Volumen 13 (2019): Heft 3 (September 2019)

The unique properties of magnetic fluids result from their ability to undergo reversible, almost immediate, changes in their rheological properties under the influence of magnetic fields as well as the possibility to position them by magnetic field forces. It is also possible to control the direction and flow rate of such fluids. These properties provide an efficient way to develop new types of controllable machines and devices, such as brakes, clutches and bearings. The objective of the study was to examine the axial force and torque friction of a magnetorheological (MR) fluid working in the shear flow mode (parallel plate system) subjected to different magnetic induction ramp profiles. The rotation speed and working gap height were also taken into account. Determining the response of the tested system to magnetic induction change in different working conditions was of particular interest.

In the recent paper, non-linear methods of data analysis were used to study bubble departure synchronisation. In the experiment, bubbles were generated in engine oils from two neighbouring brass nozzles (with an inner diameter of 1 mm). During the experiment, the time series of air pressure oscillations in the air supply system and voltage changes on phototransistor were recorded. The analysis of bubble departure synchronisation was performed using a correlation coefficient. The following methods of non-linear data analysis are considered. Fast Fourier Transformation, autocorrelation, attractor reconstruction, correlation dimension, largest Lyapunov exponent and recurrence plot analysis were used to examine the correlation between bubbles behaviour and character of pressure fluctuations. Non-linear analysis of bubble departure synchronisation revealed that the way of bubble departures from two neighbouring nozzles does not depend simply on the character of pressure fluctuations in the nozzle air supply systems. The chaotic changes of the air pressure oscillations do not always determine the chaotic bubble departures.

In this paper, an optimal fuzzy controller based on the Teaching-Learning-Based Optimization (TLBO) algorithm has been presented for the stabilization of a two-link planar horizontal under-actuated manipulator with two revolute (2R) joints. For the considered fuzzy control method, a singleton fuzzifier, a centre average defuzzifier and a product inference engine have been used. The TLBO algorithm has been implemented for searching the optimum parameters of the fuzzy controller with consideration of time integral of the absolute error of the state variables as the objective function. The proposed control method has been utilized for the 2R under-actuated manipulator with the second passive joint wherein the model moves in the horizontal plane and friction forces have been considered. Simulation results of the offered control method have been illustrated for the stabilization of the considered robot system. Moreover, for different initial conditions, the effectiveness and the robustness of the mentioned strategy have been challenged.

The study of flow around obstacles is devised into three different positions: above the obstacle, upstream of the obstacle, and downstream of the latter. The behaviour of the fluid downstream of the obstacle is less known, and the physical and numerical modelling is being given the existence of recirculation zones with their complex behaviour. The purpose of the work presented below is to study the influence of the inclined form of the two upper peaks of a rectangular cube. A three-dimensional study was carried out using the ANSYS CFX calculation code. Turbulence models have been used to study the flow characteristics around the inclined obstacle. The time-averaged results of contours of velocity vectors <V>, cross-stream <v> and stream wise velocity <u> and streamlines were obtained by using K-ω shear -stress transport (SST), RANG K-ε and K-ε to model the turbulence, and the governing equations were solved using the finite volume method. The turbulence model K-ω SST has presented the best prediction of the flow characteristics for the obstacle among the investigated turbulence models in this work.

This paper presents the control designs for an autonomous forklift vehicle that drive the vehicle from an initial configuration to a final one. Three stabilization controls, which are chained-form time-varying control, sigma-transformed discontinuous control, and navigation-variables-based discontinuous control, for a forklift vehicle are compared by simulations. The sigma-transformed and navigation-variables-based discontinuous controls provide fast convergence motions from an initial to a final configuration, while the time-varying-based control provides oscillatory motion and slow convergence. The sigma-transformed discontinuous control has a set of discontinuous points in which, from a practical point of view, the control signals can blow up if a vehicle enters the set. The navigation-variables-based control, which also has a discontinuous point at the final configuration, does not produce blown up control signals since its boundedness nature. Discussion on the implementation of control algorithm is elucidated for the three stabilization controls for the forklift vehicle.

Disc brakes in passenger cars are extremely important due to safety concerns. Their operational quality largely rests on the conditions of contact between the working elements, which mainly consists offlat and dry sliding. The tribological phenomena thatoccur during braking are, unfortunately, extremely complex and difficult to recreate in laboratory settings. Many scientific institutes conduct research to improve our understanding of these phenomena. The results they present make it possible to continuously simplify the procedures for selecting friction materials and reducing the costs of identifying the properties of new products. This article analyses the methods commonly used by researchers. It also presents different set-ups of research stations, as well as the advantages and drawbacks of each method.

Stroke is the third most common cause of death and the most common cause of long-term disability among adults around theworld. Therefore, stroke prediction and diagnosis is a very important issue. Data mining techniques come in handy to help determine the correlations between individual patient characterisation data, that is, extract from the medical information system the knowledge necessary to predict and treat various diseases. The study analysed the data of patients with stroke using eight known classification algorithms (J48 (C4.5), CART, PART, naive Bayes classifier, Random Forest, Supporting Vector Machine and neural networks Multilayer Perceptron), which allowed to build an exploration model given with an accuracy of over 88%. The potential features of patients, which may be factors that increase the risk of stroke, were also indicated.

This article deals with the model of the locally heterogeneous elastic body. The model accounts for long-range interaction and describes near-surface non-homogeneity and related size effects. The key systems of model equations are presented. From the viewpoint of the representative volume element, the boundary condition for density and the limits of applicability of the model are discussed. The difference of mass density in the near-surface body region from the reference value (near-surface mass defect) causes a non-zero stressed state. It is indicated on the strong dependence of the surface value of density from the curvature of the surface of thin fibres. The effect of the near-surface mass defect on the stressed state and the size effect of surface stresses have been investigated on an example of a hollow cylinder. Size effect of its strength has been studied as well.

In the ever increasing number of robotic system applications in the industry, the robust and fast visual recognition and pose estimation of workpieces are of utmost importance. One of the ubiquitous tasks in industrial settings is the pick-and-place task where the object recognition is often important. In this paper, we present a new implementation of a work-piece sorting system using a template matching method for recognizing and estimating the position of planar workpieces with sparse visual features. The proposed framework is able to distinguish between the types of objects presented by the user and control a serial manipulator equipped with parallel finger gripper to grasp and sort them automatically. The system is furthermore enhanced with a feature that optimizes the visual processing time by automatically adjusting the template scales. We test the proposed system in a real-world setup equipped with a UR5 manipulator and provide experimental results documenting the performance of our approach.