Parameters Estimation For A Patellofemoral Joint Of A Human Knee Using A Vector Method

Ciszkiewicz, Adam; Knapczyk, Józef

doi:10.1515/ijame-2015-0041

Cited by 3 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the one hand, it is a simplified model of the human knee mechanism concentrating on the main flexion/extension movement just in the sagittal plane. In this way it constitutes a simplification of already developed complicated and complex models taking into consideration the 3D movement, meniscus, patella (Ciszkiewicz and Knapczyk [21]) and other elements that are based mainly on bone surface cooperation (Ciszkiewicz and Knapczyk [2]). On the other hand, the proposed solution is an advance with respect to the other existing mechanisms, since it takes into consideration the complexity (roll and slide) of flexion/extension movement.…”

Section: Discussionmentioning

confidence: 99%

Design and Characterization of a Novel Knee Articulation Mechanism

Olinski¹,

Gronowicz²,

Handke³

et al. 2016

International Journal of Applied Mechanics and Engineering

View full text Add to dashboard Cite

The paper is focused on designing a novel controllable and adjustable mechanism for reproducing human knee joint's complex motion by taking into account the flexion/extension movement in the sagittal plane, in combination with roll and slide. Main requirements for a knee rehabilitation supporting device are specified by researching the knee's anatomy and already existing mechanisms. A three degree of freedom (3 DOF) system (four-bar like linkage with controlled variable lengths of rockers) is synthesised to perform the reference path of instantaneous centre of rotation (ICR). Finally, a preliminary design of the adaptive mechanism is elaborated and a numerical model is built in Adams. Numerical results are derived from simulations that are presented to evaluate the accuracy of the reproduced movement and the mechanism's capabilities.

show abstract

Section: Discussionmentioning

confidence: 99%

Design and Characterization of a Novel Knee Articulation Mechanism

Olinski¹,

Gronowicz²,

Handke³

et al. 2016

International Journal of Applied Mechanics and Engineering

View full text Add to dashboard Cite

show abstract

“…For analyzing the effects of electrical discharge machining process parameters on performance factors, as well as developing empirical models, the RSM has been the most widely used technique in recent years [ 30 ]. It includes a set of mathematical and experimental techniques that require sufficient experimental data to analyze the problem and develop mathematical models that consider the dependencies of several input variables and the resulting factors [ 27 , 31 , 32 ]. This feature is important because the EDM process usually analyses the influence of several input factors (usually three, four or more), which can include: open circuit voltage, pulse-on-time, pulse-off-time, discharge current, duty cycle, working-fluid flushing pressure, electrode, electrode polarity, electrode material, and initial interelectrode gap [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Modelling and Analysis of the Effect of EDM-Drilling Parameters on the Machining Performance of Inconel 718 Using the RSM and ANNs Methods

2022

View full text Add to dashboard Cite

Electrical Discharge Machining (EDM) is one of the most efficient processes to produce high-ratio micro holes in difficult-to-cut materials in the Inconel 718 superalloy. It is important to apply a statistical technique that guarantees a high fit between the predicted values and those measured during analysis of test results. It was especially important to check which method gives a better fit of the calculated result values in case they were relatively small and/or close to each other. This study developed models with the use of the response surface methodology (RSM) and artificial neural networks (ANNs). The aim of the study was comparison between two models (RSM and ANNs) and to check which model gives a better data fit for relatively similar values in individual tests. In all cases, the neural network models provided a better value fit. This is due to the fact that neural networks use better fitted functions than in the case of the RSM method using quadratic fitting. This comparison included the aspect ratio hole and the thickness side gap data, the values of which for individual tests were very similar. The paper reports an analysis of the impact of parameter variables on the analyzed factors. Higher values of current amplitude, pulse time length, and rotational speed of the working electrode resulted in higher drilling speed (above 15 µm/s, lower linear tool wear (below 15%), higher aspect ratio hole (above 26), lower hole conicity (below 0.005), and lower side gap thickness at the hole inlet (below 100 µm).

show abstract