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Tytuł:
Wyznaczanie struktur logicznych sieci procesorów o łagodnej degradacji i strukturze 4-wymiarowego hipersześcianu
Determination of logical structures of 4-dimensional hypercube processors network with soft degradation
Autorzy:
Kulesza, R.
Zieliński, Z.
Powiązania:
https://bibliotekanauki.pl/articles/209415.pdf
Data publikacji:
2012
Wydawca:
Wojskowa Akademia Techniczna im. Jarosława Dąbrowskiego
Tematy:
informatyka
diagnostyka systemowa
struktura logiczna sieci
sieci typu sześcian
systemy z tolerancją błędów
informatics
system level diagnosis
network logical structure
hypercube network
fault tolerant systems
Opis:
W artykule rozwinięto metodę generowania struktur logicznych sieci procesorów o łagodnej degradacji typu 4-wymiarowy hipersześcian, zaproponowaną w artykule [8], oraz przedstawiono sposób zastosowania tej metody do wyznaczenia obrazów geometrycznych cyklicznych i acyklicznych struktur roboczych takiej sieci o co najmniej czterech procesorach. Wyznaczono szeregi przeliczające etykietowanych oraz nieetykietowanych struktur roboczych sieci.
In the work, the formal model of the logical structure of a 4-dimensional hypercube processor network and the method of a composition structure were developed based on the method proposed in [8]. The method for determining geometrical form of logical network cyclic and acyclic working structures with the use of operations on the proposed condensed structure form was presented. Counting series for labelled and unlabelled working structures were determined.
Źródło:
Biuletyn Wojskowej Akademii Technicznej; 2012, 61, 4; 293-306
1234-5865
Pojawia się w:
Biuletyn Wojskowej Akademii Technicznej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Współpraca przygranicznych sieci 110 kV - skutecznie uziemionej i skompensowanej
The cooperation of the neighbouring 110 kV networks - solidly grounded and compensated
Autorzy:
Rojewski, W.
Sobierajski, M.
Powiązania:
https://bibliotekanauki.pl/articles/266986.pdf
Data publikacji:
2015
Wydawca:
Politechnika Gdańska. Wydział Elektrotechniki i Automatyki
Tematy:
sieć skompensowana
sieć skutecznie uziemiona
punkt neutralny sieci
zwarcie 1-fazowe
compensated network
solidly grounded network
1-phase to ground fault
Opis:
W pracy rozważane są wybrane problemy współpracy skompensowanej sieci 110 kV z siecią 110 kV skutecznie uziemioną. Zakłada się, że w celu takiej współpracy tworzone będą układy, w których wyizolowany od własnego systemu elektroenergetycznego obszar jednej sieci będzie promieniowo (jednostronnie) zasilany z drugiej sieci, pracującej w tym czasie w układzie normalnym. Wskazuje się na zagrożenia jakie wystąpią w połączonych sieciach podczas zwarć jednofazowych.
Some problems of the cooperation of the compensated 110 kV network and the solidly grounded 110 kV network are discussed in the paper. It is assumed that, in order to prepare such cooperation the special area network, isolated from its power system should be created. And next, this subsystem in a radial configuration will be supplied from the second power system, working at this time at normal conditions. Reference is made to the risks that occur in the interconnected networks when single phase fault.
Źródło:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej; 2015, 42; 85-88
1425-5766
2353-1290
Pojawia się w:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Use of fuzzy fault tree analysis and noisy-OR gate bayesian network for navigational risk assessment in Qingzhou Port
Autorzy:
Zhao, C.
Wu, B.
Yip, T. L.
Lv, J.
Powiązania:
https://bibliotekanauki.pl/articles/2063967.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
risk assessment
Bayesian Network Model
navigational risk
navigational risk assessment
Port of Qingzhou
fuzzy fault tree
noisy-OR gate
navigational accidents
Opis:
Collisions and groundings account for more than 80% among all types of maritime accidents, and risk assessment is an essential step in the formal safety assessment. This paper proposes a method based on fuzzy fault tree analysis and Noisy-OR gate Bayesian network for navigational risk assessment. First, a fault tree model was established with historical data, and the probability of basic events is calculated using fuzzy sets. Then, the Noisy-OR gate is utilized to determine the conditional probability of related nodes and obtain the probability distribution of the consequences in the Bayesian network. Finally, this proposed method is applied to Qinzhou Port. From sensitivity analysis, several predominant influencing factors are identified, including navigational area, ship type and time of the day. The results indicate that the consequence is sensitive to the position where the accidents occurred. Consequently, this paper provides a practical and reasonable method for risk assessment for navigational accidents.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2021, 15, 3; 765--771
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Towards robustness in neural network based fault diagnosis
Autorzy:
Patan, K.
Witczak, M.
Korbicz, J.
Powiązania:
https://bibliotekanauki.pl/articles/929913.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
diagnostyka uszkodzeń
odporność
sieć neuronowa dynamiczna
fault diagnosis
robustness
dynamic neural networks
GMDH neural network
Opis:
Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as neural networks become more and more popular in industrial applications of fault diagnosis. Taking into account the two crucial aspects, i.e., the nonlinear behaviour of the system being diagnosed as well as the robustness of a fault diagnosis scheme with respect to modelling uncertainty, two different neural network based schemes are described and carefully discussed. The final part of the paper presents an illustrative example regarding the modelling and fault diagnosis of a DC motor, which shows the performance of the proposed strategy.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2008, 18, 4; 443-454
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Temporal alarm pattern discovery in mobile telecommunication networks based on binary series analysis
Autorzy:
Mazdziarz, A.
Powiązania:
https://bibliotekanauki.pl/articles/205702.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
mobile telecommunication network
fault diagnosis
root cause analysis
Dice similarity coefficients
Hamming distance
temporal pattern mining
Opis:
Highly-advanced systems, such as mobile telecommunication networks, characterized by increased complexity, make maintenance routines difficult. Amount of data to be analyzed in a short time during fault diagnosis of the mobile telecommunication networks strongly justifies the need to automate alarm correlation and root cause analysis. A major challenge in the establishment of alarm correlation is to determine how to reflect the alarm flow inertia. Thus, adequate temporal alarm pattern discovery methods should be used in fault diagnosis for correlation-related purposes. Automatic temporal alarm pattern discovery allows fast generation of root cause analysis hypotheses and supports effective troubleshooting of network problems. The process for fault propagation throughout the network is manifested by the time lag between the root-cause alarm and potentially linked symptoms, as well as weakening correlation strength with time. The paper presents a novel method for alarm correlation analysis in mobile telecommunication networks, based on binary series analysis. The method allows for discovery of causal relationship between alarms with dynamic alarm correlation window size estimation.
Źródło:
Control and Cybernetics; 2018, 47, 2; 191-213
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
System reliability modeling and assessment for solar array drive assembly based on bayesian networks
Modelowanie i ocena niezawodności systemu w oparciu o sieci bayesowskie na przykładzie układu napędu paneli słonecznych
Autorzy:
Li, Y. F.
Mi, J.
Huang, H. Z.
Xiao, N. C.
Zhu, S. P.
Powiązania:
https://bibliotekanauki.pl/articles/302154.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
drzewo uszkodzeń
dynamiczne drzewo uszkodzeń
sieć bayesowska
niezawodność systemu
układ napędu paneli słonecznych
fault tree
dynamic fault tree
Bayesian network
system reliability
solar array drive assembly
Opis:
Along with the increase of complexity in engineering systems, there exist many dynamic characteristics within the system failure process, such as sequence dependency, functional dependency and spares. Markov-based dynamic fault trees can figure out the modeling of systems with these characteristics. However, when confronted with the issue of state space explosion resulted from the growth of system complexity, the Markov-based approach is no longer efficient. In this paper, we combine the Bayesian networks with the dynamic fault trees to model the reliability of such types of systems. The inference technique of Bayesian network is utilized for reliability assessment and fault probability estimation. The solar array drive assembly is used to demonstrate the effectiveness of this method.
Wraz ze wzrostem złożoności w systemach technicznych, pojawia się wiele charakterystyk dynamicznych w ramach procesu awarii systemu, takich jak zależność sekwencyjna, zależność funkcjonalna czy zabezpieczające elementy zapasowe. Oparte na koncepcjach Markowa dynamiczne drzewa uszkodzeń mogą posłużyć do modelowania systemów z powyższymi charakterystykami. Jednak w konfrontacji z problemem eksplozji stanów wynikającym ze wzrostu złożoności systemu, podejście oparte na teoriach Markowa nie jest już skuteczne. W niniejszej pracy łączymy sieci bayesowskie z dynamicznymi drzewami uszkodzeń w celu modelowania niezawodności tego typu systemów. Technikę wnioskowania sieci bayesowskiej wykorzystano do oceny niezawodności i prawdopodobieństwa wystąpienia uszkodzenia. Skuteczność niniejszej metody wykazano na przykładzie układu napędu paneli słonecznych.
Źródło:
Eksploatacja i Niezawodność; 2013, 15, 2; 117-122
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
System of Signal Injection and Extractioo for Protection and Insulation Monitoring in Medium Voltage Networks
Autorzy:
Kyrychenko, M.
Habrych, M.
Powiązania:
https://bibliotekanauki.pl/articles/410612.pdf
Data publikacji:
2017
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
insulation
distribution network
ground fault
signal injection
Opis:
Simple overcurrent criterion is most often used for detection and elimination of ground faults in radial industrial medium voltage networks. Since in Poland medium voltage networks work with noneffectively grounded neutral point, the ground fault currents can reach very low values, especially under high resistance faults. Such faults cannot be detected by any protection. Therefore, new methods to detect ground faults and to control the insulation in medium voltage network are of great importance. In the paper the idea for monitoring insulation parameters of the system, based on the simultaneous use of two different signals of non-industrial frequency, injected into the controlled network, is presented and discussed.
Źródło:
Present Problems of Power System Control; 2017, 8; 23-30
2084-2201
Pojawia się w:
Present Problems of Power System Control
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Soft Fault Clustering in Analog Electronic Circuits with the Use of Self Organizing Neural Network
Autorzy:
Grzechca, D.
Powiązania:
https://bibliotekanauki.pl/articles/220571.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
fault detection
parametric faults
analogue electronic circuits
self-organizing neural network
Opis:
The paper presents a methodology for parametric fault clustering in analog electronic circuits with the use of a self-organizing artificial neural network. The method proposed here allows fast and efficient circuit diagnosis on the basis of time and/or frequency response which may lead to higher production yield. A self-organizing map (SOM) has been applied in order to cluster all circuit states into possible separate groups. So, it works as a feature selector and classifier. SOM can be fed by raw data (data comes from the time or frequency response) or some pre-processing is done at first. The author proposes conversion of a circuit response with the use of e.g. gradient and differentiation. The main goal of the SOM is to distribute all single faults on a two-dimensional map without state overlapping. The method is aimed for the development stage because the tolerances of elements are not taken into account, however single but parametric faults are considered. Efficiency analyses of fault clustering have been made on several examples e.g. a Sallen-Key BPF and an ECG amplifier. Testing procedure is performed in time and frequency domains for the Sallen-Key BPF with limited number of test points i.e. it is assumed that only input and output pins are available. A similar procedure has been applied to a real ECG amplifier in the frequency domain. Results prove a high efficiency in acceptable time which makes the method very convenient (easy and quick) as a first test in the development stage.
Źródło:
Metrology and Measurement Systems; 2011, 18, 4; 555-568
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Smart Substation Network Fault Classification Based on a Hybrid Optimization Algorithm
Autorzy:
Xia, Xin
Liu, Xiaofeng
Lou, Jichao
Powiązania:
https://bibliotekanauki.pl/articles/227220.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
smart substation
network fault classification
improved separation interval method (ISIM)
support vector
machine (SVM)
Anti-noise processing (ANP)
Opis:
Accurate network fault diagnosis in smart substations is key to strengthening grid security. To solve fault classification problems and enhance classification accuracy, we propose a hybrid optimization algorithm consisting of three parts: anti-noise processing (ANP), an improved separation interval method (ISIM), and a genetic algorithm-particle swarm optimization (GA-PSO) method. ANP cleans out the outliers and noise in the dataset. ISIM uses a support vector machine (SVM) architecture to optimize SVM kernel parameters. Finally, we propose the GA-PSO algorithm, which combines the advantages of both genetic and particle swarm optimization algorithms to optimize the penalty parameter. The experimental results show that our proposed hybrid optimization algorithm enhances the classification accuracy of smart substation network faults and shows stronger performance compared with existing methods.
Źródło:
International Journal of Electronics and Telecommunications; 2019, 65, 4; 657-663
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Rotor fault detector of the converter-fed induction motor based on RBF neural network
Autorzy:
Kowalski, C. T.
Kaminski, M.
Powiązania:
https://bibliotekanauki.pl/articles/200439.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
induction motor
rotor fault
diagnostic symptom
RBF neural network
fault detector
Opis:
This paper deals with the application of the Radial Basis Function (RBF) networks for the induction motor fault detection. The rotor faults are analysed and fault symptoms are described. Next the main stages of the design methodology of the RBF-based neural detectors are described. These networks are trained and tested using measurement data of the stator current (MCSA). The efficiency of developed RBF-NN detectors is evaluated. Furthermore, influence of neural networks complexity and parameters of the RBF activation function on the quality of data classification is shown. The presented neural detectors are tested with measurement data obtained in the laboratory setup containing the converter-fed induction motor (IM) and changeable rotors with a different degree of damages.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2014, 62, 1; 69-76
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Risk analysis of maritime accidents in an estuary: a case study of Shenzhen Waters
Autorzy:
Chen, P.
Mou, J.
Li, Y.
Powiązania:
https://bibliotekanauki.pl/articles/135412.pdf
Data publikacji:
2015
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
maritime accident
risk analysis
Bayesian network
fault tree analysis (FTA)
estuarine waters
maritime safety
Opis:
Due to the unique geographic location, complex navigation environment and intense vessel traffic, a considerable number of maritime accidents occurred in estuarine waters during recent years which caused serious loss of life, property and environmental contamination. Based on the historical data of maritime accidents from 2003 to 2012, which is collected from Shenzhen Maritime Safety Administration, this paper conducted a risk analysis of maritime accidents by applying Bayesian network and fault tree analysis. First a Bayesian network model was introduced to describe the consequence of accidents based on the accident investigation report. Then fault tree analysis was applied to estimate the probability on the basis of accident statistics and ship traffic flow. Finally the risk of maritime accidents in Shenzhen Waters was depicted through the consequence multiplied by the probability of an accident.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2015, 42 (114); 54-62
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Research on big data attribute selection method in submarine optical fiber network fault diagnosis database
Autorzy:
Chen, G.
Powiązania:
https://bibliotekanauki.pl/articles/259788.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
submarine optical fiber network
fault diagnosis database
big data attribute selection
Opis:
At present, in the fault diagnosis database of submarine optical fiber network, the attribute selection of large data is completed by detecting the attributes of the data, the accuracy of large data attribute selection cannot be guaranteed. In this paper, a large data attribute selection method based on support vector machines (SVM) for fault diagnosis database of submarine optical fiber network is proposed. Mining large data in the database of optical fiber network fault diagnosis, and calculate its attribute weight, attribute classification is completed according to attribute weight, so as to complete attribute selection of large data. Experimental results prove that ,the proposed method can improve the accuracy of large data attribute selection in fault diagnosis database of submarine optical fiber network, and has high use value.
Źródło:
Polish Maritime Research; 2017, S 3; 121-127
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Reliability-aware zonotopic tube-based model predictive control of a drinking water network
Autorzy:
Khoury, Boutrous
Nejjari, Fatiha
Puig, Vicenç
Powiązania:
https://bibliotekanauki.pl/articles/2124779.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
fault tolerant control
robust MPC
zonotopes
Bayesian theory
drinking water network
sterowanie tolerujące uszkodzenia
zonotopy
teoria bayesowska
sieć wody pitnej
Opis:
A robust economic model predictive control approach that takes into account the reliability of actuators in a network is presented for the control of a drinking water network in the presence of uncertainties in the forecasted demands required for the predictive control design. The uncertain forecasted demand on the nominal MPC may make the optimization process intractable or, to a lesser extent, degrade the controller performance. Thus, the uncertainty on demand is taken into account and considered unknown but bounded in a zonotopic set. Based on this uncertainty description, a robust MPC is formulated to ensure robust constraint satisfaction, performance, stability as well as recursive feasibility through the formulation of an online tube-based MPC and an accompanying appropriate terminal set. Reliability is then modelled based on Bayesian networks, such that the resulting nonlinear function accommodated in the optimization setup is presented in a pseudo-linear form by means of a linear parameter varying representation, mitigating any additional computational expense thanks to the formulation as a quadratic optimization problem. With the inclusion of a reliability index to the economic dominant cost of the MPC, the network users’ requirements are met whilst ensuring improved reliability, therefore decreasing short and long term operational costs for water utility operators. Capabilities of the designed controller are demonstrated with simulated scenarios on the Barcelona drinking water network.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2022, 32, 2; 197--211
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Phenomena leading to asymmetry of phase–to–earth voltages in MV networks
Autorzy:
Lorenc, J.
Staszak, B.
Powiązania:
https://bibliotekanauki.pl/articles/97461.pdf
Data publikacji:
2016
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
earth faults
MV network
voltage asymmetry
earth fault protection
Opis:
When analysing the earth–fault phenomena, the longitudinal impedance of individual elements is neglected, and the capacitances and conductivities of individual phases to ground are only taken into account. Such a procedure is well–founded for resonant earthed networks and the faults accompanied by a significant resistance at the disturbance’s location (called high–resistance faults). However, in such a case, the possibility of occurrence of voltage differences between the network neutral point and the earth should be considered. The voltage is the effect of natural asymmetry in the network’s phase admittances or in the supply voltages. Level of such a voltage asymmetry significantly affects the flawless of the earth–fault protections and the accurate tuning of Petersen coils in the earth–fault compensation process. In the paper, the results of research work on how different phenomena affect the level of the network phase voltage asymmetry are presented. The investigations have been carried out on the PSCAD software–based MV network model, and investigations take into account the relations between asymmetries in the phase capacitance and conductance of the network as well as the load asymmetry degree in the individual power lines.
Źródło:
Computer Applications in Electrical Engineering; 2016, 14; 158-167
1508-4248
Pojawia się w:
Computer Applications in Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Performance analysis of multi-layered clustering network using fault tolerance multipath routing protocol (MRP-FT) in a wireless sensor network (WSN)
Autorzy:
Kaur, Gagandeep
Powiązania:
https://bibliotekanauki.pl/articles/2204100.pdf
Data publikacji:
2023
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
scalability
fault tolerance
neural networks
Boltzmann learning
wireless sensor network
Opis:
Wireless sensor networks (WSNs) are ad hoc and self-configuring networks having the possibility that any sensor node can connect or leave the network. With no central controller in WSN, wireless sensor nodes are considered responsible for data routing in the networks. The wireless sensor nodes are very small in size and have limited resources, therefore, it becomes difficult to recharge or replace the battery of the sensor nodes at far places. The present study focused on reducing the battery consumption of the sensor nodes by the deployment of the newly proposed Fault Tolerance Multipath Routing Protocol (MRP-FT) as compared with the existing Low Energy Adaptive Clustering Hierarchy (LEACH) protocol under particle swarm optimisation based fault tolerant routing (PSO-FT) technique. The proposed algorithm of MRP-FT-based on the dynamic clustering technique using Boltzmann learning of the neural network and the weights were adjusted according to the area of networks, number of nodes and rounds, the initial energy of nodes (E0), transmission energy of nodes (d
Źródło:
Operations Research and Decisions; 2023, 33, 1; 75--92
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
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