Applied sciences

Bulletin of the Polish Academy of Sciences Technical Sciences

Description

The Bulletin of the Polish Academy of Sciences Technical Sciences is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred:

Artificial and Computational Intelligence,
Biomedical Engineering and Biotechnology,
Civil Engineering,
Control, Informatics and Robotics,

Electronics, Telecommunication and Optoelectronics,
Mechanical and Aeronautical Engineering, Thermodynamics,
Material Science and Nanotechnology,
Power Systems and Power Electronics.

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Journal Metrics:

JCR Impact Factor 2023:	1.2
5 Year Impact Factor 2022:	1.1
CiteScore 2023:	2.8
SCImago Journal Rank (SJR) 2023:	0.282
Source Normalized Impact per Paper (SNIP) 2023:	0.573
Ministry of Education and Science:	100 points

Abbreviated title: Bull. Pol. Acad. Sci. Tech. Sci.

ISSN

ISSN 2300-1917

Editorial Board 2023-2025

Editor-in-Chief:

A. Rogalski, Military University of Technology

Honorary (Past) Editor-in Chief:

T. Kaczorek, Warsaw University of Technology

M.P. Kaźmierkowski, Warsaw University of Technology

Deputy Editor-in-Chief:

B. Błachowski, Institute of Fundamental Technological Research PAN

M. Mrozowski, Gdansk University of Technology

Board of Topical Co-editors:

Artificial and Computational Intelligence

S. Osowski, B. Sawicki and T. Leś, Warsaw University of Technology

Biomedical Engineering and Biotechnology

D. Pijanowska, Institute of Biocybernetics and Biomedical Engineering PAN

Civil Engineering

L. Czarnecki, Building Research Institute, ITB, Warsaw

Ł. Sadowski, Wroclaw University of Science and Technology

Control, Robotics and Informatics

J. Klamka and A. Babiarz, Silesian Technical University

J. Stefanowski, Poznan University of Technology

Electronics, Telecommunication and Optoelectronics

M. Mrozowski and A. Lamęcki, Gdansk University of Technology

Mechanical and Aeronautical Engineering, Thermodynamics

B. Błachowski, Institute of Fundamental Technological Research PAN

G. Zboiński, Institute of Fluid-Flow Machinery PAN and University of Warmia and Mazury in Olsztyn

Materials Science and Nanotechnology

B. Major and P. Czaja, Institute of Metallurgy and Materials Science PAN

Power Systems and Power Electronics

J. Rąbkowski and M. Jasiński, Warsaw University of Technology

International Editorial Advisory Board

R. Asthana, University of Wisconsin-Stout, Menomonie, USA

Xu Binshi, China Association of Plant Engineering, Beijing, P.R. China

F. Blaabjerg, Aalborg University, Denmark

C. Cecati, University of L’Aquila, Italy

A. Cichocki, RIKEN Institute, Tokyo, Japan

M. David, National Polytechnique de Toulouse, France

R. Ebner, Materials Centre Leoben, Leoben, Austria

E. Fornasini, University of Padova, Padova, Italy

L.G. Franquelo, University of Sevilla, Spain

M. Gad-el-Hak, Virginia Commonwealth University, Richmond, USA

M. Giersig, Free University of Berlin, Germany

D. van Gemert, Catholic University Leuven, KU Leuven, Belgium

L. Keviczky, Hungarian Academy of Sciences, Budapest, Hungary

V. Kučera, Czech Technical University in Prague, Prague, Czech Republic

R. Kennel, Technical University Munich, Germany

T.A. Kowalewski, Institute of Fundamental Technological Research PAN

E. Levi, Liverpool John Moore University, UK

G. Maier, Technical University of Milan, Milan, Italy

K.F. Man, City University of Hong Kong,

R. Maniewski, Institute of Biocybernetics and Biomedical Engineering PAN

H.A. Mang, Austrian Academy of Sciences, Vienna, Austria

H. Mihashi, Tohoku University, Aoba-ku, Sendai, Japan

S. Mindess, University of British Columbia, Vancouver, Canada

D.A. Mlynski, University of Karlsruhe, Karlsruhe, Germany

A.S. Nowak, University of Michigan, Ann Arbor, USA

K. Ohnishi, Keio University, Yokohama, Japan

A. Öberg, Linköping University, Linköping, Sweden

W. Pedrycz, University of Alberta, Canada

M. Razeghi, Northwestern University, Evanston, USA

J. Rodriguez, University of Andres Bello, Santiago, Chile

J.V. Sloten, Catholic University Leuven, Leuven, Belgium

B.M. Wilamowski, University of Auburn, Alabama, USA

A.L. Yarin, University of Illinois at Chicago, USA

Du Xiangwan, Chinese Academy of Engineering, China

J. Żurada, Department of Computer Engineering, University of Louisville, USA

Editorial Office:

Pałac Kultury i Nauki

Wydział IV Nauk Technicznych PAN

Pl. Defilad 1

PL 00-901 Warszawa

Managing Editor:

Renata Podraza, e-mail: Renata.Podraza@pan.pl

Finance:

Katarzyna Łasak, e-mail: Katarzyna.Lasak@pan.pl

The Bulletin of the Polish Academy of Sciences Technical Sciences is an open access journal with all content available with no charge in full text version.

The journal content is available under the licencse CC BY 4.0 https://creativecommons.org/licenses/by/4.0/.

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Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1

1 Contents vol. 72 no. 1 - Special Section

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1

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2 Contents vol. 72 no. 1 - Regular Papers

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1

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3 On IIoT and AI-based optimization

Dariusz Mikołajewski , Jacek M. Czerniak , Maciej Piechowiak , Katarzyna Węgrzyn-Wolska , Janusz Kacprzyk

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e149174 | DOI: 10.24425/bpasts.2024.149174

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Authors and Affiliations

Dariusz Mikołajewski

e-mail:

ORCID:

Jacek M. Czerniak

e-mail:

ORCID:

Maciej Piechowiak

e-mail:

ORCID:

Katarzyna Węgrzyn-Wolska

e-mail:

ORCID:

Janusz Kacprzyk

e-mail:

ORCID:

Kazimierz Wielki University, Bydgoszcz, Poland
EFREI Panthéon-Assas University Paris II, France
Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

4 The Internet of Things and AI-based optimization within the Industry 4.0 paradigm

Dariusz Mikołajewski , Jacek M. Czerniak , Maciej Piechowiak , Katarzyna Węgrzyn-Wolska , Janusz Kacprzyk

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e147346 | DOI: 10.24425/bpasts.2023.147346

Keywords: Industry 4.0 Internet of Things machine learning cyber-physical system industrial Internet of Things

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Abstract

By reviewing the current state of the art, this paper opens a Special Section titled “The Internet of Things and AI-driven optimization in the Industry 4.0 paradigm”. The topics of this section are part of the broader issues of integration of IoT devices, cloud computing, big data analytics, and artificial intelligence to optimize industrial processes and increase efficiency. It also focuses on how to use modern methods (i.e. computerization, robotization, automation, machine learning, new business models, etc.) to integrate the entire manufacturing industry around current and future economic and social goals. The article presents the state of knowledge on the use of the Internet of Things and optimization based on artificial intelligence within the Industry 4.0 paradigm. The authors review the previous and current state of knowledge in this field and describe known opportunities, limitations, directions for further research, and industrial applications of the most promising ideas and technologies, considering technological, economic, and social opportunities.

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Authors and Affiliations

Dariusz Mikołajewski

e-mail:

ORCID:

Jacek M. Czerniak

e-mail:

ORCID:

Maciej Piechowiak

e-mail:

ORCID:

Katarzyna Węgrzyn-Wolska

e-mail:

ORCID:

Janusz Kacprzyk

e-mail:

ORCID:

Faculty of Computer Science, Kazimierz Wielki University, Bydgoszcz, Poland
EFREI Paris Pantheon Assas University, Paris, France
Systems Research Institute, Polish Academy of Science, Warsaw, Poland

5 A decentralized radio network for small groups of unmanned aerial vehicles

Patryk Szywalski , Andrzej Waindok

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e147922 | DOI: 10.24425/bpasts.2023.147922

Keywords: decentralized communication unmanned aerial vehicles (UAVs) unmanned aerial system (UAS)

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Abstract

The investigation of a decentralized radio network dedicated to unmanned aerial systems (UASs) was presented in the paper. Two frequencies (315 MHz; 434 MHz) and five different configurations of Gaussian frequency-shift keying (GFSK) were taken into account. Three different algorithms for decentralized networks were investigated and their influence on the network capacity was measured. The research was done both for static and dynamically changed unmanned aerial vehicle (UAV) positions. In order to quantify the research three different parameters were determined: RSSI, nP (number of data packets in one second), and f (frequency of data update).

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Authors and Affiliations

Patryk Szywalski

Andrzej Waindok

e-mail:

ORCID:

Faculty of Electrical Engineering, Automatic Control and Informatics, Department of Electrical Engineering and Mechatronics,Opole University of Technology, Opole, Poland

6 An off-line application that determines the maximum accuracy of the realization of reference points from G-code for given parameters of CNC machine dynamics

Bogdan Kwiatkowski , Tadeusz Kwater , Damian Mazur , Jacek Bartman

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e147345 | DOI: 10.24425/bpasts.2023.147345

Keywords: JERK reference points CNC machine feed

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Abstract

The paper presents an off-line application that determines the maximum accuracy of the reference points for the given dynamics parameters of a CNC machine. These parameters are maximum speed, acceleration, and JERK. The JERK parameter determines the rate of change of acceleration. These parameters are defined for each working axis of the machine. The main achievement of the algorithm proposed in the article is the determination of the smallest error specified for each reference point resulting from the implemented G-code for the considered dynamic parameters of the CNC machine. The solutions to this problem in industry consider the improvement in the accuracy of hitting the reference points, but they do not provide information on whether the obtained solution is optimal for such parameters of the machine dynamics. The algorithm makes the accuracy dependent on the adopted dynamic parameters of the machine and the parameters of the PLC controller used in the CNC machine.

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Authors and Affiliations

Bogdan Kwiatkowski

e-mail: b.kwiatkowsk@prz.edu.pl

ORCID:

Tadeusz Kwater

e-mail:

ORCID:

Damian Mazur

e-mail: mazur@prz.edu.pl

ORCID:

Jacek Bartman

e-mail:

ORCID:

Department of Electrical and Computer Engineering Fundamentals, Rzeszow University of Technology, ul. W. Pola 2, 35-959 Rzeszow, Poland
Institute of Technical Engineering, State University of Technology and Economics in Jaroslaw, ul. Czarnieckiego 16, 37-500 Jaroslaw, Poland
University of Rzeszow, ul. Rejtana 16C, Rzeszow, Poland

7 Wood-based composite materials in the aspect of structural new generation materials. Recognition research

Anna Czajkowska , Tomasz Rydzkowski , Dorota Laskowska

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e146618 | DOI: 10.24425/bpasts.2023.146618

Keywords: composite material wind turbine wind turbine recycling plastics wood-based composites epoxy resin polyester resin

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Abstract

Composite materials are a constantly evolving group of engineering materials, which has significantly changed their current, and potential role as structural materials over the past decades. Composites offer greater strength, stiffness, and less deformation to structural designers than previously available engineering materials. Resin matrix composites are widely used in the transportation, marine, aerospace, energy, and even sports industries. The manufacturing stage has a profound influence on the quality of the final product. This paper presents the production of composite materials by gravity casting in silicone moulds, using an epoxy/polyester resin matrix reinforced with wood chips and shredded glass fiber reinforced composite from recycled wind turbine blades. Some of the fabricated samples were degassed in a reduced-pressure chamber. The mechanical properties of the produced material were then examined. It was noted that the silicone moulds did not affect the resin self-degassing due to the large surface area to weight ratio, and the remaining small air bubbles had a limited effect on the mechanical properties of the samples. The filler used also played a significant role. Composites filled with crushed GFRC showed better strength properties than composites filled with wood chips. The conducted research is aimed at selecting materials for further testing with a view to their use in the manufacture of next-generation wood-based composite structural materials.

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Authors and Affiliations

Anna Czajkowska

e-mail:

ORCID:

Tomasz Rydzkowski

e-mail:

ORCID:

Dorota Laskowska

e-mail:

ORCID:

Koszalin University of Technology, Faculty of Mechanical Engineering, Racławicka 15-17 street, 75-620 Koszalin, Poland

8 Multifunctional clustering based on the LEACH algorithm for edge-cloud continuum ecosystem

A. Paszkiewicz , C. Ćwikła , M. Bolanowski , M. Ganzha , M. Paprzycki , M. Hodoň

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e147919 | DOI: 10.24425/bpasts.2023.147919

Keywords: LEACH IoT cluster sensors phase transition

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Abstract

This paper introduces a novel approach to building network cluster structures, based on the modified LEACH algorithm. The proposed solution takes into account the multitasking of the network infrastructure, resulting from various functions performed by individual nodes. Therefore, instead of a single head, dedicated to a given cluster, a set of heads is selected, the number of which corresponds to the number of performed functions. Outcomes of simulations, comparing the classical and the multifunctional approach, are presented. The obtained results confirm that both algorithms deliver similar levels of energy consumption, as well as efficiency in terms of the number of individual nodes discharged.

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Authors and Affiliations

A. Paszkiewicz

e-mail:

ORCID:

C. Ćwikła

M. Bolanowski

e-mail:

ORCID:

M. Ganzha

e-mail:

ORCID:

M. Paprzycki

e-mail:

ORCID:

M. Hodoň

e-mail:

ORCID:

Department of Complex Systems, Rzeszow University of Technology, Al. Powstańców Warszawy 12, Rzeszów 35-959, Poland
Rzeszow University of Technology, Al. Powstańców Warszawy 12, Rzeszów 35-959, Poland
Systems Research Institute Polish Academy of Sciences, Newelska 6, Warszawa 01-447, Poland
Department of Technical Cybernetics, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia

9 Three methods of selecting a smart meter for data concentration in the automatic meter reading last mile network

Piotr Kiedrowski

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e146476 | DOI: 10.24425/bpasts.2023.146476

Keywords: Smart Meter AMR last mile network network optimization Industrial IoT

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Abstract

This paper proposes three methods of the optimal smart meter selection for acting as a data concentrator in the automatic meter reading last mile network. The study explains the reasons why the selected smart meter should also act as a data concentrator, in addition to its basic role. To select the smart meter, either the reliability of communication or the speed of the automatic meter reading process was considered. Graph theory is employed to analyse the last mile network, described as sets of nodes and unreliable links. The frame error ratio was used to assess the unreliability whilst the number of hops was used to describe the speed of the reading process. The input data for the analysis are qualitative parameters determined based on observations in the real, operated last mile networks as well as their typical topological arrangements. The results of the research can be useful in the last mile network migration process, which uses concentrators to the networks without them, or during the process of newer last mile network implementation, where data concentrators are no longer applicable. The efficiency of the proposed methods is assessed measurably.

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Authors and Affiliations

Piotr Kiedrowski

e-mail:

ORCID:

Institute of Telecommunications and Computer Science, Bydgoszcz University of Science and Technology,Al. Prof. S. Kaliskiego 7, 85-796 Bydgoszcz, Poland

10 Comparative study of experimental thermographic data and finite element analysis on temperature evolution of PET-G layer deposition during additive manufacturing process

Łukasz Kowalski , Michał Bembenek , Andrzej Uhryński , Szymon Bajda

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e147926 | DOI: 10.24425/bpasts.2023.147926

Keywords: FDM 3D printing thermography FEA

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Abstract

Additive manufacturing (AM) technologies have been gaining popularity in recent years due to patent releases – and in effect – better accessibility of the technology. One of the most popular AM technologies is fused deposition modeling (FDM), which is used to manufacture products out of thermoplastic polymers in a layer-by-layer manner. Due to the specificity of the method, parts manufactured in this manner tend to have non-isotropic properties. One of the factors influencing the part’s mechanical behavior and quality is the thermoplastic material’s bonding mechanism correlated with the processing temperature, as well as thermal shrinkage during processing. In this research, the authors verified the suitability of finite element method (FEM) analysis for determining PET-G thermal evolution during the process, by creating a layer transient heat transfer model, and comparing the obtained modelling results with ones registered during a real-time process recorded with a FLIR T1020 thermal imaging camera. Our model is a valuable resource for providing thermal conditions in existing numerical models that connect heat transfer, mesostructure and AM product strength, especially when experimental data is lacking. The FE model presented reached a maximum sample-specific error of 11.3%, while the arithmetic mean percentage error for all samples and layer heights is equal to 4.3%, which the authors consider satisfactory. Model-to-experiment error is partially caused by glass transition of the material, which can be observed on the experimental cooling rate curve after processing the temperature signal.

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Authors and Affiliations

Łukasz Kowalski

e-mail:

ORCID:

Michał Bembenek

e-mail:

ORCID:

Andrzej Uhryński

e-mail:

ORCID:

Szymon Bajda

e-mail:

ORCID:

Department of Manufacturing Systems, Faculty of Mechanical Engineering and Robotics, AGH University of Krakow,Al. Adama Mickiewicza 30,230-059 Kraków, Poland
Department of Machine Design and Maintenance, Faculty of Mechanical Engineering and Robotics, AGH University of3Krakow,Al. Adama Mickiewicza 30, 30-059 Kraków, Poland
Faculty of Metals Engineering and Industrial Computer Science, AGH University of Krakow, Al. Adama Mickiewicza 30, 30-059, Kraków, Poland

11 The solution of MRSLP with the use of heuristic algorithms

Joanna Kochańska , Anna Burduk , Dagmara Łapczyńska , Kamil Musiał

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e146407 | DOI: 10.24425/bpasts.2023.146407

Keywords: in-plant logistics milk run heuristic algorithms assembly line genetic algorithm tabu Search simulated annealing

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Abstract

Improving production processes includes not only activities concerning manufacturing itself, but also all the activities that are necessary to achieve the main objectives. One such activity is transport, which, although a source of waste in terms of adding value to the product, is essential to the realization of the production process. Over the years, many methods have been developed to help manage supply and transport in such a way as to reduce it to the necessary minimum. In the paper, the problem of delivering components to a production area using trains and appropriately laid-out carriages was described. It is a milk run stop locations problem (MRSLP), whose proposed solution is based on the use of heuristic algorithms. Intelligent solutions are getting more and more popular in the industry because of the possible advantages they offer, especially those that include the possibility of finding an optimum local solution in a relatively short time and the prevention of human errors. In this paper, the applicability of three algorithms – tabu search, genetic algorithm, and simulated annealing – was explored.

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Authors and Affiliations

Joanna Kochańska

Anna Burduk

e-mail: anna.burduk@pwr.edu.pl

ORCID:

Dagmara Łapczyńska

Kamil Musiał

Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland

12 Mechanical properties of ABS samples manufactured under different process conditions

Piotr Czyżewski , Dawid Marciniak , Dariusz Sykutera

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e147065 | DOI: 10.24425/bpasts.2023.147065

Keywords: FDM injection molding mechanical properties microtomography ABS

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Abstract

The purpose of this study is to determine the effect of manufacturing conditions on the mechanical properties and structure of ABS parts. Two sets of samples with the same geometric characteristics were produced by fused deposition modelling (FDM) and injection molding (IM). The molding pressure and cooling rate were found to have a significant effect on shaping the mechanical properties and structure of ABS products. The manufacturing method and adopted process parameters have a significant impact on the degree of packing of macromolecules in the volume of the product and thus determine its density. Selected mechanical properties were determined and compared with their specific gravity. The research was carried out using tools and machines, i.e. injection molds of unique design and standard measuring stations. Tensile and bending strengths and Young’s modulus were related to the density of products obtained under different process conditions and having gradient and solid structures. The results provide useful information for engineers designing products using FDM technology. Relating tensile and flexural strength and Young’s modulus to the specific gravity of the product. It was found that the value of product properties is closely related to various process conditions, which further provides a true description of the products.

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Authors and Affiliations

Piotr Czyżewski

Dawid Marciniak

e-mail:

ORCID:

Dariusz Sykutera

e-mail:

ORCID:

Department of Manufacturing Techniques, Faculty of Mechanical Engineering, Bydgoszcz University of Science and Technology,Kaliskiego 7, 85-796 Bydgoszcz, Poland

13 Fixed fleet open vehicle routing problem: Mathematical model and a modified ant colony optimization

Majid Yousefikhoshbakht , Farzad Didehvar , Farhad Rahmati , Zakir Hussain Ahmed

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e148253 | DOI: 10.24425/bpasts.2023.148253

Keywords: open vehicle routing problem heterogeneous ant colony optimization combinatorial optimization problems

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Abstract

The fixed fleet heterogeneous open vehicle routing problem (HFFOVRP) is one of the most practical versions of the vehicle routing problem (VRP) defined because the use of rental vehicles reduces the cost of purchasing and routing for shipping companies nowadays. Also, applying a heterogeneous fleet is recommended due to the physical limitations of the streets and efforts to reduce the running costs of these companies. In this paper, a mixed-integer linear programming is proposed for HFFOVRP. Because this problem, like VRP, is related to NP-hard issues, it is not possible to use exact methods to solve real-world problems. Therefore, in this paper, a hybrid algorithm based on the ant colony algorithm called MACO is presented. This algorithm uses only global updating pheromones for a more efficient search of feasible space and considers a minimum value for pheromones on the edges. Also, pheromones of some best solutions obtained so far are updated, based on the quality of the solutions at each iteration, and three local search algorithms are used for the intensification mechanism. This method was tested on several standard instances, and the results were compared with other algorithms. The computational results show that the proposed algorithm performs better than these methods in cost and CPU time. Besides, not only has the algorithm been able to improve the quality of the best-known solutions in nine cases but also the high-quality solutions are obtained for other instances.

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Authors and Affiliations

Majid Yousefikhoshbakht

e-mail:

ORCID:

Farzad Didehvar

Farhad Rahmati

Zakir Hussain Ahmed

Department of Mathematics, Faculty of Sciences, Bu-Ali Sina University, Hamedan, Iran
Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Kingdom of Saudi Arabia

14 Highly efficient scheduling algorithms for identical parallel machines with sufficient conditions for optimality of the solutions

Sergii Telenyk , Grzegorz Nowakowski , Oleksandr Pavlov , Olena Misura , Oleg Melnikov , Olena Khalus

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e148939 | DOI: 10.24425/bpasts.2024.148939

Keywords: scheduling intractable problems of discrete optimisation sufficient conditions for optimality parallel machines common due date

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Abstract

This paper aims to develop new highly efficient PSC-algorithms (algorithms that contain a polynomial-time sub-algorithm with sufficient conditions for the optimality of the solutions obtained) for several interrelated problems involving identical parallel machine scheduling. These problems share common basic theoretical positions and common principles of their solving. Two main intractable scheduling problems are considered: (“Minimization of the total tardiness of jobs on parallel machines with machine release times and a common due date” (TTPR) and “Minimising the total tardiness of parallel machines completion times with respect to the common due date with machine release times” (TTCR)) and an auxiliary one (“Minimising the difference between the maximal and the minimal completion times of the machines” (MDMM)). The latter is used to efficiently solve the first two ones. For the TTPR problem and its generalisation in the case when there are machines with release times that extend past the common due date (TTPRE problem), new theoretical properties are given, which were obtained on the basis of the previously published ones. Based on the new theoretical results and computational experiments the PSC-algorithm solving these two problems is modified (sub-algorithms A1, A2). Then the auxiliary problem MDMM is considered and Algorithm A0 is proposed for its solving. Based on the analysis of computational experiments, A0 is included in the PSC-algorithm for solving the problems TTPR, TTPRE as its polynomial component for constructing a schedule with zero tardiness of jobs if such a schedule exists (a new third sufficient condition of optimality). Next, the second intractable combinatorial optimization problem TTCR is considered, deducing its sufficient conditions of optimality, and it is shown that Algorithm A0 is also an efficient polynomial component of the PSC-algorithm solving the TTCR problem. Next, the case of a schedule structure is analysed (partially tardy), in which the functionals of the TTPR and TTCR problems become identical. This facilitates the use of Algorithm A1 for the TTPR problem in this case of the TTCR problem. For Algorithm A1, in addition to the possibility of obtaining a better solution, there exists a theoretically proven estimate of the deviation of the solution from the optimum. Thus, the second PSC-algorithm solving the TTCR problem finds an exact solution or an approximate solution with a strict upper bound for its deviation from the optimum. The practicability of solving the problems under consideration is substantiated.

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Authors and Affiliations

Sergii Telenyk

e-mail:

ORCID:

Grzegorz Nowakowski

e-mail:

ORCID:

Oleksandr Pavlov

e-mail:

ORCID:

Olena Misura

e-mail:

ORCID:

Oleg Melnikov

e-mail:

ORCID:

Olena Khalus

e-mail:

ORCID:

Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155 Cracow, Poland
National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Prosp. Peremohy 37, Kyiv, Ukraine

15 Machine learning for two-phase gas-liquid flow regime evaluation based on raw 3D ECT measurement data

Radosław Wajman , Jacek Nowakowski , Michał Łukiański , Robert Banasiak

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e148842 | DOI: 10.24425/bpasts.2024.148842

Keywords: neural networks machine learning data augmentation electrical capacitance tomography industrial process monitoring

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Abstract

This paper presents a study on applying machine learning algorithms for the classification of a two-phase flow regime and its internal structures. This research results may be used in adjusting optimal control of air pressure and liquid flow rate to pipeline and process vessels. To achieve this goal the model of an artificial neural network was built and trained using measurement data acquired from a 3D electrical capacitance tomography (ECT) measurement system. Because the set of measurement data collected to build the AI model was insufficient, a novel approach dedicated to data augmentation had to be developed. The main goal of the research was to examine the high adaptability of the artificial neural network (ANN) model in the case of emergency state and measurement system errors. Another goal was to test if it could resist unforeseen problems and correctly predict the flow type or detect these failures. It may help to avoid any pernicious damage and finally to compare its accuracy to the fuzzy classifier based on reconstructed tomography images – authors’ previous work.

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Authors and Affiliations

Radosław Wajman

e-mail:

ORCID:

Jacek Nowakowski

e-mail:

ORCID:

Michał Łukiański

Robert Banasiak

e-mail:

ORCID:

Institute of Applied Computer Science, Lodz University of Technology, Stefanowskiego 18, 90-537 Łódź, Poland

16 Real-time operational load monitoring of a composite aerostructure using FPGA-based computing system

Waldemar Mucha

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e148251 | DOI: 10.24425/bpasts.2023.148251

Keywords: operational load monitoring real time computations FPGA aerostructures neural networks artificial intelligence structural health monitoring green computing

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Abstract

Operational load monitoring (OLM) is an industrial process related to structural health monitoring, where fatigue of the structure is tracked. Artificial intelligence methods, such as artificial neural networks (ANNs) or Gaussian processes, are utilized to improve efficiency of such processes. This paper focuses on moving such processes towards green computing by deploying and executing the algorithm on low-power consumption FPGA where high-throughput and truly parallel computations can be performed. In the following paper, the OLM process of typical aerostructure (hat-stiffened composite panel) is performed using ANN. The ANN was trained using numerically generated data, of every possible load case, to be working with sensor measurements as inputs. The trained ANN was deployed to Xilinx Artix-7 A100T FPGA of a real-time microcontroller. By executing the ANN on FPGA (where every neuron of a given layer can be processed at the same time, without limiting the number of parallel threads), computation time could be reduced by 70% as compared to standard CPU execution. Series of real-time experiments were performed that have proven the efficiency and high accuracy of the developed FPGA-based algorithm. Adjusting the ANN algorithm to FPGA requirements takes some effort, however it can lead to high performance increase. FPGA has the advantages of many more potential parallel threads than a standard CPU and much lower consumption than a GPU. This is particularly important taking into account potential embedded and remote applications, such as widely performed monitoring of airplane structures.

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Authors and Affiliations

Waldemar Mucha

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Department of Computational Mechanics and Engineering, Silesian University of Technology, Konarskiego 18A, 44-100 Gliwice, Poland

17 Fault diagnosis of electrical faults of three-phasei nduction motors using acoustic analysis

Adam Glowacz , Maciej Sulowicz , Jarosław Kozik , Krzysztof Piech , Witold Glowacz , Zhixiong Li , Frantisek Brumercik , Miroslav Gutten , Daniel Korenciak , Anil Kumar , Guilherme Beraldi Lucas , Muhammad Irfan , Wahyu Caesarendra , Hui Lui

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e148440 | DOI: 10.24425/bpasts.2024.148440

Keywords: acoustic signal induction motor fault neural network

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Abstract

Fault diagnosis techniques of electrical motors can prevent unplanned downtime and loss of money, production, and health. Various parts of the induction motor can be diagnosed: rotor, stator, rolling bearings, fan, insulation damage, and shaft. Acoustic analysis is non-invasive. Acoustic sensors are low-cost. Changes in the acoustic signal are often observed for faults in induction motors. In this paper, the authors present a fault diagnosis technique for three-phase induction motors (TPIM) using acoustic analysis. The authors analyzed acoustic signals for three conditions of the TPIM: healthy TPIM, TPIM with two broken bars, and TPIM with a faulty ring of the squirrel cage. Acoustic analysis was performed using fast Fourier transform (FFT), a new feature extraction method called MoD-7 (maxima of differences between the conditions), and deep neural networks: GoogLeNet, and ResNet-50. The results of the analysis of acoustic signals were equal to 100% for the three analyzed conditions. The proposed technique is excellent for acoustic signals. The described technique can be used for electric motor fault diagnosis applications.

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Authors and Affiliations

Adam Glowacz

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Maciej Sulowicz

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Jarosław Kozik

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Krzysztof Piech

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Witold Glowacz

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Zhixiong Li

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Frantisek Brumercik

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Miroslav Gutten

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Daniel Korenciak

Anil Kumar

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Guilherme Beraldi Lucas

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Muhammad Irfan

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Wahyu Caesarendra

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Hui Lui

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Cracow University of Technology, Faculty of Electrical and Computer Engineering, Department of Electrical Engineering, ul. Warszawska 24,31-155 Kraków, Poland
AGH University of Krakow, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of PowerElectronics and Energy Control Systems, al. A. Mickiewicza 30, 30-059 Kraków, Poland
AGH University of Krakow, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of AutomaticControl and Robotics, al. A. Mickiewicza 30, 30-059 Krakw, Poland
Faculty of Mechanical Engineering, Opole University of Technology, Opole 45-758, Poland
University of Religions and Denomina, Qom, Iran
University of Zilina, Faculty of Mechanical Engineering, Department of Design and Machine Elements, Univerzitna 1, 010 26 Zilina, Slovakia
University of Zilina, Faculty of Electrical Engineering and Information Technology, 8215/1 Univerzitna, 01026 Zilina, Slovakia
Wenzhou University, College of Mechanical and Electrical Engineering, Wenzhou, 325 035, China
Sao Paulo State University, Department of Electrical Engineering, Av. Eng. Luís Edmundo Carrijo Coube, 14-01, Bauru, Sao Paulo, Brazil
Najran University Saudi Arabia, Electrical Engineering Department, College of Engineering, Najran 61441, Saudi Arabia
Faculty of Integrated Technologies, Universiti Brunei Darusalam, Jalan Tungku Link, Gadong BE1410, Brunei
China Jiliang University, College of Quality and Safety Engineering, Hangzhou 310018, China

18 DC power supply with parallel active compensation function and tuneable inductive filter based on analogue control: Part 1

Michał Gwóźdź , Łukasz Ciepliński

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e148839 | DOI: 10.24425/bpasts.2024.148839

Keywords: active compensator analogue control power factor correction DC power supply tuneable inductive filter

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Abstract

In this paper, a DC power supply is presented that, in addition to a power factor correction, is equipped with an active power filter function. This function enables compensation of both the reactive and the distortion power, generated by an external load, which is connected to the same power line node as the presented device. A tuneable inductive filter is added at the input of the power electronics controlled current source, which constitutes the main block of the power supply. This filter allows for a visible improvement in the quality of the current source control, compared to a similar device with a fixed inductive filter. This improvement depends on extending the “frequency response” of the current source, which facilitates an increase in the dynamics of changes in the input current of the power supply. The actual modification to the presented device is related to its control section, which is equipped with analogue regulators. The main purpose of this work is to present the results from a simulation model of an electrical system with a power supply, especially compared to those from a similar device but with a discrete control. The work represents a continuation of a research cycle on DC power supplies that are equipped with a power compensation function and are based on tuneable magnetic devices.

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Authors and Affiliations

Michał Gwóźdź

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Łukasz Ciepliński

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Poznan University of Technology, Faculty of Control, Robotics and Electrical Engineering, Piotrowo 3A, 60-965 Poznan, Poland

19 Experimental study of dispersed flow in the thermopressor of the intercooling system for marine and stationary power plants compressors

Dmytro Konovalov , Halina Kobalava , Mykola Radchenko , Terese Løvås , Anatoliy Pavlenko , Roman Radchenko , Andrii Radchenko

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e148439 | DOI: 10.24425/bpasts.2023.148439

Keywords: energy efficiency power plant thermo-gas-dynamic effect compressor contact cooling

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Abstract

This study investigates the use of a thermopressor to achieve highly dispersed liquid atomization, with a primary focus on its application in enhancing contact cooling systems of the cyclic air for gas turbines. The use of a thermopressor results in a substantial reduction in the average droplet diameter, specifically to less than 25 μm, within the dispersed flow. Due to practically instantaneous evaporation of highly atomized liquid droplets in accelerated superheated air the pressure drop is reduced to minimum. A further increase of the air pressure takes place in diffuser. In its turn, this allows for the compensation of hydraulic pressure losses in the air path, thereby reducing compressive work. Experimental data uncover a significant decrease in the average droplet diameter, with reductions ranging from 20 to 30 µm within the thermopressor due to increased flow turbulence and intense evaporation. The minimum achievable droplet diameter is as low as 15 µm and accompanied by a notable increase in the fraction of small droplets (less than 25 µm) to 40–60%. Furthermore, the droplet distribution becomes more uniform, with the absence of large droplets exceeding 70 µm in diameter. Increasing the water flow during injection has a positive impact on the number of smaller droplets, particularly those around 25 μm, which is advantageous for contact cooling. The use of the thermopressor method for cooling cyclic air provides maximum protection to blade surfaces against drop-impact erosion, primarily due to the larger number of droplets with diameters below 25 μm. These findings underline the potential of a properly configured thermopressor to improve the efficiency of contact cooling systems in gas turbines, resulting in improved performance and reliability in power generation applications. The hydrodynamic principles explored in this study may have wide applications in marine and stationary power plants based on gas and steam turbines, gas and internal combustion engines.

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Authors and Affiliations

Dmytro Konovalov

Halina Kobalava

Mykola Radchenko

Terese Løvås

Anatoliy Pavlenko

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Roman Radchenko

Andrii Radchenko

Norwegian University of Science and Technology, Kolbjørn Hejes vei 1a, Trøndelag, Trondheim, 7034, Norway
Admiral Makarov National University of Shipbuilding, Avenue Ushakov 44, Kherson, 73003, Ukraine
Admiral Makarov National University of Shipbuilding, Machine Building Institute, Avenue 9, 54025 Mykolayiv, Ukraine
Kielce University of Technology, Aleja Tysiaclecia Panstwa Polskiego 7, Kielce, 25-314, Poland

20 Can data processing algorithms ensure sufficient accuracy to estimate human body pose via wearable systems with use of IMU sensors? – an experimental evaluation

Aleksandra Szczerba , Piotr Prochor , Szczepan Piszczatowski

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e148835 | DOI: 10.24425/bpasts.2024.148835

Keywords: pose estimation wearable electronics motion sensors inertial measurement unit human motion tracking

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Abstract

Background: The aim of the study was to answer two questions: 1 – Can data processing algorithms ensure sufficient accuracy for estimating human body pose via wearable systems? 2 – How to process the IMU sensor data to obtain the most accurate information on the human body pose? To answer these questions, the authors evaluated proposed algorithms in terms of accuracy and reliability. Methodology: data acquisition was performed with tested IMU sensors system mounted onto a Biodex System device. Research included pendulum movement with seven angular velocities (10-120°/s) in five angular movement ranges (30-120°). Algorithms used data from accelerometers and gyroscopes and considered complementary and/or Kalman filters with adjusted parameters. Moreover, angular velocity registration quality was also taken into consideration. Results: differences between means for angular velocity were 0.55÷1.05°/s and 1.76÷3.11%. In the case of angular position relative error of means was 4.77÷10.84%, relative error of extreme values was 2.15÷4.81% and Spearman’s correlation coefficient was 0.74÷0.89. Conclusions: Algorithm calculating angles based on acceleration-derived quaternions and with implementation of Kalman filter was the most accurate for data processing and can be adapted for future work with IMU sensors systems, especially in wearable devices that are designated to support human in daily activity.

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Aleksandra Szczerba

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Piotr Prochor

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Szczepan Piszczatowski

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Department of Biomaterials and Medical Devices Engineering, Institute of Biomedical Engineering, Faculty of Mechanical Engineering, BialystokUniversity of Technology, Wiejska 45C Street, 15-351 Bialystok, Poland

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