Wyniki wyszukiwania - BazTech

1

Fuzzy logic in risk assessment of production machines failure in forming and assembly processes

Burduk Anna, Lapczynska Dagmara, Kochanska Joanna, Musial Kamil, Husar Jozef

Journal of Machine Engineering

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2024

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Vol. 24, No. 2

34--43

EN

The article presents the application of fuzzy logic to risk assessment in assembly and forming production processes. The fuzzy FMEA method was used, enabling the assessment of risk parameters based on expert opinions. This resulted in the development of a system that allows for greater flexibility and increased resistance to errors associated with human factors, enabling risk assessment through the use of linguistic variables. This allows organisations to analyse and manage risk, improving the efficiency and safety of their operations. This article presents an analysis of the benefits of using fuzzy logic in risk assessment in production in conjunction with the FMEA method, which is one of the most widely used risk assessment methods in industry. It discusses how fuzzy logic can help capture uncertainties in production processes and provide a more flexible framework for their evaluation. A case study is also presented, in which fuzzy logic was applied to risk assessment, highlighting the benefits it brings to production efficiency and safety.

2

Medical fuzzy-expert system for prediction of engraftment degree of dental implants in patients with chronic liver disease

Polishchuk Vitaliy, Pavlov Sergii, Polishchuk Sergii, Shuvalov Sergii, Dalishchuk Andriy, Sachaniuk-Kavets’ka Natalia, Mukhsina Kuralay, Nazerke Abilkaiyr

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

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2024

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T. 14, nr 1

90--94

EN

The paper presents an information technology for assessing the degree of engraftment of dental implants in the event of a pathology violation through the use of fuzzy sets, which allows using this method for medical diagnostic tasks. Main scientific results: developed algorithms and mathematical models that formalize the process supporting diagnostic decisions based on fuzzy logic; developed mathematical models of membership functions that formalize the presentation of qualitative and qualitative informational features based on the rules of fuzzy logic, which can be used in information expert systems when assessing the degree of engraftment of dental implants in case of disease with pathological diseases.

PL

W artykule przedstawiono technologię informacyjną do oceny stopnia wszczepienia implantów stomatologicznych u pacjentów z przewlekłą chorobą wątroby za pomocą zbiorów rozmytych, co pozwala na zastosowanie tej metody do medycznych zadań diagnostycznych. Główne wyniki naukowe: opracowano algorytmy i modele matematyczne formalizujące proces wspomagania podejmowania decyzji diagnostycznych w oparciu o logikę rozmytą; opracowano matematyczne modele funkcji przynależności formalizujące reprezentację ilościowych i jakościowych cech informacyjnych opartych na regułach logiki rozmytej, które mogą być wykorzystane w informatycznych systemach ekspertowych do oceny stopnia wszczepienia implantów stomatologicznych u pacjentów z przewlekłą chorobą wątroby.

3

Fuzzy logic-based prediction data for the CNC lathe

Kunhirunbawon S., Suwichien N., Jantarasricha T., Jantarasricha T., Butdee S.

Archives of Materials Science and Engineering

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2024

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Vol. 126, nr 2

58--64

EN

Purpose: The research aims to predict the parameters between the cutting speed range correlated to the depth of cut for the CNC lathe. Design/methodology/approach: The model predicts the cutting speed parameters carried out based on the data range between the depth of the cut and the cutting speed. That information has been derived from the machine tool handbook and expert engineer recommendations. The fuzzy logic-based methods were used to predict cutting speed parameters for three different materials: aluminium, machine steel, and stainless steel. The data range in each material was used to condition the membership function. Findings: The result shows that the prediction cutting speed parameters are related to the range of the depth of the cut between 0.15 and 0.4 mm. It is observed that if the depth of the cut is very high, the cutting speed is lower. The information obtained is slightly different from the machine tool handbook. It can be used with the feed rate parameters to perform the machining process of the CNC lathes in the smart factory. Research limitations/implications: Further research should focus on predicting surface roughness and tool wear in the turning. Practical implications: The cutting speed selection has a significant impact on manufacturing. It affects production time, tool wear, cost, etc. Generally, the parameter has been derived from machining handbooks or machine tools textbooks, and some data is vague because it has only maximum and minimum. The data between ranges is unclear for operation. Executing production planning for new engineers was hard, which can affect manufacturing systems. Therefore, proper and precise cutting parameters are required. Originality/value: General machine tool manuals often provide vague information on recommended parameters and only show the maximum and minimum values. In past research, it has only a determined parameters range for the experiment. The data between ranges is unclear for operation. In this research, the parameter prediction was performed between the cutting speed range related to the cutting depth, which is for use in the CNC lathe process.

4

A fuzzy logic modelling of predictive maintenance in rotating machinery

Prommachan W., Surin P., Srinoi P., Pipathattakul M.

Archives of Materials Science and Engineering

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2024

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Vol. 126, nr 1

15--22

EN

Purpose: The study aims to investigate and assess the application of Fuzzy Logic to construct a predictive maintenance model for rotating machinery. Design/methodology/approach: The research uses a mixed approach, with both quantitative and qualitative approaches, and are four main steps: 1) surveying and analysing existing predictive maintenance techniques; 2) determining appropriate expert assessment criteria for predictive maintenance techniques; 3) vibration analysis by the experts; 4) evaluate the performance of rotating machinery with fuzzy logic. Findings: The result of the study will be used to build a rotating machinery predictive maintenance model, which is very similar to the traditional method. The obtained data showed that the efficiency of the rotating machinery and the vibration level were compliant with the standard ISO 10816-3. Thus, such data can be planned for maintenance to maximize benefit. Research limitations/implications: Future research should optimise the model and add additional modules for automatic data collection. The production monitoring system should help collect data by considering downtime, predicting the functional service life of rotating machinery, etc. Practical implications: The proposed model can be used in small water pumps in order to perform predictive maintenance. The conceptual framework was tested, particularly with rotating machinery. Originality/value: The fuzzy logic model is described as the fuzzy of a process with linguistics for greater clarity.

5

Evaluation of some thermophysical properties of sn500 lubrication oil blended with SIO2, AL2O3 and TIO2 nano-additives, using fuzzy logic

Sankar E., Duraivelu K.

Acta Mechanica et Automatica

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2024

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Vol. 18, no. 2

352--360

EN

Nano-additives are generally blended with the base lubricant oil, to enhance the lubricant characteristics such as wear, coefficient of friction (CoF), thermal conductivity, density, and flash and fire points of the lubricant. In this research, nano-additives of SiO2, Al2O3 and TiO2 are blended with the base SN500 oil with different proportions of mixture. When these three nanoparticles are used together in base oil, they enhance most of the desirable properties of a lubricant; 27 samples with three different levels of a mixture of nano-additives are identified using factorial design of experiments. The experimental outcomes for the selected three characteristics of interest of density, flash point and fire point are determined. Conducting experiments for ‘n’ number of samples with different proportions of mixture of nano-additives is a cumbersome, expensive and time-consuming process, in order to determine the optimum mix of nano-additives for the desirable level of characteristics of interest. In this research, attempt has been made to apply fuzzy logic to simulate a greater number of samples with different proportions of a mixture of three nano-additives with the respective outcomes of characteristics of three thermophysical properties. Out of the numerous samples simulated using fuzzy logic, the sample with the optimum mix of three nano-additives of SiO2, Al2O3 and TiO2 blended with the base oil is identified for the desirable level of characteristics of interest of density, flash point and fire point. The values of the identified sample are found to be at the desirable level of 0.9008 gm/ml, 231C and 252C, respectively.

6

Modern method based on artificial intelligence for safe control in the marine environment

Mohamed-Seghir Gdynia Maritime University, Gdynia, Poland

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2023

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Vol. 17 No. 2

283--288

EN

The article presents an approach to formulating a ship control process model in order to solve the problem of determining a safe ship trajectory in collision situations. Fuzzy process properties are included in the model to bring it closer to reality, as in many situations the navigator makes a subjective decision. A special neural network was used to solve the presented problem. This artificial neural network is characterized by minimum and maximum operations when set. In order to confirm the correctness of the operation of the proposed algorithm, the results of the simulations obtained were presented and an discussion was conducted.

7

Analysis and evaluation of the technical equipment maintenance system in the Polish Army

Pszczółkowski Józef, Goliasz Tomasz

Systemy Logistyczne Wojsk

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2023

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Vol. 59, no. 2

73--103

EN

Maintaining the high level of operational readiness of the army requires ensuring constant high technical readiness of its technical equipment. The reliability of a technical device results from its design and operational features, and in the operation phase it depends solely on the efficiency of the logistics supply system, service, and diagnosis. The principles of implementing these processes and the functioning of the systems are determined by the adopted equipment exploitation strategy. The study presents the results of the assessment of the technical equipment maintenance system in the Polish Army. Methods, procedures and tools for obtaining data to achieve the set goal, methods of data processing, and analysis of the obtained information were characterized. Information and data characterizing the functioning of the maintenance system were obtained as a result of the use of interview techniques with experts with theoretical and practical knowledge about the functioning of the system in the armed forces, using observation techniques, analysis of operational documentation in paper form as well as collected in IT systems. The method of surveying of two groups of experts, participants of the logistics course involved in the implementation and managing the operation of the equipment was of fundamental importance in the research process. IT tools such as MS Excel, MatLab and Statistica were used to develop the obtained numerical and linguistic results. The study determined the parameters of descriptive statistics, histograms and probability distributions and used fuzzy logic. As a result of the study, the reasons for the currently not fully satisfactory level of operation of the equipment maintenance system were revealed and possible solutions were identified to increase the efficiency and effectiveness of the system, and thus the technical readiness of the equipment.

PL

Utrzymanie wysokiego poziomu gotowości operacyjnej wojska wymaga zapewnienia stałej wysokiej gotowości technicznej sprzętu stanowiącego jego wyposażenie. Niezawodność urządzenia technicznego wynika z jego cech konstrukcyjnych i eksploatacyjnych, a w fazie eksploatacji jest zależna wyłącznie od sprawności działania systemu zaopatrzenia logistycznego, obsługiwania, w tym diagnozowania. Zasady realizacji tych procesów i funkcjonowania systemów determinuje przyjęta strategia eksploatacji sprzętu. W opracowaniu przedstawiono wyniki oceny funkcjonowania systemu obsługiwania sprzętu technicznego w wojsku polskim. Scharakteryzowano metody, procedury i narzędzia pozyskiwania danych dla realizacji postawionego celu, metody przetwarzania i opracowania danych oraz analizy uzyskanej informacji. Informacje i dane charakteryzujące funkcjonowanie systemu obsługiwania uzyskano w wyniku zastosowania techniki wywiadu z ekspertami dysponującymi wiedzą teoretyczną jak i praktyczną o funkcjonowaniu systemu w siłach zbrojnych, za pomocą techniki obserwacji, analizy dokumentacji eksploatacyjnej w formie papierowej, jak również zgromadzonej w systemach informatycznych. Podstawowe znaczenie w procesie badawczym miała metoda ankietowania dwóch grup ekspertów, uczestników kursu logistycznego związanych z realizacją i zarządzających eksploatacją sprzętu. Do opracowania uzyskanych wyników liczbowych i lingwistycznych wykorzystano narzędzia informatyczne w postaci MS Excel, MatLab i Statistica. W opracowaniu wyznaczono parametry statystyki opisowej, histogramy i rozkłady prawdopodobieństwa oraz wykorzystano logikę rozmytą. W wyniku przeprowadzonego badania ujawniono przyczyny aktualnie nie w pełni zadowalającego poziomu funkcjonowania systemu utrzymania stanu technicznego sprzętu oraz wskazano możliwe do zastosowania rozwiązania pozwalające na podniesienie sprawności i efektywności systemu, a tym samym gotowości technicznej sprzętu.

8

Dynamic voltage restorer for voltage unbalance mitigation and voltage profile improvement in distribution network

Al-Karakchi Ahmed A. Abdullah, Albanna Enaam, Al-Rifaie Alya Hamid

Przegląd Elektrotechniczny

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2023

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R. 99, nr 6

188--191

EN

Unbalanced network voltage damages utility and end-user equipment. Electrified trains, single-phase distributed generators, and line-toline connected industrial loads can increase voltage imbalances. Using Dynamic Voltage Restorer (DVR) at appropriate places is one way to reduce imbalance in practical networks. This research proposes a new technique for managing DVR to improve voltage profile. The simulation results imply that real-time implementation of the suggested controller is practical and resilient.

PL

Niezrównoważone napięcie sieciowe uszkadza sprzęt komunalny i użytkownika końcowego. Zelektryfikowane pociągi, jednofazowe rozproszone generatory i obciążenia przemysłowe połączone między liniami mogą zwiększać nierównowagę napięcia. Używanie dynamicznego przywracania napięcia (DVR) w odpowiednich miejscach jest jednym ze sposobów zmniejszenia asymetrii w praktycznych sieciach. Badanie to proponuje nową technikę zarządzania DVR w celu poprawy profilu napięcia. Wyniki symulacji sugerują, że implementacja sugerowanego kontrolera w czasie rzeczywistym jest praktyczna i odporna.

9

ANFIS based inverse controller design for liquid level control of a spherical tank

Akca Talha Burak, Ulu Cenk, Obut Salih

Przegląd Elektrotechniczny

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2023

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R. 99, nr 2

32--36

EN

In this study, an adaptive neuro fuzzy inference system (ANFIS) based inverse controller design is presented for liquid level control application of a spherical tank. First, an excitation signal is applied to the system and the corresponding output signal is obtained. ANFIS-based fuzzy model of the nonlinear spherical tank system is constructed by using this input-output data set. While constructing the fuzzy model, a fuzzy model structure with two inputs and one output is preferred considering design simplicity. The input-output data used for constructing the fuzzy model of the system are exchanged, and by using this new data set, an ANFIS based inverse controller is designed. To improve the control performance against disturbances and model mismatches, the inverse controller is used in an internal model control structure. The performance of the proposed controller is compared to that of classical PI and fuzzy PI controllers under set point variation and disturbance conditions. The results of comparisons reveal that the proposed inverse controller outperforms both the classical and fuzzy PI controllers.

PL

W niniejszym opracowaniu przedstawiono projekt regulatora odwrotnego opartego na adaptacyjnym neurorozmytym systemie wnioskowania (ANFIS) do zastosowania w kontroli poziomu cieczy w zbiorniku kulistym. Najpierw do systemu doprowadzany jest sygnał wzbudzenia i uzyskiwany jest odpowiedni sygnał wyjściowy. Oparty na ANFIS model rozmyty nieliniowego systemu zbiorników sferycznych jest tworzony przy użyciu tego zestawu danych wejściowych i wyjściowych. Podczas konstruowania modelu rozmytego preferowana jest struktura modelu rozmytego z dwoma danymi wejściowymi i jednym wynikiem, biorąc pod uwagę prostotę projektowania. Dane wejściowe-wyjściowe wykorzystywane do budowy modelu rozmytego systemu są wymieniane, a przy użyciu tego nowego zestawu danych projektowany jest sterownik odwrotny oparty na ANFIS. W celu poprawy wydajności sterowania w przypadku zakłóceń i niezgodności modelu, w wewnętrznej strukturze sterowania modelu zastosowano regulator odwrotny. Wydajność proponowanego regulatora jest porównywana z klasycznymi regulatorami PI i rozmytymi regulatorami PI w warunkach zmienności wartości zadanej i zakłóceń. Wyniki porównań pokazują, że proponowany regulator odwrotny przewyższa zarówno klasyczne, jak i rozmyte regulatory PI.

10

Optimal State Estimation via Adaptive Fuzzy Particle Filter

Sąsiadek Jurek, Bitlmal Hamdan Alatresh

Pomiary Automatyka Robotyka

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2023

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R. 27, nr 4

5--12

EN

Particle Filters (PF) accomplish nonlinear system estimation and have received high interest from numerous engineering domains over the past decade. The main problem of PF is to degenerate over time due to the loss of particle diversity. One of the essential causes of losing particle diversity is sample impoverishment (most of particle’s weights are insignificant) which affects the result from the particle depletion in the resampling stage and unsuitable prior information of process and measurement noise. To address this problem, a new Adaptive Fuzzy Particle Filter (AFPF) is used to improve the precision and efficiency of the state estimation results. The error in AFPF state is avoided from diverging by using Fuzzy logic. This method is called tuning weighting factor (α) as output membership function of fuzzy logic and input memberships function is the mean and the covariance of residual error. When the motion model is noisier than measurement, the performance of the proposed method (AFPF) is compared with the standard method (PF) at various particles number. The performance of the proposed method can be compared by keeping the noise level acceptable and convergence of the particle will be measured by the standard deviation. The simulation experiment findings are discussed and evaluated.

PL

Adaptacyjny filtr cząstek rozmytych (AFPF) służy do poprawy precyzji i wydajności wyników szacowania stanu. Metoda ta nazywana jest dostrajaniem współczynnika ważenia (α), ponieważ wyjściowa funkcja przynależności logiki rozmytej, a wejściowa funkcja przynależności jest średnią i kowariancją błędu resztowego. Wydajność proponowanej metody jest porównywana przez utrzymanie dopuszczalnego poziomu hałasu, a zbieżność cząstki będzie mierzona przez odchylenie standardowe. Wyniki eksperymentu symulacyjnego są omawiane i oceniane.

11

Forecasting the Flow Coefficient of the River Basin Using Adaptive Fuzzy Inference System and Fuzzy SMRGT Method

Gunal Ayse Yeter, Mehdi Ruya

Journal of Ecological Engineering

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2023

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Vol. 24, nr 7

96--107

EN

In hydrology and water resources engineering, predicting the flow coefficient is a crucial task that helps estimate the precipitation resulting in a surface flow. Accurate flow coefficient prediction is essential for efficient water management, flood control strategy development, and water resource planning. This investigation calculated the flow coefficient using models based on Simple Membership functions and fuzzy Rules Generation Technique (SMRGT) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) model. The fuzzy logic methods are used to model the intricate connections between the inputs and the output. Statistical parameters such as the coefficient of determination (R2), the root mean square error (RMSE), the mean absolute error (MAE), and the mean absolute percentage error (MAPE) were used to evaluate the performance of models. The statistical tests outcome for the SMRGT model was (RMSE:0.056, MAE:1.92, MAPE:6.88, R2:0.996), and for the ANFIS was (RMSE:0.96, MAE:2.703, MAPE:19.97, R2:0.8038). According to the findings, the SMRGT, a physics-based model, exhibited superior accuracy and reliability in predicting the flow coefficient compared to ANFIS. This is attributed to the SMRGT’s ability to integrate expert knowledge and domain-specific information, rendering it a viable solution for diverse issues.

12

Information technology for comprehensive monitoring and control of the microclimate in industrial greenhouses based on fuzzy logic

Laktionov Ivan, Vovna Oleksandr, Kabanets Maryna

Journal of Artificial Intelligence and Soft Computing Research

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2023

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Vol. 13, No. 1

19--35

EN

Nowadays, applied computer-oriented and information digitalization technologies are developing very dynamically and are widely used in various industries. One of the highest priority sectors of the economy of Ukraine and other countries around the world, the needs of which require intensive implementation of high-performance information technologies, is agriculture. The purpose of the article is to synthesise scientific and practical provisions to improve the information technology of the comprehensive monitoring and control of microclimate in industrial greenhouses. The object of research is nonstationary processes of aggregation and transformation of measurement data on soil and climatic conditions of the greenhouse microclimate. The subject of research is methods and models of computer-oriented analysis of measurement data on the soil and climatic state of the greenhouse microclimate. The main scientific and practical effect of the article is the development of the theory of intelligent information technologies for monitoring and control of greenhouse microclimate through the development of methods and models of distributed aggregation and intellectualised transformation of measurement data based on fuzzy logic.

13

K-Means and Fuzzy based Hybrid Clustering Algorithm for WSN

Angadi Basavaraj M., Kakkasageri Mahabaleshwar S.

International Journal of Electronics and Telecommunications

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2023

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Vol. 69, No. 4

793--801

EN

Wireless Sensor Networks (WSN) acquired a lot of attention due to their widespread use in monitoring hostile environments, critical surveillance and security applications. In these applications, usage of wireless terminals also has grown significantly. Grouping of Sensor Nodes (SN) is called clustering and these sensor nodes are burdened by the exchange of messages caused due to successive and recurring re-clustering, which results in power loss. Since most of the SNs are fitted with nonrechargeable batteries, currently researchers have been concentrating their efforts on enhancing the longevity of these nodes. For battery constrained WSN concerns, the clustering mechanism has emerged as a desirable subject since it is predominantly good at conserving the resources especially energy for network activities. This proposed work addresses the problem of load balancing and Cluster Head (CH) selection in cluster with minimum energy expenditure. So here, we propose hybrid method in which cluster formation is done using unsupervised machine learning based kmeans algorithm and Fuzzy-logic approach for CH selection.

14

Ventilation control of the new safe confinement of the Chornobylnuclear power plant based on neuro-fuzzy networks

Loboda Petro, Starovit Ivan S., Shushura Oleksii M, Havrylko Yevhen V., Saveliev Maxim V., Sachaniuk-Kavets’ka Natalia, Neprytskyi Oleksandr, Oralbekova Dina, Mussayeva Dinara

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

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2023

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T. 13, nr 4

114--118

EN

The accident at the Chornobyl Nuclear Power Plant (ChNPP) in Ukraine in 1986 became one of the largest technological disasters in human history. During the accident cleanup, a special protective structure called the Shelter Object was built to isolate the destroyed reactor from the environment. However, the planned operational lifespan of the Shelter Object was only 30 years. Therefore, with the assistance of the international community, a new protective structure called the New Safe Confinement (NSC) was constructed and put into operation in 2019. The NSC is a large and complex system that relies on a significant number of various tools and subsystems to function. Due to temperature fluctuations and the influence of wind, hydraulic processes occur within the NSC, which can lead to the release of radioactive aerosols into the environment. The personnel of the NSC prevents these leaks, including through ventilation management. Considering the long planned operational term of the NSC, the development and improvement of information technologies for its process automation is a relevant task. The purpose of this paper is to develop a method for managing the ventilation system of the NSC based on neuro-fuzzy networks. An investigation of the current state of ventilation control in the NSC has been conducted, and automation tools for the process have been proposed. Using an adaptive neuro-fuzzy inference system (ANFIS) and statistical data on the NSC's operation, neuro-fuzzy models have been formed, which allows to calculate the expenses of the ventilation system using the Takagi-Sugeno method. The verification of the proposed approaches on a test data sample demonstrated sufficiently high accuracy of the calculations, confirming the potential practical utility in decision-making regarding NSC’s ventilation management. The results of this paper can be useful in the development of digital twins of the NSC for process management and personnel training.

PL

Awaria w Czarnobylskiej Elektrowni Jądrowej (ChNPP), która miała miejsce w Ukrainie w 1986 roku, stała się jedną z największych katastrof technologicznych w historii ludzkości. Podczas likwidacji awarii zbudowano specjalną strukturę ochronną – Obiekt "Ukrycie", mającą na celu izolację zniszczonego reaktora od otoczenia. Jednak planowany okres eksploatacji sarkofagu "Ukrycie" wynosił tylko 30 lat, dlatego przy wsparciu społeczności międzynarodowej zbudowano nową strukturę ochronną – "Nowa Bezpieczna Powłoka" (NSC), która została oddana do użytku w 2019 roku. NSC jest dużym i skomplikowanym systemem, którego funkcjonowanie zapewnia znaczna liczba różnych narzędzi i podsystemów. Ze względu na zmienne temperatury i wpływ wiatru, w NSC zachodzą procesy hydrauliczne, które mogą prowadzić do uwolnienia promieniotwórczych aerozoli do otoczenia. Personel NSC zapobiega tym wyciekom, między innymi poprzez zarządzanie wentylacją. W związku z długim planowanym okresem eksploatacji NSC, istotnym zadaniem jest rozwój i doskonalenie technologii informatycznych dla automatyzacji procesów. Celem pracy jest opracowanie metody zarządzania systemem wentylacji NSC opartej na rozmytych sieciach neuronowych. Przeprowadzono badania istniejącego stanu rozwiązywania problemów zarządzania wentylacją NSC oraz wybrano narzędzia do automatyzacji procesu. Za pomocą adaptacyjnego systemu wnioskowania neuro-rozmytego (ANFIS) i danych statystycznych dotyczących funkcjonowania NSC, stworzono modele neuro-rozmyte, które pozwalają na kalkulację kosztów systemu wentylacyjnego metodą Takagi-Sugeno. Weryfikacja zaproponowanych podejść na próbce kontrolnej danych wykazała wystarczająco wysoką dokładność obliczeń, co potwierdza możliwość ich praktycznego zastosowania w procesie podejmowania decyzji dotyczących zarządzania wentylacją NSC. Wyniki pracy mogą być również przydatne przy tworzeniu cyfrowe bliźniaków NSC w celu zarządzania procesami i szkolenia personelu.

15

Analiza ryzyka w ocenie jakości betonu towarowego, z wykorzystaniem logiki rozmytej

Skrzypczak Izabela, Zięba Joanna

Cement Wapno Beton

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2023

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R. 28, nr 1

26--39

PL

Decyzja o zaliczeniu rozpatrywanej partii betonu do projektowanej klasy, zależy od spełnienia warunków dotyczących wytrzymałości - każdego wyniku i wartości średniej. Kryteria zgodności betonu zostały opisane w normie PN-EN 206+A1:2016. Rozpatrując ryzyko w ocenie jakości betonu można przyjąć, że w tej ocenie występują trzy poziomy wyniku: mały, średni i duży. Wykorzystując operacje logiczne na zbiorach rozmytych, można ustalać reguły wnioskowania, w celu ustalenia zależności między różnymi zmiennymi. W pracy przedstawiono analizę ryzyka produkowanego betonu, przeprowadzoną dla dwóch parametrów wejściowych, dotyczących średniej wytrzymałości betonu na ściskanie oraz usterek, uzyskanych podczas sprawdzania zgodności ocenianych właściwości, z prawdopodobieństwem ich wystąpienia. Trzecim czynnikiem, jako konsekwencji wystąpienia tych właściwości, będzie sprawdzenie wytrzymałości na ściskanie, produkowanego betonu. W przypadku oceny wytrzymałości betonu na ściskanie, w oparciu o trzy wyniki n = 3, uzyskanej średniej 28 MPa przed i po kontroli, zgodności określonej na poziomie średnich właściwości, ryzyko dotyczące prawidłowej oceny jakości produkowanego betonu, jest średnie.

EN

The decision to include the considered batch of concrete in the designed class depends on the satisfaction of the conditions imposed on the strength of each individual result and the average value. The concrete conformity criteria are formulated in EN 206+A1:2016. When considering risk in concrete quality assessment, it can be assumed that there are three levels of result: low, medium, and high risk in quality assessment. Using logical operations on fuzzy sets, inference rules can be constructed to establish relationships between different variables. The paper presents an analysis of the risk of produced concrete carried out for two input parameters. Parameters on the average compressive strength of concrete and online defects obtained during compliance checks. Defects are identified by the probability of their occurrence. The third parameter introduced relates to the consequences of the occurrence of events identified with the obtained defectiveness after the compliance check of the compressive strength of the concrete produced. When verifying the compressive strength of concrete based on a sample size of n = 3, with the result obtained of a mean value of 28 MPa and a defect before and after conformity control defined at the medium defectiveness, the risk regarding the correct assessment of the quality of the produced concrete is medium.

16

The Application of Fuzzy Logic Analysis for the Fast Calculations of Proper Parameters of Manufacturing Titanium Alloys from Powders

Zyguła Krystian, Wojtaszek Marek

Archives of Metallurgy and Materials

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2023

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Vol. 68, iss. 2

703--710

EN

This paper presents a method based on the use of fuzzy logic for the rapid selection of optimal induction sintering parameters. The prepared fuzzy controller uses expert knowledge developed from the results of induction sintering tests of Ti-5Al-5Mo-5V-3Cr alloy green compacts produced from a mixture of elemental powders. The analysis of the influence of the applied sintering parameters on the material characteristics was based on the evaluation of the microstructure state and the measurement of the relative density of the samples after sintering. In this way, a universal tool for estimating the sintering parameters of titanium powder-based green compacts was obtained. It was shown that with the help of fuzzy logic it is possible to analyze the influence of the parameters of the manufacturing process of metal powder materials on the quality of the obtained products.

17

A new method of decision making in multi-objective optimal placement and sizing of distributed generators in the smart grid

Khoshayand Hossein Ali, Wattanapongsakorn Naruemon, Mahdavian Mehdi, Ganji Ehsan

Archives of Electrical Engineering

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2023

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Vol. 72, nr 1

253--271

EN

One of the most important aims of the sizing and allocation of distributed generators (DGs) in power systems is to achieve the highest feasible efficiency and performance by using the least number of DGs. Considering the use of two DGs in comparison to a single DG significantly increases the degree of freedom in designing the power system. In this paper, the optimal placement and sizing of two DGs in the standard IEEE 33-bus network have been investigated with three objective functions which are the reduction of network losses, the improvement of voltage profiles, and cost reduction. In this way, by using the backward-forward load distribution, the load distribution is performed on the 33-bus network with the power summation method to obtain the total system losses and the average bus voltage. Then, using the iterative search algorithm and considering problem constraints, placement and sizing are done for two DGs to obtain all the possible answers and next, among these answers three answers are extracted as the best answers through three methods of fuzzy logic, the weighted sum, and the shortest distance from the origin. Also, using the multi-objective non-dominated sorting genetic algorithm II (NSGA-II) and setting the algorithm parameters, thirty-six Pareto fronts are obtained and from each Pareto front, with the help of three methods of fuzzy logic, weighted sum, and the shortest distance from the origin, three answers are extracted as the best answers. Finally, the answer which shows the least difference among the responses of the iterative search algorithm is selected as the best answer. The simulation results verify the performance and efficiency of the proposed method.

18

Assessment of the technical condition of heritage buildings with the use of fuzzy logic

Lendo-Siwicka Marzena, Trach Roman, Pawluk Katarzyna, Wrzesiński Grzegorz, Żochowska Ada

Archives of Civil Engineering

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2023

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Vol. 69, nr 2

123--140

EN

Construction objects must be protected not only at the stage of their construction, but also during exploitation. Particular attention should be paid to objects included in the list of monuments. The Act on the Protection of Monuments and the Guardianship of Monuments states that any building that is important for history and science can become a heritage building and should therefore be preserved. The aim of this article was to improve the method of visual assessment of the technical condition of heritage buildings with the use of fuzzy logic. The improved method is to facilitate the comparison of assessments of the technical condition of a building performed at intervals specified in the regulations, often by different people. The research was conducted on the basis of technical expertise prepared for five examined buildings that were tenement houses entered in the register of monuments. The use of the visual method provides for the assessment of individual elements of the object by an expert and a verbal description of the elements using a five-point scale. A significant limitation of this method is uncertainty associated with the exact ranges of the acceptable values, as these ranges are subjective and depend on the opinion of an evaluator. The impact of this limitation can be reduced by applying fuzzy logic. In the fuzzy logic model, as input variables the following were applied; assessments of the technical condition of individual elements of the object (underground structure, load-bearing walls, ceilings, roof, other elements) and an integral indicator of the technical condition of the entire historic object, calculated as the output value.

PL

Obiekty budowlane trzeba chronić nie tylko na etapie ich powstawania, ale także podczas eksploatacji. Szczególną uwagę należy zwrócić na obiekty wpisane na listę zabytków. Ustawa o ochronie zabytków i opiece nad zabytkami podaje, iż zabytkiem stać się może każdy budynek, który ma znaczenie dla historii i nauki, przez co powinien być zachowany. Celem niniejszego artykułu było udoskonalenie metody wizualnej oceny stanu technicznego obiektów zabytkowych z wykorzystaniem logiki rozmytej. Udoskonalona metoda ma ułatwić porównanie ocen stanu technicznego budynku wykonywanych w określonych w przepisach odstępach czasu, często przez rożne osoby. Badanie przeprowadzano na podstawie ekspertyz technicznych sporządzonych dla pięciu badanych obiektów będących kamienicami wpisanymi do rejestru zabytków. Stosowanie metody wizualnej przewiduje ocenę poszczególnych elementów obiektu przez eksperta i werbalny opis elementów przy użyciu pięciostopniowej skali. Istotnym ograniczeniem metody wizualnej jest niepewność związana z dokładnymi zakresami dopuszczalnych wartości, ponieważ przedziały te są subiektywne i zależą od opinii oceniającej osoby. Wpływ tego ograniczenia można zmniejszyć za pomocą stosowania logiki rozmytej (Fuzzy Logic). W modelu logiki rozmytej jako zmienne wejściowe wykorzystano oceny stanu technicznego poszczególnych elementów obiektu (konstrukcja podziemna, ściany nośne, stropy, dach, inne elementy) i integralny wskaźnik stanu technicznego całego obiektu zabytkowego obliczony jako wartość wyjściowa.

19

Enhancing the efficiency of the Levenshtein distance-based heuristic method of arranging 2D apictorial elements for industrial applications

Skulimowski Stanisław, Montusiewicz Jerzy, Badurowicz Marcin

Applied Computer Science

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2023

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Vol. 19, no 4

1--13

EN

The article addresses the challenge of reconstructing 2D broken pictorial objects by automating the search for matching elements, which is particularly relevant in fields like archaeology and forensic science. The authors propose a method to match such elements and streamline the search process by detecting and filtering out low quality matches. The study delves into optimizing the search process in terms of duration and assembly quality. It examines factors like comparison window length, Levenshtein measure margin, and number of variants to check, using theoretical calculations and experiments on synthetic elements. The experimental results demonstrate enhanced method effectiveness, yielding more useful solutions and significantly reducing the complexity of element comparisons by up to 100 times in extreme cases.

20

Using Fuzzy Logic to Make Decisions Based on the Data From Customer Relationship Management Systems

Bojanowska Agnieszka Barbara, Kulisz Monika

Advances in Science and Technology. Research Journal

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2023

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Vol. 17, no 5

270--279

EN

The purpose of the article is to propose a fuzzy logic solution for decision-making based on data from CRM (Customer Relationship Management) systems to evaluate banking customer attractiveness. The article is based on theory about management IT systems, especially the CRM type. Based on the literature research, nine identified factors were proposed that can influence whether the relationship with the customer will be profitable for the bank. Factors that affect banking customer attractiveness are considered, including the share of the customer's wallet and the customer's tendency to express a positive opinion of the bank. Data allowing for the identification of these factors is collected in the bank's IT systems, among other CRMs. Based on the research, a model prepared in Simulink using a Mamdani-type Fuzzy Inference System was made. It is a decision model that provides a result in the form of a binary value of 0 or 1, where 1 means it is worth investing in a customer, while 0 means it is not. After considering the subjective opinions, competence and experience of specialists and confronting them with the results from the developed model, it can be confirmed that the model works as expected.