Rotordynamic force estimation of turbulent, annular seals using OpenFOAM®

2021 ◽  
Vol 43 (3) ◽  
Author(s):  
Troy Snyder ◽  
Ilmar Santos
Keyword(s):  
Force Estimation ◽  
Annular Seals

Voltage- and Current-Measurement Based Force Estimation in Broaching Using Synchronous Motor Drive

2020 ◽  
Author(s):  
Kazumasa Miura ◽  
Tobias Seelbach ◽  
Thorsten Augspurger ◽  
Daniel Schraknepper ◽  
Thomas Bergs
Keyword(s):  
Synchronous Motor ◽  
Current Measurement ◽  
Motor Drive ◽  
Force Estimation ◽  
Synchronous Motor Drive

scholarly journals Orbit Decomposition Method for Rotordynamic Coefficients Identification of Annular Seals

2021 ◽  
Vol 11 (9) ◽  
pp. 4237
Author(s):  
Mingjie Zhang ◽  
Jiangang Yang ◽  
Wanfu Zhang ◽  
Qianlei Gu
Keyword(s):  
Circular Orbit ◽  
Present Method ◽  
Decomposition Method ◽  
Parameter Analysis ◽  
Elliptical Orbit ◽  
Computational Time ◽  
Solution Technique ◽  
Rotordynamic Coefficients ◽  
Cfd Method ◽  
Annular Seals

The elliptical orbit whirl model is widely used to identify the frequency-dependent rotordynamic coefficients of annular seals. The existing solution technique of an elliptical orbit whirl model is the transient computational fluid dynamics (CFD) method. Its computational time is very long. For rapid computation, this paper proposes the orbit decomposition method. The elliptical whirl orbit is decomposed into the forward and backward circular whirl orbits. Under small perturbation circumstances, the fluid-induced forces of the elliptical orbit model can be obtained by the linear superposition of the fluid-induced forces arising from the two decomposed circular orbit models. Due to that the fluid-induced forces of circular orbit, the model can be calculated with the steady CFD method, and the transient computations can be replaced with steady ones when calculating the elliptical orbit whirl model. The computational time is significantly reduced. To validate the present method, its rotordynamic results are compared with those of the transient CFD method and experimental data. Comparisons show that the present method can accurately calculate the rotordynamic coefficients. Elliptical orbit parameter analysis reveals that the present method is valid when the whirl amplitude is less than 20% of seal clearance. The effect of ellipticity on rotordynamic coefficients can be ignored.

scholarly journals Force estimation from 4D OCT data in a human tumor xenograft mouse model

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Maximilian Neidhardt ◽  
Nils Gessert ◽  
Tobias Gosau ◽  
Julia Kemmling ◽  
Susanne Feldhaus ◽  
...  
Keyword(s):  
Deep Learning ◽  
Mouse Model ◽  
Haptic Feedback ◽  
Human Tumor ◽  
Tumor Xenograft ◽  
Human Tumor Xenograft ◽  
Force Estimation ◽  
Xenograft Mouse Model ◽  
Dead Tissue

AbstractMinimally invasive robotic surgery offer benefits such as reduced physical trauma, faster recovery and lesser pain for the patient. For these procedures, visual and haptic feedback to the surgeon is crucial when operating surgical tools without line-of-sight with a robot. External force sensors are biased by friction at the tool shaft and thereby cannot estimate forces between tool tip and tissue. As an alternative, vision-based force estimation was proposed. Here, interaction forces are directly learned from deformation observed by an external imaging system. Recently, an approach based on optical coherence tomography and deep learning has shown promising results. However, most experiments are performed on ex-vivo tissue. In this work, we demonstrate that models trained on dead tissue do not perform well in in vivo data. We performed multiple experiments on a human tumor xenograft mouse model, both on in vivo, perfused tissue and dead tissue. We compared two deep learning models in different training scenarios. Training on perfused, in vivo data improved model performance by 24% for in vivo force estimation.

scholarly journals Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks

2021 ◽  
Author(s):  
Loris Roveda ◽  
Dario Piga
Keyword(s):  
Impedance Control ◽  
Interaction Force ◽  
Industrial Robots ◽  
Force Estimation ◽  
Interaction Control ◽  
Stiffness Properties ◽  
Implementation Effort ◽  
Coupling Dynamics ◽  
And Control ◽  
Assembly Tasks

AbstractIndustrial robots are increasingly used to perform tasks requiring an interaction with the surrounding environment (e.g., assembly tasks). Such environments are usually (partially) unknown to the robot, requiring the implemented controllers to suitably react to the established interaction. Standard controllers require force/torque measurements to close the loop. However, most of the industrial manipulators do not have embedded force/torque sensor(s) and such integration results in additional costs and implementation effort. To extend the use of compliant controllers to sensorless interaction control, a model-based methodology is presented in this paper. Relying on sensorless Cartesian impedance control, two Extended Kalman Filters (EKF) are proposed: an EKF for interaction force estimation and an EKF for environment stiffness estimation. Exploiting such estimations, a control architecture is proposed to implement a sensorless force loop (exploiting the provided estimated force) with adaptive Cartesian impedance control and coupling dynamics compensation (exploiting the provided estimated environment stiffness). The described approach has been validated in both simulations and experiments. A Franka EMIKA panda robot has been used. A probing task involving different materials (i.e., with different - unknown - stiffness properties) has been considered to show the capabilities of the developed EKFs (able to converge with limited errors) and control tuning (preserving stability). Additionally, a polishing-like task and an assembly task have been implemented to show the achieved performance of the proposed methodology.

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