Bulletin of the Polish Academy of Sciences Technical Sciences

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Authors and Affiliations

Stanislaw Osowski

1 2

e-mail:

ORCID:

Bartosz Sawicki

1

e-mail:

ORCID:

Andrzej Cichocki

3

Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, Poland
Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland
RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0106, Japan

3 Multi-feature ensemble system in the renal tumour classification task

Aleksandra Maria Osowska-Kurczab , Tomasz Markiewicz , Miroslaw Dziekiewicz , Malgorzata Lorent

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e136749 | DOI: 10.24425/bpasts.2021.136749

Keywords: medical imaging renal cell carcinoma convolutional neural networks textural features support vector machine computer vision deep learning

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Abstract

Recently, the analysis of medical imaging is gaining substantial research interest, due to advancements in the computer vision field. Automation of medical image analysis can significantly improve the diagnosis process and lead to better prioritization of patients waiting for medical consultation. This research is dedicated to building a multi-feature ensemble model which associates two independent methods of image description: textural features and deep learning. Different algorithms of classification were applied to single-phase computed tomography images containing 8 subtypes of renal neoplastic lesions. The final ensemble includes a textural description combined with a support vector machine and various configurations of Convolutional Neural Networks. Results of experimental tests have proved that such a model can achieve 93.6% of weighted F1-score (tested in 10-fold cross validation mode). Improvement of performance of the best individual predictor totalled 3.5 percentage points.

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Authors and Affiliations

Aleksandra Maria Osowska-Kurczab

1

e-mail:

ORCID:

Tomasz Markiewicz

1 2

e-mail:

ORCID:

Miroslaw Dziekiewicz

2

Malgorzata Lorent

2

Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland
Military Institute of Medicine, ul. Szaserów 128, 04-141 Warsaw, Poland

4 Deep learning-based framework for tumour detection and semantic segmentation

Estera Kot , Zuzanna Krawczyk , Krzysztof Siwek , Leszek Królicki , Piotr Czwarnowski

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e136750 | DOI: 10.24425/bpasts.2021.136750

Keywords: deep learning medical imaging tumour detection semantic segmentation image fusion

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Abstract

For brain tumour treatment plans, the diagnoses and predictions made by medical doctors and radiologists are dependent on medical imaging. Obtaining clinically meaningful information from various imaging modalities such as computerized tomography (CT), positron emission tomography (PET) and magnetic resonance (MR) scans are the core methods in software and advanced screening utilized by radiologists. In this paper, a universal and complex framework for two parts of the dose control process – tumours detection and tumours area segmentation from medical images is introduced. The framework formed the implementation of methods to detect glioma tumour from CT and PET scans. Two deep learning pre-trained models: VGG19 and VGG19-BN were investigated and utilized to fuse CT and PET examinations results. Mask R-CNN (region-based convolutional neural network) was used for tumour detection – output of the model is bounding box coordinates for each object in the image – tumour. U-Net was used to perform semantic segmentation – segment malignant cells and tumour area. Transfer learning technique was used to increase the accuracy of models while having a limited collection of the dataset. Data augmentation methods were applied to generate and increase the number of training samples. The implemented framework can be utilized for other use-cases that combine object detection and area segmentation from grayscale and RGB images, especially to shape computer-aided diagnosis (CADx) and computer-aided detection (CADe) systems in the healthcare industry to facilitate and assist doctors and medical care providers.

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Authors and Affiliations

Estera Kot

1

Zuzanna Krawczyk

1

Krzysztof Siwek

1

Leszek Królicki

2

Piotr Czwarnowski

2

Warsaw University of Technology, Faculty of Electrical Engineering, Pl. Politechniki 1, 00-661 Warsaw, Poland
Medical University of Warsaw, Nuclear Medicine Department, ul. Banacha 1A, 02-097 Warsaw, Poland

5 Segmentation of bone structures with the use of deep learning techniques

Zuzanna Krawczyk , Jacek Starzyński

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e136751 | DOI: 10.24425/bpasts.2021.136751

Keywords: deep learning semantic segmentation U-net FCN ResNet computed tomography

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Abstract

The paper is focused on automatic segmentation task of bone structures out of CT data series of pelvic region. The authors trained and compared four different models of deep neural networks (FCN, PSPNet, U-net and Segnet) to perform the segmentation task of three following classes: background, patient outline and bones. The mean and class-wise Intersection over Union (IoU), Dice coefficient and pixel accuracy measures were evaluated for each network outcome. In the initial phase all of the networks were trained for 10 epochs. The most exact segmentation results were obtained with the use of U-net model, with mean IoU value equal to 93.2%. The results where further outperformed with the U-net model modification with ResNet50 model used as the encoder, trained by 30 epochs, which obtained following result: mIoU measure – 96.92%, “bone” class IoU – 92.87%, mDice coefficient – 98.41%, mDice coefficient for “bone” – 96.31%, mAccuracy – 99.85% and Accuracy for “bone” class – 99.92%.

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Authors and Affiliations

Zuzanna Krawczyk

1

Jacek Starzyński

1

Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland

6 U-Net based frames partitioning and volumetric analysis for kidney detection in tomographic images

Tomasz Les

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137051 | DOI: 10.24425/bpasts.2021.137051

Keywords: kidney detection medical image processing U-Net frames partitioning volumetric analysis

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Abstract

This work presents an automatic system for generating kidney boundaries in computed tomography (CT) images. This paper presents the main points of medical image processing, which are the parts of the developed system. The U-Net network was used for image segmentation, which is now widely used as a standard solution for many medical image processing tasks. An innovative solution for framing the input data has been implemented to improve the quality of the learning data as well as to reduce the size of the data. Precision-recall analysis was performed to calculate the optimal image threshold value. To eliminate false-positive errors, which are a common issue in segmentation based on neural networks, the volumetric analysis of coherent areas was applied. The developed system facilitates a fully automatic generation of kidney boundaries as well as the generation of a three-dimensional kidney model. The system can be helpful for people who deal with the analysis of medical images, medical specialists in medical centers, especially for those who perform the descriptions of CT examination. The system works fully automatically and can help to increase the accuracy of the performed medical diagnosis and reduce the time of preparing medical descriptions.

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Authors and Affiliations

Tomasz Les

1

Faculty of Electrical Engineering, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warszawa, Poland

7 A new method of cardiac sympathetic index estimation using a 1D-convolutional neural network

Marcin Kołodziej , Andrzej Majkowski , Paweł Tarnowski , Remigiusz Jan Rak , Andrzej Rysz

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e136921 | DOI: 10.24425/bpasts.2021.136921

Keywords: epilepsy seizure detection seizure prediction convolutional neural network deep learning ECG HRV cardiac sympathetic index

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Abstract

Epilepsy is a neurological disorder that causes seizures of many different types. The article presents an analysis of heart rate variability (HRV) for epileptic seizure prediction. Considering that HRV is nonstationary, our research focused on the quantitative analysis of a Poincare plot feature, i.e. cardiac sympathetic index (CSI). It is reported that the CSI value increases before the epileptic seizure. An algorithm using a 1D-convolutional neural network (1D-CNN) was proposed for CSI estimation. The usability of this method was checked for 40 epilepsy patients. Our algorithm was compared with the method proposed by Toichi et al. The mean squared error (MSE) for testing data was 0.046 and the mean absolute percentage error (MAPE) amounted to 0.097. The 1D-CNN algorithm was also compared with regression methods. For this purpose, a classical type of neural network (MLP), as well as linear regression and SVM regression, were tested. In the study, typical artifacts occurring in ECG signals before and during an epileptic seizure were simulated. The proposed 1D-CNN algorithm estimates CSI well and is resistant to noise and artifacts in the ECG signal.

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Marcin Kołodziej

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Andrzej Majkowski

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Paweł Tarnowski

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Remigiusz Jan Rak

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Andrzej Rysz

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8 Deep learning vs feature engineering in the assessment of voice signals for diagnosis in Parkinson’s disease

Ewelina Majda-Zdancewicz , Anna Potulska-Chromik , Jacek Jakubowski , Monika Nojszewska , Anna Kostera-Pruszczyk

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137347 | DOI: 10.24425/bpasts.2021.137347

Keywords: voice processing Parkinson’s disease non-linear analysis convolutional networks

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Abstract

Voice acoustic analysis can be a valuable and objective tool supporting the diagnosis of many neurodegenerative diseases, especially in times of distant medical examination during the pandemic. The article compares the application of selected signal processing methods and machine learning algorithms for the taxonomy of acquired speech signals representing the vowel a with prolonged phonation in patients with Parkinson’s disease and healthy subjects. The study was conducted using three different feature engineering techniques for the generation of speech signal features as well as the deep learning approach based on the processing of images involving spectrograms of different time and frequency resolutions. The research utilized real recordings acquired in the Department of Neurology at the Medical University of Warsaw, Poland. The discriminatory ability of feature vectors was evaluated using the SVM technique. The spectrograms were processed by the popular AlexNet convolutional neural network adopted to the binary classification task according to the strategy of transfer learning. The results of numerical experiments have shown different efficiencies of the examined approaches; however, the sensitivity of the best test based on the selected features proposed with respect to biological grounds of voice articulation reached the value of 97% with the specificity no worse than 93%. The results could be further slightly improved thanks to the combination of the selected deep learning and feature engineering algorithms in one stacked ensemble model.

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Authors and Affiliations

Ewelina Majda-Zdancewicz

1

e-mail:

ORCID:

Anna Potulska-Chromik

2

e-mail:

ORCID:

Jacek Jakubowski

1

e-mail:

ORCID:

Monika Nojszewska

2

e-mail:

ORCID:

Anna Kostera-Pruszczyk

2

e-mail:

ORCID:

Faculty of Electronics, Military University of Technology, ul. Gen. Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland
Department of Neurology, Medical University of Warsaw, ul. Banacha 1a, 02-097 Warsaw, Poland

9 Fusion of feature selection methods in gene recognition

Fabian Gil , Stanislaw Osowski

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e136748 | DOI: 10.24425/bpasts.2021.136748

Keywords: diagnostic features selection methods genes recognition biomarkers

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Abstract

The paper presents the fusion approach of different feature selection methods in pattern recognition problems. The following methods are examined: nearest component analysis, Fisher discriminant criterion, refiefF method, stepwise fit, Kolmogorov-Smirnov criteria, T2-test, Kruskall-Wallis test, feature correlation with class, and SVM recursive feature elimination. The sensitivity to the noisy data as well as the repeatability of the most important features are studied. Based on this study, the best selection methods are chosen and applied in the process of selection of the most important genes and gene sequences in a dataset of gene expression microarray in prostate and ovarian cancers. The results of their fusion are presented and discussed. The small selected set of such genes can be treated as biomarkers of cancer.

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Authors and Affiliations

Fabian Gil

1

Stanislaw Osowski

1 2

e-mail:

ORCID:

Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, Poland
Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland

10 Optimisation of MCTS player for The Lord of the Rings: The Card Game

Konrad Godlewski , Bartosz Sawicki

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e136752 | DOI: 10.24425/bpasts.2021.136752

Keywords: Computational Intelligence Monte-Carlo Tree Search LoTR

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Abstract

The article presents research on the use of Monte-Carlo Tree Search (MCTS) methods to create an artificial player for the popular card game “The Lord of the Rings”. The game is characterized by complicated rules, multi-stage round construction, and a high level of randomness. The described study found that the best probability of a win is received for a strategy combining expert knowledge-based agents with MCTS agents at different decision stages. It is also beneficial to replace random playouts with playouts using expert knowledge. The results of the final experiments indicate that the relative effectiveness of the developed solution grows as the difficulty of the game increases.

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Authors and Affiliations

Konrad Godlewski

1

Bartosz Sawicki

1

e-mail:

ORCID:

Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland

11 Research on hybrid modeling and predictive energy management for power split hybrid electric vehicle

Shaohua Wang , Sheng Zhang , Dehua Shi , Xiaoqiang Sun , Tao Yang

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137064 | DOI: 10.24425/bpasts.2021.137064

Keywords: power split HEV energy management mixed logical dynamical model piecewise affine model predictive control

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Abstract

Due to the coexistence of continuity and discreteness, energy management of a multi-mode power split hybrid electric vehicle (HEV) can be considered a typical hybrid system. Therefore, the hybrid system theory is applied to investigate the optimum energy distribution strategy of a power split multi-mode HEV. In order to obtain a unified description of the continuous/discrete dynamics, including both the steady power distribution process and mode switching behaviors, mixed logical dynamical (MLD) modeling is adopted to build the control-oriented model. Moreover, linear piecewise affine (PWA) technology is applied to deal with nonlinear characteristics in MLD modeling. The MLD model is finally obtained through a high level modeling language, i.e. HYSDEL. Based on the MLD model, hybrid model predictive control (HMPC) strategy is proposed, where a mixed integer quadratic programming (MIQP) problem is constructed for optimum power distribution. Simulation studies under different driving cycles demonstrate that the proposed control strategy can have a superior control effect as compared with the rule-based control strategy.

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Authors and Affiliations

Shaohua Wang

1

Sheng Zhang

1

Dehua Shi

1 2 3

Xiaoqiang Sun

1

Tao Yang

3

e-mail:

ORCID:

Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
Vehicle Measurement, Control and Safety Key Laboratory of Sichuan Province, Xihua University, Chengdu 610039, China
Jiangsu Chunlan Clean Energy Research Institute Co., Ltd., Taizhou 225300, China

12 IEC 61850 interface for real time power system simulation

Karol Kurek , Łukasz Nogal , Ryszard Kowalik , Marcin Januszewski

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137057 | DOI: 10.24425/bpasts.2021.137057

Keywords: implementation in real time power system protection relays testing computer simulation IEC 61850

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Abstract

Real time simulators of IEC 61850 compliant protection devices can be implemented without their analogue part, reducing costs and increasing versatility. Implementation of Sampled Values (SV) and GOOSE interfaces to Matlab/Simulink allows for interaction with protection relays in closed loop during power system simulation. Properly configured and synchronized Linux system with Real Time (RT) patch, can be used as a low latency run time environment for Matlab/Simulink generated model. The number of overruns during model execution using proposed SV and GOOSE interfaces with 50 µs step size is minimal. The paper discusses the implementation details and time synchronization methods of IEC 61850 real time simulator implemented in Matlab/Simulink that is built on top of run time environment shown in authors preliminary works and is the further development of them. Correct operation of the proposed solution is evaluated during the hardware-in-the-loop testing of ABB REL670 relay.

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Authors and Affiliations

Karol Kurek

1

e-mail:

ORCID:

Łukasz Nogal

1

e-mail:

ORCID:

Ryszard Kowalik

1

Marcin Januszewski

1

Faculty of Electrical Engineering, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warszawa, Poland

13 Active power losses and energy efficiency analysis of HPS lamps with electromagnetic control gear and electronic ballast under the sinusoidal and nonsinusoidal condition

Roman Sikora , Przemysław Markiewicz , Paweł Rózga

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137194 | DOI: 10.24425/bpasts.2021.137194

Keywords: HPS lamp electromagnetic control gear electronic ballast energy performance indicator road lighting

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Abstract

Outdoor lighting is an important element in creating an evening and nocturnal image of urban spaces. Properly designed and constructed lighting installations provide residents with comfort and security. One way to improve the energy efficiency of road lighting installation is to replace the electromagnetic control gear (ECG) with electronic ballasts (EB). The main purpose of this article is to provide an in-depth comparative analysis of the energy efficiency and performance of HPS lamps with ECG and EB. It will compare their performance under sinusoidal and nonsinusoidal voltage supply conditions for the four most commonly used HPS lamps of 70 W, 100 W, 150 W, and 250 W. The number of luminaires supplied from one circuit was determined based on the value of permissible active power losses. With the use of the DIALux program, projects of road lighting installation were developed. On this basis, energy performance indicators, electricity consumption, electricity costs, and CO 2 emissions were calculated for one-phase and three-phase installations. The obtained results indicate that an HPS lamp with EB is better than an HPS lamp with ECG in terms of energy quality, energy savings, and environmental impact. The results of this analysis are expected to assist in the choice of HPS lighting technology.

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Authors and Affiliations

Roman Sikora

1

e-mail:

ORCID:

Przemysław Markiewicz

1

e-mail:

ORCID:

Paweł Rózga

1

Lodz University of Technology, Institute of Electrical Power Engineering, ul. Stefanowskiego 18/22, 90-924 Lodz, Poland

14 Prediction of Kaplan turbine coordination tests based on least squares support vector machine with an improved grey wolf optimization algorithm

Fannie Kong , Jiahui Xia , Daliang Yang , Ming Luo

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137124 | DOI: 10.24425/bpasts.2021.137124

Keywords: Kaplan turbine coordination tests least squares support vector machine improved grey wolf optimization

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Abstract

The optimum combination of blade angle of the runner and guide vane opening with Kaplan turbine can improve the hydroelectric generating the set operation efficiency and the suppression capability of oscillations. Due to time and cost limitations and the complex operation mechanism of the Kaplan turbine, the coordination test data is insufficient, making it challenging to obtain the whole curves at each head under the optimum coordination operation by field tests. The field test data is employed to propose a least-squares support vector machine (LSSVM)-based prediction model for Kaplan turbine coordination tests. Considering the small sample characteristics of the test data of Kaplan turbine coordination, the LSSVM parameters are optimized by an improved grey wolf optimization (IGWO) algorithm with mixed non-linear factors and static weights. The grey wolf optimization (GWO) algorithm has some deficiencies, such as the linear convergence factor, which inaccurately simulates the actual situation, and updating the position indeterminately reflects the absolute leadership of the leader wolf. The IGWO algorithm is employed to overcome the aforementioned problems. The prediction model is simulated to verify the effectiveness of the proposed IGWO-LSSVM. The results show high accuracy with small samples, a 2.59% relative error in coordination tests, and less than 1.85% relative error in non-coordination tests under different heads.

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Authors and Affiliations

Fannie Kong

1

e-mail:

ORCID:

Jiahui Xia

1

e-mail:

ORCID:

Daliang Yang

1

e-mail:

ORCID:

Ming Luo

1

e-mail:

ORCID:

School of Electrical Engineering, Guangxi University, Nanning, 530000, China

15 Thermal problems during start-up of cage induction motors

Jan Mróz , Piotr Bogusz

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137058 | DOI: 10.24425/bpasts.2021.137058

Keywords: cage induction motor direct start-up softstart winding temperature

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Abstract

This article considers the problem of the rise in temperature of the windings of an induction motor during start-up. Excessive growth of thermal stresses in the structure of a cage winding increases the probability of damage to the winding of the rotor. For the purpose of analysis of the problem, simplified mathematical relationships are given, enabling the comparison of quantities of energy released in a rotor winding during start-up by different methods. Also, laboratory tests were carried out on a specially adapted cage induction motor enabling measurement of the temperature of a rotor winding during its operation. Because there was no possibility of investigating motors in medium- and high-power drive systems, the authors decided to carry out tests on a low-power motor. The study concerned the start-up of a drive system with a 4 kW cage induction motor. Changes in the winding temperature were recorded for three cases: direct online start-up, soft starting, and the use of a variable-frequency drive (VFD). Conclusions were drawn based on the results obtained. In high-power motors, the observed phenomena occur with greater intensity, because of the use of deep bar and double cage rotors. For this reason, indication is made of the particular need for research into the energy aspects of different start-up methods for medium- and high-power cage induction motors in conditions of prolonged start-up.

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Authors and Affiliations

Jan Mróz

1

Piotr Bogusz

1

Rzeszów University of Technology, The Faculty of Electrical and Computer Engineering, al. Powstańców Warszawy 12, 35-959 Rzeszów, Poland

16 Nonlinear PID controller parameter optimization using modified hybrid artificial bee colony algorithm for continuous stirred tank reactor

Nedumal Pugazhenthi P , S. Selvaperumal , K. Vijayakumar

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137348 | DOI: 10.24425/bpasts.2021.137348

Keywords: artificial bee colony stirred tank reactor genetic algorithm nonlinear PID controller performance measures

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Abstract

The artificial bee colony (ABC) algorithm is well known and widely used optimization method based on swarm intelligence, and it is inspired by the behavior of honeybees searching for a high amount of nectar from the flower. However, this algorithm has not been exploited sufficiently. This research paper proposes a novel method to analyze the exploration and exploitation of ABC. In ABC, the scout bee searches for a source of random food for exploitation. Along with random search, the scout bee is guided by a modified genetic algorithm approach to locate a food source with a high nectar value. The proposed algorithm is applied for the design of a nonlinear controller for a continuously stirred tank reactor (CSTR). The statistical analysis of the results confirms that the proposed modified hybrid artificial bee colony (HMABC) achieves consistently better performance than the traditional ABC algorithm. The results are compared with conventional ABC and nonlinear PID (NLPID) to show the superiority of the proposed algorithm. The performance of the HMABC algorithm-based controller is competitive with other state-of-the-art meta-heuristic algorithm-based controllers in the literature.

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Authors and Affiliations

Nedumal Pugazhenthi P

1

S. Selvaperumal

1

e-mail:

ORCID:

K. Vijayakumar

2

Department of EEE, Syed Ammal Engineering College, Ramanathapuram, Tamilnadu, India
Department of electronics and instrumentation, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamilnadu, India

17 NFTSM control of direct yaw moment for autonomous electric vehicles with consideration of tire nonlinear mechanical properties

Xiaoqiang Sun , Yujun Wang , Yingfeng Cai , Pak Kin Wong , Long Chen

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137065 | DOI: 10.24425/bpasts.2021.137065

Keywords: autonomous electric vehicles direct yaw moment control (DYC) tire nonlinear mechanical properties nonsingular fast terminal sliding mode (NFTSM) trust-region interior-point method

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Abstract

To improve the curve driving stability and safety under critical maneuvers for four-wheel-independent drive autonomous electric vehicles, a three-stage direct yaw moment control (DYC) strategy design procedure is proposed in this work. The first stage conducts the modeling of the tire nonlinear mechanical properties, i.e. the coupling relationship between the tire longitudinal force and the tire lateral force, which is crucial for the DYC strategy design, in the STI (Systems Technologies Inc.) form based on experimental data. On this basis, a 7-DOF vehicle dynamics model is established and the direct yaw moment calculation problem of the four-wheel-independent drive autonomous electric vehicle is solved through the nonsingular fast terminal sliding mode (NFTSM) control method, thus the optimal direct yaw moment can be obtained. To achieve this direct yaw moment, an optimal allocation problem of the tire forces is further solved by using the trust-region interior-point method, which can effectively guarantee the solving efficiency of complex optimization problem like the tire driving and braking forces allocation of four wheels in this work. Finally, the effectiveness of the DYC strategy proposed for the autonomous electric vehicles is verified through the CarSim-Simulink co-simulation results.

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Authors and Affiliations

Xiaoqiang Sun

1 2

Yujun Wang

1

Yingfeng Cai

1

Pak Kin Wong

3

Long Chen

2

e-mail:

ORCID:

Automotive Engineering Research Institute, Jiangsu University, Zhenjiang Jiangsu, China
State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China
Department of Electromechanical Engineering, University of Macau, Taipa, Macau

18 Fault detection for DFIG based on sliding mode observer of new reaching law

RuiQi Li , Wenxin Yu , JunNian Wang , Yang Lu , Dan Jiang , GuoLiang Zhong , ZuanBo Zhou

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137389 | DOI: 10.24425/bpasts.2021.137389

Keywords: fault detection doubly-fed induction generator sliding mode observer new reaching law

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Abstract

For fault detection of doubly-fed induction generator (DFIG), in this paper, a method of sliding mode observer (SMO) based on a new reaching law (NRL) is proposed. The SMO based on the NRL (NRL- SMO) theoretically eliminates system chatter caused by the reaching law and can be switched in time with system interference in terms of robustness and smoothness. In addition, the sliding mode control law is used as the index of fault detection. Firstly, this paper gives the NRL with the theoretically analyzes. Secondly, according to the mathematical model of DFIG, NRL-SMO is designed, and its analysis of stability and robustness are carried out. Then this paper describes how to choose the optimal parameters of the NRL-SMO. Finally, three common wind turbine system faults are given, which are DFIG inter-turn stator fault, grid voltage drop fault, and rotor current sensor fault. The simulation models of the DFIG under different faults is established. The simulation results prove that the superiority of the method of NRL-SMO in state tracking and the feasibility of fault detection.

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Authors and Affiliations

RuiQi Li

1 2

Wenxin Yu

1 2

JunNian Wang

3 2

Yang Lu

1 2

Dan Jiang

1 2

GuoLiang Zhong

1 2

ZuanBo Zhou

1 2

School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China
Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China
School of Physics and Electronics, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China

19 Hybrid synchronization and parameter estimation of a complex chaotic network of permanent magnet synchronous motors using adaptive integral sliding mode control

Nazam Siddique , Fazal U. Rehman

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137056 | DOI: 10.24425/bpasts.2021.137056

Keywords: chaotic systems hybrid synchronization (HS) complex chaotic permanent magnet synchronous motor adaptive integral sliding mode control (ISMC) Lyapunov function

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Abstract

The synchronisation of a complex chaotic network of permanent magnet synchronous motor systems has increasing practical importance in the field of electrical engineering. This article presents the control design method for the hybrid synchronization and parameter estimation of ring-connected complex chaotic network of permanent magnet synchronous motor systems. The design of the desired control law is a challenging task for control engineers due to parametric uncertainties and chaotic responses to some specific parameter values. Controllers are designed based on the adaptive integral sliding mode control to ensure hybrid synchronization and estimation of uncertain terms. To apply the adaptive ISMC, firstly the error system is converted to a unique system consisting of a nominal part along with the unknown terms which are computed adaptively. The stabilizing controller incorporating nominal control and compensator control is designed for the error system. The compensator controller, as well as the adopted laws, are designed to get the first derivative of the Lyapunov equation strictly negative. To give an illustration, the proposed technique is applied to 4-coupled motor systems yielding the convergence of error dynamics to zero, estimation of uncertain parameters, and hybrid synchronization of system states. The usefulness of the proposed method has also been tested through computer simulations and found to be valid.

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Authors and Affiliations

Nazam Siddique

1

e-mail:

ORCID:

Fazal U. Rehman

1

Capital University of Science and Technology, Islamabad Expressway, Kahuta Road, Zone-V Islamabad, Pakistan

20 Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks

Jarosław Krzywanski , Karol Sztekler , Marcin Bugaj , Wojciech Kalawa , Karolina Grabowska , Patryk Robert Chaja , Marcin Sosnowski , Wojciech Nowak , Łukasz Mika , Sebastian Bykuć

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137054 | DOI: 10.24425/bpasts.2021.137054

Keywords: adsorption heat pumps polygeneration cooling capacity low-grade thermal energy artificial neural networks soft computing

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Abstract

Adsorption cooling and desalination technologies have recently received more attention. Adsorption chillers, using eco-friendly refrigerants, provide promising abilities for low-grade waste heat recovery and utilization, especially renewable and waste heat of the near ambient temperature. However, due to the low coefficient of performance (COP) and cooling capacity (CC) of the chillers, they have not been widely commercialized. Although operating in combined heating and cooling (HC) systems, adsorption chillers allow more efficient conversion and management of low-grade sources of thermal energy, their operation is still not sufficiently recognized, and the improvement of their performance is still a challenging task. The paper introduces an artificial intelligence (AI) approach for the optimization study of a two-bed adsorption chiller operating in an existing combined HC system, driven by low-temperature heat from cogeneration. Artificial neural networks are employed to develop a model that allows estimating the behavior of the chiller. Two crucial energy efficiency and performance indicators of the adsorption chiller, i.e., CC and the COP, are examined during the study for different operating sceneries and a wide range of operating conditions. Thus this work provides useful guidance for the operating conditions of the adsorption chiller integrated into the HC system. For the considered range of input parameters, the highest CC and COP are equal to 12.7 and 0.65 kW, respectively. The developed model, based on the neurocomputing approach, constitutes an easy-to-use and powerful optimization tool for the adsorption chiller operating in the complex HC system.

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Authors and Affiliations

Jarosław Krzywanski

1

e-mail:

ORCID:

Karol Sztekler

2

e-mail:

ORCID:

Marcin Bugaj

3

e-mail:

ORCID:

Wojciech Kalawa

2

e-mail:

ORCID:

Karolina Grabowska

1

e-mail:

ORCID:

Patryk Robert Chaja

4

e-mail:

ORCID:

Marcin Sosnowski

1

e-mail:

ORCID:

Wojciech Nowak

2

e-mail:

ORCID:

Łukasz Mika

2

e-mail:

ORCID:

Sebastian Bykuć

4

e-mail:

ORCID:

Jan Dlugosz University in Czestochowa, Faculty of Science and Technology, ul. A. Krajowej 13/15, 42-200 Czestochowa, Poland
AGH University of Science and Technology, Faculty of Energy and Fuels, ul. A. Mickiewicza 30, 30-059 Cracow, Poland
Warsaw University of Technology, Faculty of Power and Aeronautical Engineering, ul. Nowowiejska 24, 00-665 Warsaw, Poland
Institute of Fluid-Flow Machinery Polish Academy of Sciences, Department of Distributed Energy, ul. Fiszera 14, 80-952 Gdansk, Poland

21 Multi-line signal change detection for image segmentation with application in the ceramic tile industry

Filip Sušac , Tomislav Matić , Ivan Aleksi , Tomislav Keser

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137121 | DOI: 10.24425/bpasts.2021.137121

Keywords: segmentation edge detection biscuit tile image processing visual inspection ceramic industry

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Abstract

In the ceramic industry, quality control is performed using visual inspection in three different product stages: green, biscuit, and the final ceramic tile. To develop a real-time computer visual inspection system, the necessary step is successful tile segmentation from its background. In this paper, a new statistical multi-line signal change detection (MLSCD) segmentation method based on signal change detection (SCD) method is presented. Through experimental results on seven different ceramic tile image sets, MLSCD performance is analyzed and compared with the SCD method. Finally, recommended parameters are proposed for optimal performance of the MLSCD method.

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Authors and Affiliations

Filip Sušac

1

Tomislav Matić

1

Ivan Aleksi

1

Tomislav Keser

1

J. J. Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Kneza Trpimira 2B, 31000 Osijek, Croatia

22 Aspect-based sentiment classification model employing whale-optimized adaptive neural network

Nallathambi Balaganesh , K. Muneeswaran

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137271 | DOI: 10.24425/bpasts.2021.137271

Keywords: aspect-based sentiment analysis whale optimization algorithm artificial neural network opinion mining

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Abstract

Nowadays in e-commerce applications, aspect-based sentiment analysis has become vital, and every consumer started focusing on various aspects of the product before making the purchasing decision on online portals like Amazon, Walmart, Alibaba, etc. Hence, the enhancement of sentiment classification considering every aspect of products and services is in the limelight. In this proposed research, an aspect-based sentiment classification model has been developed employing sentiment whale-optimized adaptive neural network (SWOANN) for classifying the sentiment for key aspects of products and services. The accuracy of sentiment classification of the product and services has been improved by the optimal selection of weights of neurons in the proposed model. The promising results are obtained by analyzing the mobile phone review dataset when compared with other existing sentiment classification approaches such as support vector machine (SVM) and artificial neural network (ANN). The proposed work uses key features such as the positive opinion score, negative opinion score, and term frequency-inverse document frequency (TF-IDF) for representing each aspect of products and services, which further improves the overall effectiveness of the classifier. The proposed model can be compatible with any sentiment classification problem of products and services.

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Authors and Affiliations

Nallathambi Balaganesh

1

e-mail:

ORCID:

K. Muneeswaran

1

e-mail:

ORCID:

Department of Computer Science & Engineering, Mepco Schlenk Engineering College (Autonomous), Sivakasi, Tamilnadu, India

23 Bio inspired salamander robot with Pneu-Net Soft actuators – design and walking gait analysis

Elango Natarajan , Kwang Y. Chia , Ahmad Athif Mohd Faudzi , Wei Hong Lim , Chun Kit Ang , Ali Jafaari

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137055 | DOI: 10.24425/bpasts.2021.137055

Keywords: soft actuator pneumatic network salamander robot hyperelastic parametric study

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Abstract

The research was attempted to mimic the locomotion of the salamander, which is found to be one of the main animals from an evolutionary point of view. The design of the limb and body was started with the parametric studies of pneumatic network (Pneu-Net). Pneu-Net is a pneumatically operated soft actuator that bends when compressed fluid is passed inside the chamber. Finite Element Analysis software, ANSYS, was used to evaluate the height of the chamber, number of chambers and the gap between chambers for both limb and body of the soft mechanism. The parameters were decided based on the force generated by the soft actuators. The assembly of the salamander robot was then exported to MATLAB for simulating the locomotion of the robot in a physical environment. Sine-based controller was used to simulate the robot model and the fastest locomotion of the salamander robot was identified at 1 Hz frequency, 0.3 second of signal delay for limb actuator and negative π phase difference for every contralateral side of the limbs. Shin-Etsu KE-1603, a hyper elastic material, was used to build the salamander robot and a series of experiments were conducted to record the bending angle, the respective generated force in soft actuators and the gait speed of the robot. The developed salamander robot was able to walk at 0.06774 m/s, following an almost identical pattern to the simulation.

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Authors and Affiliations

Elango Natarajan

1

e-mail:

ORCID:

Kwang Y. Chia

1

Ahmad Athif Mohd Faudzi

2

Wei Hong Lim

1

Chun Kit Ang

1

Ali Jafaari

2

Faculty of Engineering, UCSI University, Kuala Lumpur, Malaysia
Center for Artificial Intelligence and Robotics (CAIRO), Universiti Teknologi Malaysia, Kulala Lumpur, Malaysia

24 Fluidized bed in gravitational shelf dryers: optimization calculation

Nadiia Artyukhova , Jan Krmela , Vladimíra Krmelová , Artem Artyukhov , Mária Gavendová

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137388 | DOI: 10.24425/bpasts.2021.137388

Keywords: multistage gravitational shelf dryer fluidized bed hydrodynamics motion trajectory simulation of engineering calculation

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Abstract

The article deals with studying the hydrodynamic characteristics of the fluidized bed in gravitation shelf dryers. The algorithm to calculate hydrodynamic characteristics of the fluidized bed in the dryer’s workspace is described. Every block of the algorithm has a primary hydrodynamic characteristics theoretical model of calculation. Principles of disperse phase motion in various areas in the gravitation shelf dryer are established. The software realization of the author’s mathematic model to calculate disperse phase motion trajectory in a free and constrained regime, disperse phase residence time in the dryers’ workspace, polydisperse systems classification is proposed in the study. Calculations of disperse phase motion hydrodynamic characteristics using the software product ANSYS CFX, based on the author’s mathematic model, are presented in the article. The software product enables automating calculation simultaneously by several optimization criteria and visualizing calculation results in the form of 3D images. The disperse phase flow velocity fields are obtained; principles of a wide fraction of the disperse phase distribution in the workspace of the shelf dryer are fixed. The way to define disperse phase residence time91 in the workspace of the shelf dryer in free (without consideration of cooperation with other particles and dryer’s elements) and con-strained motion regimes is proposed in the research. The calculation results make a base for the optimal choice of the gravitation shelf dryer working chamber sizes.

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B. Paprocki, A. Pregowska and J. Szczepanski, “Optimizing information processing in brain-inspired neural networks”, Bull. Pol. Acad. Sci. Tech. Sci. 68(2), 225‒233 (2020), doi: 10.24425/bpasts.2020.131844.
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Authors and Affiliations

Nadiia Artyukhova

1

Jan Krmela

2

e-mail:

ORCID:

Vladimíra Krmelová

3

Artem Artyukhov

1

e-mail:

ORCID:

Mária Gavendová

3

Sumy State University, Oleg Balatskyi Academic and Research Institute of Finance, Economics and Management, Department of Marketing, Rymskogo-Korsakova st. 2, 40007, Sumy, Ukraine
Alexander Dubček University of Trenčín, Faculty of Industrial Technologies in Púchov, Department of Numerical Methods and Computational Modeling, Ivana Krasku 491/30, 020 01 Púchov, Slovakia
Alexander Dubček University of Trenčín, Faculty of Industrial Technologies in Púchov, Department of Material Technologies and Environment, Ivana Krasku 491/30, 020 01 Púchov, Slovakia

25 Adaptation of the machine to the new geological conditions – excavation unit redesign and optimization

Jakub Andruszko , Przemyslaw Moczko , Damian Pietrusiak

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137122 | DOI: 10.24425/bpasts.2021.137122

Keywords: dredger rigid-body dynamic 3D scanning discrete element method finite element method

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Abstract

The paper presents and sums up the research and technical aspects of the modernization of the cutting tool of the dredger. Improper adjustment of the cutting elements not adjusted to the characteristics of excavated material is not an uncommon situation, causing versatile geological conditions. Relocation of the machines from one pit to another may result in the significant influence on the excavation process (wear, output, etc.). Common practice is the field try and error approach to obtain desired machine performance. In the paper authors present the approach with aid of cutting-edge technologies. Coupled DEM and kinematic simulations supported by the reverse engineering technologies of laser scanning were the fundamental drivers for final adjustments of the cutting tool at its present operational conditions.

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Authors and Affiliations

Jakub Andruszko

1

Przemyslaw Moczko

1

Damian Pietrusiak

1

Department of Machine Design and Research, Wroclaw University of Science and Technology, ul. Ignacego Lukasiewicza 7/9, 50-371 Wroclaw, Poland

26 Impact of heat treatment on the mechanical performance of hot extruded Al6061-BN reinforced metal matrix composites

Y.B. Mukesh , Prem Kumar Naik , Raghavendra Rao R , N.R. Vishwanatha , N.S. Prema , H.N. Girish , Naik L. Laxmana , Puttaswamy Madhusudan

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137014 | DOI: 10.24425/bpasts.2021.137014

Keywords: Al6061 metal matrix composites boron nitride heat treatment hot extrusion

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Abstract

Boron nitride (BN) reinforced Al6061 aluminum-based composites are synthesized by conventional stir casting method followed by exposure to hot extrusion. The optical images confirmed the distribution of BN nanoparticles in the aluminum alloy matrix. The concentration of BN is varied from (0.5, 1.5, 3, 4.5, 6, 7.5, and 9 wt%) in the composites and its effect on the tensile strength was investigated. The results revealed that both extruded and heat-treated composites specimens showed enhanced toughness and tensile strength by increasing BN nanoparticle concentration. The heat-treated composite samples showed lower flexibility of up to 40%, and further, it exhibited 37% greater hardness and 32% enhancement in tensile strength over the extruded sample. The tensile properties of Al6061-BN composites were evaluated by temperature-dependent internal friction (TDIF) analysis and the results showed that the as-prepared composite's strength increased with temperature.

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Authors and Affiliations

Y.B. Mukesh

1

Prem Kumar Naik

2

Raghavendra Rao R

3

N.R. Vishwanatha

4

N.S. Prema

5

H.N. Girish

6

Naik L. Laxmana

3

Puttaswamy Madhusudan

7 8

e-mail:

ORCID:

Department of Mechanical Engineering, Chaitanya Bharathi Institute of Technology, Proddatur, Andhra Pradesh, India
Department of Mechanical Engineering, AMC Engineering College, Bengaluru, India
Department of Mechanical Engineering, Malnad College of Engineering, Hassan, India
Department of Mechanical Engineering, Navkis College of Engineering, Hassan, India
Department of Information Science and Engineering, Vidyavardhaka College of Engineering, Mysore, India
Department of Studies in Earth Science, University of Mysore, 570006, India
Environmental Engineering and Management Research Group, Ton Duc Thang University, Ho Chi Minh City 758307, Vietnam
Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City 758307, Vietnam

27 Mechanical properties and geometric accuracy of angle-shaped parts manufactured using the FFF method

Wiesław Kuczko , Adam Hamrol , Radosław Wichniarek , Filip Górski , Michał Rogalewicz

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137387 | DOI: 10.24425/bpasts.2021.137387

Keywords: material extrusion additive manufacturing mechanical properties angle-shaped parts

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Abstract

The paper presents the results of research on the influence of the parameters of Fused Deposition Modelling (FDM) on the mechanical properties and geometric accuracy of angle-shaped parts. The samples were manufactured from acrylonitrile butadiene styrene (ABS) on a universal machine. A complete factorial experiment was conducted. The results indicated that the critical technological parameter was the angular orientation of the sample in the working chamber of the machine. The results were compared with the results of research performed on simple rectangular samples. A significant similarity was found in the relationships between the FDM parameters and properties for both sample types.

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Authors and Affiliations

Wiesław Kuczko

1

e-mail:

ORCID:

Adam Hamrol

1

e-mail:

ORCID:

Radosław Wichniarek

1

e-mail:

ORCID:

Filip Górski

1

e-mail:

ORCID:

Michał Rogalewicz

1

e-mail:

ORCID:

Poznan University of Technology, Faculty of Mechanical Engineering, Piotrowo 3, 61-138 Poznan, Poland

28 The measurements of surface defect area with an RGB-D camera for a BIM-backed bridge inspection

Bartosz Wójcik , Mateusz Żarski

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137123 | DOI: 10.24425/bpasts.2021.137123

Keywords: 3D reconstruction RGB-D camera depth sensing bridge inspection as-is BIM

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Abstract

Bridge inspections are a vital part of bridge maintenance and the main information source for Bridge Management Systems is used in decision-making regarding repairs. Without a doubt, both can benefit from the implementation of the Building Information Modelling philosophy. To fully harness the BIM potential in this area, we have to develop tools that will provide inspection accurate information easily and fast. In this paper, we present an example of how such a tool can utilise tablets coupled with the latest generation RGB-D cameras for data acquisition; how these data can be processed to extract the defect surface area and create a 3D representation, and finally embed this information into the BIM model. Additionally, the study of depth sensor accuracy is presented along with surface area accuracy tests and an exemplary inspection of a bridge pillar column.

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Authors and Affiliations

Bartosz Wójcik

1

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ORCID:

Mateusz Żarski

1

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Department of Mechanics and Bridges, Faculty of Civil Engendering, Silesian University of Technology, ul. Akademicka 5, 44-100 Gliwice, Poland

29 Polynomial alignment using general transition curves

Andrzej Kobryń

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137195 | DOI: 10.24425/bpasts.2021.137195

Keywords: road design horizontal alignment general transition curves

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Abstract

This paper presents a new approach to the design methodology of road routes, in literature often referred to as the polynomial alignment. The author proposes the use of the so-called general transition curves that have been described in detail in his earlier research papers. General transition curves employ only one curvature extremum, and the whole curved transition between two extreme points of zero curvature value is described by a single equation. As a result, the curves are very useful for the creation of route geometry in accordance with the principles of polynomial alignment. The paper describes the main concept of polynomial alignment and presents equations of curves which can be used in the proposed alignment procedure. In addition, the paper gives a detailed description of design procedures.

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Authors and Affiliations

Andrzej Kobryń

1

e-mail:

ORCID:

Faculty of Civil Engineering and Environmental Sciences, Bialystok University of Technology, ul. Wiejska 45E, 15-351 Bialystok, Poland

30 Multiparameter reliability model for SiC power MOSFET subjected to repetitive thermomechanical load

Sebastian Bąba

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137386 | DOI: 10.24425/bpasts.2021.137386

Keywords: reliability engineering reliability modelling power MOSFET SiC

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Abstract

The main drawback of any Design for Reliability methodology is lack of easy accessible reliability models, prepared individually for each critical component. In this paper, a reliability model for SiC power MOSFET in SOT – 227 B housing, subjected to power cycling, is presented. Discussion covers preparation of Accelerated Lifetime Test required to develop such reliability model, analysis of semiconductor degradation progress, samples post-failure analysis and identification of reliability model parameters. Such model may be further used for failure prognostics or useful lifetime estimation of High Performance Power Supplies.

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Authors and Affiliations

Sebastian Bąba

1

e-mail:

ORCID:

TRUMPF Huettinger Sp. z o.o., Research and Development Department, 05-220 Zielonka, Poland

31 First vertical-cavity surface-emitting laser made entirely in Poland

Marcin Gębski , Patrycja Śpiewak , Walery Kołkowski , Iwona Pasternak , Weronika Głowadzka , Włodzimierz Nakwaski , Robert P. Sarzała , Michał Wasiak , Tomasz Czyszanowski , Włodzimierz Strupiński

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137272 | DOI: 10.24425/bpasts.2021.137272

Keywords: semiconductor laser GaAs optical communication VCSEL

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Abstract

The paper presents the first vertical-cavity surface-emitting lasers (VCSELs) designed, grown, processed and evaluated entirely in Poland. The lasers emit at »850 nm, which is the most commonly used wavelength for short-reach (<2 km) optical data communication across multiple-mode optical fiber. Our devices present state-of-the-art electrical and optical parameters, e.g. high room-temperature maximum optical powers of over 5 mW, laser emission at heat-sink temperatures up to at least 95°C, low threshold current densities (<10 kA/cm2) and wall-plug efficiencies exceeding 30% VCSELs can also be easily adjusted to reach emission wavelengths of around 780 to 1090 nm.

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Authors and Affiliations

Marcin Gębski

1

e-mail:

ORCID:

Patrycja Śpiewak

1

e-mail:

ORCID:

Walery Kołkowski

2

Iwona Pasternak

2

Weronika Głowadzka

1

Włodzimierz Nakwaski

1

Robert P. Sarzała

1

e-mail:

ORCID:

Michał Wasiak

1

e-mail:

ORCID:

Tomasz Czyszanowski

1

Włodzimierz Strupiński

2

Photonics Group, Institute of Physics, Lodz University of Technology, ul. Wólczańska 219, 90-924 Łódź
Vigo System S.A., ul. Poznańska 129/133, 05-850 Ożarów Mazowiecki

32 Ultrasonic specific absorption rate in nanoparticle-mediated moderate hyperthermia

Barbara Gambin , Eleonora Kruglenko

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137053 | DOI: 10.24425/bpasts.2021.137053

Keywords: ultrasonic hyperthermia agar-based tissue mimicking phantom magnetic nanoparticles temperature specific absorption rate (SAR)

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Abstract

Magnetic nanoparticle’s different applications in nanomedicine, due to their unique physical properties and biocompatibility, were intensively investigated. Recently, Fe₃O₄ nanoparticles, are confirmed to be the best sonosensitizers to enhance the performance of HIFU (high intensity focused ultrasound). They are also used as thermo-sensitizers in magnetic hyperthermia. A new idea of dual, magneto-ultrasound, coupled hyperthermia allows the ultrasound intensity to be reduced from the high to a moderate level. Our goal is to evaluate the enhancement of thermal effects of focused ultrasound of moderate intensity due to the presence of nanoparticles. We combine experimental results with numerical analysis. Experiments are performed on tissue-mimicking materials made of the 5% agar gel and gel samples containing Fe₃O₄ nanoparticles with φ = 100 nm with two fractions of 0.76 and 1.53% w/w. Thermocouples registered curves of temperature rising during heating by focused ultrasound transducer with acoustic powers of the range from 1 to 4 W. The theoretical model of ultrasound-thermal coupling is solved in COMSOL Multiphysics. We compared the changes between the specific absorption rates (SAR) coefficients determined from the experimental and numerical temperature rise curves depending on the nanoparticle fractions and applied acoustic powers.We confirmed that the significant role of nanoparticles in enhancing the thermal effect is qualitatively similarly estimated, based on experimental and numerical results. So that we demonstrated the usefulness of the FEM linear acoustic model in the planning of efficiency of nanoparticle-mediated moderate hyperthermia.

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Authors and Affiliations

Barbara Gambin

1

e-mail:

ORCID:

Eleonora Kruglenko

1

Institute of Fundamental Technological Research, Polish Academy of Sciences, ul. Pawińskiego 5B, 02-106 Warsaw, Poland

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

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Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3

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