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Dr. Alexander Hošovský
Faculty of Manufacturing Technologies Technical University of Kosice with a seat in Presov, Bayerova 1, 080 01 Presov, Slovakia

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Research Keywords & Expertise

0 Automatic Control
0 System Identification
0 soft robotics
0 soft actuators
0 Soft Computing Techniques

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Journal article
Published: 14 May 2021 in Applied Sciences
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This article describes the dynamics of a manipulator with two degrees of freedom, while the dynamic model of the manipulator’s arm is derived using Lagrangian formalism, which considers the difference between the kinetic and potential energy of the system. The compiled dynamic model was implemented in Matlab, taking into account the physical parameters of the manipulator and friction term. Physical parameters were exported from the 3D CAD model. A scheme (model) was compiled in the Simulink, which was used for the subsequent validation process. The outputs of the validations were compared with measured data of joint angles from the system (expected condition) obtained by using gravity tests. For obtaining better results were parameters of the model optimizing by using the Trust Region Algorithm for Nonlinear Least Squares optimization method. Therefore, the aim of the research described in the article is the comparison of the model with the parameters that come from CAD and its improvement by estimating the parameters based on gravitational measurements. The model with estimated parameters achieved an improvement in the results of the Normal Root Mean Square Error compared to the model with CAD parameters. For link 1 was an improvement from 28.49% to 67.93% depending on the initial joint angle, and for link 2, from 63.84% to 66.46%.

ACS Style

Monika Trojanová; Tomáš Čakurda; Alexander Hošovský; Tibor Krenický. Estimation of Grey-Box Dynamic Model of 2-DOF Pneumatic Actuator Robotic Arm Using Gravity Tests. Applied Sciences 2021, 11, 4490 .

AMA Style

Monika Trojanová, Tomáš Čakurda, Alexander Hošovský, Tibor Krenický. Estimation of Grey-Box Dynamic Model of 2-DOF Pneumatic Actuator Robotic Arm Using Gravity Tests. Applied Sciences. 2021; 11 (10):4490.

Chicago/Turabian Style

Monika Trojanová; Tomáš Čakurda; Alexander Hošovský; Tibor Krenický. 2021. "Estimation of Grey-Box Dynamic Model of 2-DOF Pneumatic Actuator Robotic Arm Using Gravity Tests." Applied Sciences 11, no. 10: 4490.

Journal article
Published: 08 May 2021 in Applied Sciences
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The assisted assembly of customized products supported by collaborative robots combined with mixed reality devices is the current trend in the Industry 4.0 concept. This article introduces an experimental work cell with the implementation of the assisted assembly process for customized cam switches as a case study. The research is aimed to design a methodology for this complex task with full digitalization and transformation data to digital twin models from all vision systems. Recognition of position and orientation of assembled parts during manual assembly are marked and checked by convolutional neural network (CNN) model. Training of CNN was based on a new approach using virtual training samples with single shot detection and instance segmentation. The trained CNN model was transferred to an embedded artificial processing unit with a high-resolution camera sensor. The embedded device redistributes data with parts detected position and orientation into mixed reality devices and collaborative robot. This approach to assisted assembly using mixed reality, collaborative robot, vision systems, and CNN models can significantly decrease assembly and training time in real production.

ACS Style

Kamil Židek; Ján Piteľ; Michal Balog; Alexander Hošovský; Vratislav Hladký; Peter Lazorík; Angelina Iakovets; Jakub Demčák. CNN Training Using 3D Virtual Models for Assisted Assembly with Mixed Reality and Collaborative Robots. Applied Sciences 2021, 11, 4269 .

AMA Style

Kamil Židek, Ján Piteľ, Michal Balog, Alexander Hošovský, Vratislav Hladký, Peter Lazorík, Angelina Iakovets, Jakub Demčák. CNN Training Using 3D Virtual Models for Assisted Assembly with Mixed Reality and Collaborative Robots. Applied Sciences. 2021; 11 (9):4269.

Chicago/Turabian Style

Kamil Židek; Ján Piteľ; Michal Balog; Alexander Hošovský; Vratislav Hladký; Peter Lazorík; Angelina Iakovets; Jakub Demčák. 2021. "CNN Training Using 3D Virtual Models for Assisted Assembly with Mixed Reality and Collaborative Robots." Applied Sciences 11, no. 9: 4269.

Journal article
Published: 02 November 2020 in Journal of Building Engineering
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Forecasting energy consumption in buildings is crucial for achieving effective energy management as well as reducing environmental impacts. With the availability of large amounts of relevant data through smart metering, gas consumption forecasting is becoming an integral part of smart building design so that these requirements are met. In this study, we investigate week-ahead forecasting of daily gas consumption in three types of buildings characterized by different gas consumption profiles during a five-year period. As gas consumption in buildings is highly correlated with the average outdoor temperature, regression models with additional residual modeling are used for forecasting. However, conventional regression models with autoregressive moving averages (ARMA) errors (regARMA) perform poorly when the temperature forecasts are inaccurate. To address this, a new forecasting model termed genetic-algorithm-optimized regression wavelet neural network (GA-optimized regWANN) is proposed. It uses the wavelet decomposition of the residuals of temperature regression time-series, which are modeled by multiple nonlinear autoregressive (NAR) models based on sigmoid neural networks. The appropriate delays in the regression vectors of the NAR models are selected using a binary GA. Compared with regARMA and seasonal regARMA, the GA-optimized regWANN model achieved in the three buildings a reduction of 22.6%, 17.7%, and 57% in the mean absolute error (MAE) values in ex post forecasting with recorded temperatures, and a 52.5%, 27%, and 43.6% reduction in the MAE values in ex ante forecasting with week-ahead forecasted temperatures, even under conditions of relatively significant errors in the forecasted temperature.

ACS Style

Alexander Hošovský; Ján Piteľ; Milan Adámek; Jana Mižáková; Kamil Židek. Comparative study of week-ahead forecasting of daily gas consumption in buildings using regression ARMA/SARMA and genetic-algorithm-optimized regression wavelet neural network models. Journal of Building Engineering 2020, 34, 101955 .

AMA Style

Alexander Hošovský, Ján Piteľ, Milan Adámek, Jana Mižáková, Kamil Židek. Comparative study of week-ahead forecasting of daily gas consumption in buildings using regression ARMA/SARMA and genetic-algorithm-optimized regression wavelet neural network models. Journal of Building Engineering. 2020; 34 ():101955.

Chicago/Turabian Style

Alexander Hošovský; Ján Piteľ; Milan Adámek; Jana Mižáková; Kamil Židek. 2020. "Comparative study of week-ahead forecasting of daily gas consumption in buildings using regression ARMA/SARMA and genetic-algorithm-optimized regression wavelet neural network models." Journal of Building Engineering 34, no. : 101955.

Journal article
Published: 01 May 2020 in Sustainability
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This article deals with the creation of a digital twin for an experimental assembly system based on a belt conveyor system and an automatized line for quality production check. The point of interest is a Bowden holder assembly from a 3D printer, which consists of a stepper motor, plastic components, and some fastener parts. The assembly was positioned in a fixture with ultra high frequency (UHF) tags and internet of things (IoT) devices for identification of status and position. The main task was parts identification and inspection, with the synchronization of all data to a digital twin model. The inspection system consisted of an industrial vision system for dimension, part presence, and errors check before and after assembly operation. A digital twin is realized as a 3D model, created in CAD design software (CDS) and imported to a Tecnomatix platform to simulate all processes. Data from the assembly system were collected by a programmable logic controller (PLC) system and were synchronized by an open platform communications (OPC) server to a digital twin model and a cloud platform (CP). Digital twins can visualize the real status of a manufacturing system as 3D simulation with real time actualization. Cloud platforms are used for data mining and knowledge representation in timeline graphs, with some alarms and automatized protocol generation. Virtual digital twins can be used for online optimization of an assembly process without the necessity to stop that is involved in a production line.

ACS Style

Kamil Židek; Ján Piteľ; Milan Adámek; Peter Lazorík; Alexander Hošovský. Digital Twin of Experimental Smart Manufacturing Assembly System for Industry 4.0 Concept. Sustainability 2020, 12, 3658 .

AMA Style

Kamil Židek, Ján Piteľ, Milan Adámek, Peter Lazorík, Alexander Hošovský. Digital Twin of Experimental Smart Manufacturing Assembly System for Industry 4.0 Concept. Sustainability. 2020; 12 (9):3658.

Chicago/Turabian Style

Kamil Židek; Ján Piteľ; Milan Adámek; Peter Lazorík; Alexander Hošovský. 2020. "Digital Twin of Experimental Smart Manufacturing Assembly System for Industry 4.0 Concept." Sustainability 12, no. 9: 3658.

Journal article
Published: 05 April 2019 in Symmetry
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Small series production with a high level of variability is not suitable for full automation. So, a manual assembly process must be used, which can be improved by cooperative robots and assisted by augmented reality devices. The assisted assembly process needs reliable object recognition implementation. Currently used technologies with markers do not work reliably with objects without distinctive texture, for example, screws, nuts, and washers (single colored parts). The methodology presented in the paper introduces a new approach to object detection using deep learning networks trained remotely by 3D virtual models. Remote web application generates training input datasets from virtual 3D models. This new approach was evaluated by two different neural network models (Faster RCNN Inception v2 with SSD, MobileNet V2 with SSD). The main advantage of this approach is the very fast preparation of the 2D sample training dataset from virtual 3D models. The whole process can run in Cloud. The experiments were conducted with standard parts (nuts, screws, washers) and the recognition precision achieved was comparable with training by real samples. The learned models were tested by two different embedded devices with an Android operating system: Virtual Reality (VR) glasses, Cardboard (Samsung S7), and Augmented Reality (AR) smart glasses (Epson Moverio M350). The recognition processing delays of the learned models running in embedded devices based on an ARM processor and standard x86 processing unit were also tested for performance comparison.

ACS Style

Kamil Židek; Peter Lazorík; Ján Piteľ; Alexander Hošovský. An Automated Training of Deep Learning Networks by 3D Virtual Models for Object Recognition. Symmetry 2019, 11, 496 .

AMA Style

Kamil Židek, Peter Lazorík, Ján Piteľ, Alexander Hošovský. An Automated Training of Deep Learning Networks by 3D Virtual Models for Object Recognition. Symmetry. 2019; 11 (4):496.

Chicago/Turabian Style

Kamil Židek; Peter Lazorík; Ján Piteľ; Alexander Hošovský. 2019. "An Automated Training of Deep Learning Networks by 3D Virtual Models for Object Recognition." Symmetry 11, no. 4: 496.

Journal article
Published: 12 December 2018 in MM Science Journal
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ACS Style

Alexander Hosovsky; Ján Piteľ; Jana Mizakova; Kamil Zidek. INTRODUCTORY ANALYSIS OF GAS CONSUMPTION TIME SERIES IN NON-RESIDENTIAL BUILDINGS FOR PREDICTION PURPOSES USING WAVELET DECOMPOSITION. MM Science Journal 2018, 12, 2648 -2655.

AMA Style

Alexander Hosovsky, Ján Piteľ, Jana Mizakova, Kamil Zidek. INTRODUCTORY ANALYSIS OF GAS CONSUMPTION TIME SERIES IN NON-RESIDENTIAL BUILDINGS FOR PREDICTION PURPOSES USING WAVELET DECOMPOSITION. MM Science Journal. 2018; 12 (2018):2648-2655.

Chicago/Turabian Style

Alexander Hosovsky; Ján Piteľ; Jana Mizakova; Kamil Zidek. 2018. "INTRODUCTORY ANALYSIS OF GAS CONSUMPTION TIME SERIES IN NON-RESIDENTIAL BUILDINGS FOR PREDICTION PURPOSES USING WAVELET DECOMPOSITION." MM Science Journal 12, no. 2018: 2648-2655.

Conference paper
Published: 15 September 2018 in Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020)
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The paper describes the experiments with the use of deep neural networks (CNN) for robust identification of assembly parts (screws, nuts) and assembly features (holes), to speed up any assembly process with augmented reality application. The simple image processing tasks with static camera and recognized parts can be handled by standard image processing algorithms (threshold, Hough line/circle detection and contour detection), but the augmented reality devices require dynamic recognition of features detected in various distances and angles. The problem can be solved by deep learning CNN which is robust to orientation, scale and in cases when element is not fully visible. We tested two pretrained CNN models Mobilenet V1 and SSD Fast RCNN Inception V2 SSD extension have been tested to detect exact position. The results obtained were very promising in comparison to standard image processing techniques.

ACS Style

Kamil Židek; Alexander Hosovsky; Jan Piteľ; Slavomír Bednár. Recognition of Assembly Parts by Convolutional Neural Networks. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) 2018, 281 -289.

AMA Style

Kamil Židek, Alexander Hosovsky, Jan Piteľ, Slavomír Bednár. Recognition of Assembly Parts by Convolutional Neural Networks. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020). 2018; ():281-289.

Chicago/Turabian Style

Kamil Židek; Alexander Hosovsky; Jan Piteľ; Slavomír Bednár. 2018. "Recognition of Assembly Parts by Convolutional Neural Networks." Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) , no. : 281-289.

Journal article
Published: 01 August 2018 in Applied Sciences
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The paper deals with the special filtration method using a filter with membership function. The paper presents a model of a filter, its specific characteristics and some parameters that have an impact on quality of filtration. A filter with different membership functions (Gauss, Bell, Power and Triangle) was designed and tested for specific demands, which followed from the experience with the realization of a biomass combustion control system. Data obtained from the combustion process were extremely noisy (influenced by various transfer errors, disturbances and external interferences) and, therefore, had to be properly filtered. The paper also describes some results of filter simulation in the Matlab Simulink environment and its implementation into an on-line monitored process control system of biomass combustion. It was proven by implementation that such a filter can be useful for the signal filtering of oxygen concentration and carbon monoxide emission sensing and it can be very useful in reducing signal interferences arising in biomass combustion.

ACS Style

Jana Mižáková; Ján Piteľ; Alexander Hošovský; Martin Kolarčík; Madhawa Ratnayake. Using Special Filter with Membership Function in Biomass Combustion Process Control. Applied Sciences 2018, 8, 1279 .

AMA Style

Jana Mižáková, Ján Piteľ, Alexander Hošovský, Martin Kolarčík, Madhawa Ratnayake. Using Special Filter with Membership Function in Biomass Combustion Process Control. Applied Sciences. 2018; 8 (8):1279.

Chicago/Turabian Style

Jana Mižáková; Ján Piteľ; Alexander Hošovský; Martin Kolarčík; Madhawa Ratnayake. 2018. "Using Special Filter with Membership Function in Biomass Combustion Process Control." Applied Sciences 8, no. 8: 1279.

Journal article
Published: 07 March 2018 in MM Science Journal
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ACS Style

Kamil Zidek; Vladimir Vasek; Jan Pitel; Alexander Hošovský. AUXILIARY DEVICE FOR ACCURATE MEASUREMENT BY THE SMART VISION SYSTEM. MM Science Journal 2018, 2018, 2136 -2139.

AMA Style

Kamil Zidek, Vladimir Vasek, Jan Pitel, Alexander Hošovský. AUXILIARY DEVICE FOR ACCURATE MEASUREMENT BY THE SMART VISION SYSTEM. MM Science Journal. 2018; 2018 (1):2136-2139.

Chicago/Turabian Style

Kamil Zidek; Vladimir Vasek; Jan Pitel; Alexander Hošovský. 2018. "AUXILIARY DEVICE FOR ACCURATE MEASUREMENT BY THE SMART VISION SYSTEM." MM Science Journal 2018, no. 1: 2136-2139.

Journal article
Published: 07 March 2018 in MM Science Journal
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ACS Style

Alexander Hošovský; Sergej Hloch; Jozef Jurko; Anton Panda; Monika Trojanova. PRELIMINARY INVESTIGATION OF STATIC AND DYNAMIC HYSTERESIS OF DMSP-5 FLUIDIC MUSCLE. MM Science Journal 2018, 2018, 2172 -2178.

AMA Style

Alexander Hošovský, Sergej Hloch, Jozef Jurko, Anton Panda, Monika Trojanova. PRELIMINARY INVESTIGATION OF STATIC AND DYNAMIC HYSTERESIS OF DMSP-5 FLUIDIC MUSCLE. MM Science Journal. 2018; 2018 (1):2172-2178.

Chicago/Turabian Style

Alexander Hošovský; Sergej Hloch; Jozef Jurko; Anton Panda; Monika Trojanova. 2018. "PRELIMINARY INVESTIGATION OF STATIC AND DYNAMIC HYSTERESIS OF DMSP-5 FLUIDIC MUSCLE." MM Science Journal 2018, no. 1: 2172-2178.

Conference paper
Published: 01 January 2018 in Proceedings of the 3rd EAI International Conference on Management of Manufacturing Systems
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ACS Style

Kamil Zidek; Dagmar Janacova; Alexander Hosovsky; Jan Pitel; Peter Lazorik. Data optimization for communication between wireless IoT devices and Cloud platforms in production process. Proceedings of the 3rd EAI International Conference on Management of Manufacturing Systems 2018, 1 .

AMA Style

Kamil Zidek, Dagmar Janacova, Alexander Hosovsky, Jan Pitel, Peter Lazorik. Data optimization for communication between wireless IoT devices and Cloud platforms in production process. Proceedings of the 3rd EAI International Conference on Management of Manufacturing Systems. 2018; ():1.

Chicago/Turabian Style

Kamil Zidek; Dagmar Janacova; Alexander Hosovsky; Jan Pitel; Peter Lazorik. 2018. "Data optimization for communication between wireless IoT devices and Cloud platforms in production process." Proceedings of the 3rd EAI International Conference on Management of Manufacturing Systems , no. : 1.

Journal article
Published: 01 December 2017 in Transactions of the Canadian Society for Mechanical Engineering
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A lesser known type of pneumatic actuators is pneumatic artificial muscle (PAM) although these pneumatic actuators play an important role in industrial, medical and other applications. In this study a PAM model based on the assumption Euler’s law is developed, some static force models (geometric model-based static force model, static force model using maximum force of PAM and static force model using a polynomial function) are compared to Sárosi’s force model and two dynamic models based on Sárosi’s static force model and Hill’s muscle model are presented.

ACS Style

József Sárosi; Ján Piteľ; Mária Tóthová; Alexander Hošovský; István Bíró. COMPARATIVE SURVEY OF VARIOUS STATIC AND DYNAMIC MODELS OF PNEUMATIC ARTIFICIAL MUSCLES. Transactions of the Canadian Society for Mechanical Engineering 2017, 41, 825 -844.

AMA Style

József Sárosi, Ján Piteľ, Mária Tóthová, Alexander Hošovský, István Bíró. COMPARATIVE SURVEY OF VARIOUS STATIC AND DYNAMIC MODELS OF PNEUMATIC ARTIFICIAL MUSCLES. Transactions of the Canadian Society for Mechanical Engineering. 2017; 41 (5):825-844.

Chicago/Turabian Style

József Sárosi; Ján Piteľ; Mária Tóthová; Alexander Hošovský; István Bíró. 2017. "COMPARATIVE SURVEY OF VARIOUS STATIC AND DYNAMIC MODELS OF PNEUMATIC ARTIFICIAL MUSCLES." Transactions of the Canadian Society for Mechanical Engineering 41, no. 5: 825-844.

Journal article
Published: 07 September 2016 in MM Science Journal
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ACS Style

Alexander Hosovsky; Jan Pitel; Kamil Zidek. ANALYSIS OF HYSTERETIC BEHAVIOR OF TWO-DOF SOFT ROBOTIC ARM. MM Science Journal 2016, 2016, 935 -941.

AMA Style

Alexander Hosovsky, Jan Pitel, Kamil Zidek. ANALYSIS OF HYSTERETIC BEHAVIOR OF TWO-DOF SOFT ROBOTIC ARM. MM Science Journal. 2016; 2016 (3):935-941.

Chicago/Turabian Style

Alexander Hosovsky; Jan Pitel; Kamil Zidek. 2016. "ANALYSIS OF HYSTERETIC BEHAVIOR OF TWO-DOF SOFT ROBOTIC ARM." MM Science Journal 2016, no. 3: 935-941.

Journal article
Published: 07 September 2016 in MM Science Journal
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ACS Style

Kamil Zidek; Jan Pitel; Alexander Hosovsky. DESIGN OF ADJUSTABLE SMART VISION SYSTEM BASEDON ARTIFICIAL MUSCLE ACTUATORS. MM Science Journal 2016, 2016, 947 -951.

AMA Style

Kamil Zidek, Jan Pitel, Alexander Hosovsky. DESIGN OF ADJUSTABLE SMART VISION SYSTEM BASEDON ARTIFICIAL MUSCLE ACTUATORS. MM Science Journal. 2016; 2016 (3):947-951.

Chicago/Turabian Style

Kamil Zidek; Jan Pitel; Alexander Hosovsky. 2016. "DESIGN OF ADJUSTABLE SMART VISION SYSTEM BASEDON ARTIFICIAL MUSCLE ACTUATORS." MM Science Journal 2016, no. 3: 947-951.

Journal article
Published: 01 September 2016 in Mechanism and Machine Theory
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Pneumatic artificial muscles (PAMs) belong to the group of nonconventional actuators with remarkable force/weight ratio that can be used for the construction of soft mechanisms safe in contact with humans. In order to be able to design an effective control of 2-link soft robot arm actuated with PAMs, a dynamic model of this system needs to be derived. We use a PAM dynamic model derived using first principles modeling (for contraction, pressure, and air flow dynamics) and ANFIS-based approximation based on the experimental data for the muscle force function. To derive the dynamics of the robot arm, we use Lagrangian mechanics approach for planar arm with the inertial and mass data based on the 3D CAD model. To validate the complete dynamic model of the soft robot arm, we used a gravity test (without PAM actuation) and pulse excitation for PAM control. The results confirm good validity of the dynamic model for all relevant variables (joint angles, muscle contractions, and pressures) as well as the dynamic coupling between the joints.

ACS Style

A. Hošovský; J. Piteľ; K. Židek; M. Tóthová; J. Sárosi; L. Cveticanin. Dynamic characterization and simulation of two-link soft robot arm with pneumatic muscles. Mechanism and Machine Theory 2016, 103, 98 -116.

AMA Style

A. Hošovský, J. Piteľ, K. Židek, M. Tóthová, J. Sárosi, L. Cveticanin. Dynamic characterization and simulation of two-link soft robot arm with pneumatic muscles. Mechanism and Machine Theory. 2016; 103 ():98-116.

Chicago/Turabian Style

A. Hošovský; J. Piteľ; K. Židek; M. Tóthová; J. Sárosi; L. Cveticanin. 2016. "Dynamic characterization and simulation of two-link soft robot arm with pneumatic muscles." Mechanism and Machine Theory 103, no. : 98-116.

Review
Published: 01 January 2016 in Procedia Engineering
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Abrasive water jet has been used for more than thirty years. It quickly became one of the core non-conventional technologies for cutting operations of various materials, ranging from soft and easy to cut materials, through ductile metal materials to brittle, hard to cut ceramics and metals. Abrasive water suspension jet (AWSJ) did not gain much popularity in machining industry in the beginning as opposed to abrasive water injection jet, but has found niche applications where its advantages were put to use. In this study a review of recent development in the eld of AWSJ is presented. Micro-machining, as a potential application for AWSJ, is discussed at the beginning, followed by several advances in the AWSJ technology. At the end, typical applications for AWSJ as decommissioning and dismantling of structures or rock drilling are presented.

ACS Style

Matúš Molitoris; Ján Piteľ; Alexander Hošovský; Mária Tóthová; Kamil Židek. A Review of Research on Water Jet with Slurry Injection. Procedia Engineering 2016, 149, 333 -339.

AMA Style

Matúš Molitoris, Ján Piteľ, Alexander Hošovský, Mária Tóthová, Kamil Židek. A Review of Research on Water Jet with Slurry Injection. Procedia Engineering. 2016; 149 ():333-339.

Chicago/Turabian Style

Matúš Molitoris; Ján Piteľ; Alexander Hošovský; Mária Tóthová; Kamil Židek. 2016. "A Review of Research on Water Jet with Slurry Injection." Procedia Engineering 149, no. : 333-339.

Journal article
Published: 01 November 2013 in Applied Mechanics and Materials
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Pneumatic artificial muscles belong to a category of nonconventional pneumatic actuators that are distinctive for their high power/weight ratio, simple construction and low price and maintenance costs. As such, pneumatic artificial muscles represent an alternative type of pneumatic actuator that could replace the traditional ones in certain applications. Due to their specific construction, PAM-based systems have nonlinear characteristics which make it more difficult to design a control system with good performance. In the paper, a gray-box model (basically analytical but with certain experimental parts) of the one degree-of-freedom PAM-based actuator is derived. This model interconnects the description of pneumatic and mechanical part of the system through a set of several nonlinear differential equations and its main purpose is the design of intelligent control system in simulation environment. The model is validated in both open-loop and closed-loop mode using the measurements on real plant and the results confirm that model performance is in good agreement with the performance of real actuator.

ACS Style

Alexander Hošovský; Kamil Zidek. Experimental Validation of Nominal Model Characteristics for Pneumatic Muscle Actuator. Applied Mechanics and Materials 2013, 460, 1 -12.

AMA Style

Alexander Hošovský, Kamil Zidek. Experimental Validation of Nominal Model Characteristics for Pneumatic Muscle Actuator. Applied Mechanics and Materials. 2013; 460 ():1-12.

Chicago/Turabian Style

Alexander Hošovský; Kamil Zidek. 2013. "Experimental Validation of Nominal Model Characteristics for Pneumatic Muscle Actuator." Applied Mechanics and Materials 460, no. : 1-12.

Journal article
Published: 01 January 2013 in Advances in Mechanical Engineering
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The paper describes methods for biomass combustion process control and burning stabilization based on low-cost sensing of carbon monoxide emissions and oxygen concentration in the flue gas. The designed control system was tested on medium-scale biomass-fired boilers and some results are evaluated and presented in the paper.

ACS Style

Ján Piteľ; Jana Mižáková; Alexander Hošovský. Biomass Combustion Control and Stabilization Using Low-Cost Sensors. Advances in Mechanical Engineering 2013, 5, 1 .

AMA Style

Ján Piteľ, Jana Mižáková, Alexander Hošovský. Biomass Combustion Control and Stabilization Using Low-Cost Sensors. Advances in Mechanical Engineering. 2013; 5 ():1.

Chicago/Turabian Style

Ján Piteľ; Jana Mižáková; Alexander Hošovský. 2013. "Biomass Combustion Control and Stabilization Using Low-Cost Sensors." Advances in Mechanical Engineering 5, no. : 1.