
Real Time Optimization ◽  
Real Experimental Data

Developing the so-called grey box or hybrid models of limited complexity for process systems is the cornerstone in advanced control and real-time optimization routines. These models must be based on fundamental principles and customized with sub-models obtained from process experimental data. This allows the engineer to transfer the available process knowledge into a model. However, there is still a lack of a flexible but systematic methodology for grey-box modeling which ensures certain coherence of the experimental sub-models with the process physics. This paper proposes such a methodology based in data reconciliation (DR) and polynomial constrained regression. A nonlinear optimization of limited complexity is to be solved in the DR stage, whereas the proposed constrained regression is based in sum-of-squares (SOS) convex programming. It is shown how several desirable features on the polynomial regressors can be naturally enforced in this optimization framework. The goodnesses of the proposed methodology are illustrated through: (1) an academic example and (2) an industrial evaporation plant with real experimental data.

scholarly journals Coupling Analytical Models and Machine Learning Methods for Fast and Reliable Resolution of Effects in Multifrequency Eddy-Current Sensors

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 618
Author(s):  
Sergey Kucheryavskiy ◽  
Alexander Egorov ◽  
Victor Polyakov
Keyword(s):  
Machine Learning ◽  
Experimental Data ◽  
Eddy Current ◽  
Prediction Models ◽  
Parameters Estimation ◽  
Analytical Models ◽  
Conductive Materials ◽  
Machine Learning Methods ◽  
Lift Off ◽  
Real Experimental Data

Eddy current (EC) measurements, widely used for diagnostics of conductive materials, are highly dependent on physical properties and geometry of a sample as well as on a design of an EC-sensor. For a sensor of a given design, the conductivity and thickness of a sample as well as the gap between the sample and the sensor (lift-off) are the most influencing parameters. Estimation of these parameters, based on signals acquired from the sensor, is quite complicated in case when all three parameters are unknown and may vary. In this paper, we propose a machine learning based approach for solving this problem. The approach makes it possible to avoid time and resource-consuming computations and does not require experimental data for training of the prediction models. The approach was tested using independent sets of measurements from both simulated and real experimental data.

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