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1
Content available remote Global sensitivity analysis of multi-state markov reliability models of power equipment approximated by polynomial chaos expansion
Rocco C. M., Zio E.
Journal of KONBiN
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2012
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No. 3 (23)
59--70
EN
Reliability and availability of electric power system equipment (e.g., generator units, transformers) are often evaluated by defining and solving Markov models. Transition rates among the identified equipment states are estimated from experimental and field data, or expert judgment, with inevitable uncertainty. For model understanding and to guide validation and confidence building, it is of interest to investigate the effects of the uncertainty in the input transition rates on the output reliability and availability. To this aim, Global Sensitivity Analysis (GSA) can be used for defining importance (sensitivity) indexes that allow a ranking of the transition rates with respect to their influence on the uncertainty in the output. In general, GSA requires a large number of model evaluations. In this paper, a metamodel is defined to estimate the performance index of interest (e.g. reliability or availability). The metamodel is built based on polynomial chaos expansion (PCE), a multidimensional polynomial model approximation whose coefficients are determined by evaluating the model in a reduced set of predetermined values of the input. The proposed approach is illustrated on a power generating unit.
PL
Niezawodność i gotowość urządzeń elektroenergetycznych jest często oceniana poprzez definiowanie i rozwiązywanie modeli łańcuchów Markowa. Współczynniki prawdopodobieństwa przejścia pomiędzy zdefiniowanymi stanami urządzeń są oceniane na podstawie badań doświadczalnych i danych otrzymanych dla realnych systemów lub są przedmiotem oceny ekspertów. W celu zrozumienia istoty modelu, kierowania procesem jego walidacji oraz budowania zaufania należy się zainteresować zbadaniem wpływu niepewności w określeniu wejściowych współczynników przejścia w modelu Markowa na uzyskiwane wyjściowe wartości niezawodności i gotowości. W tym celu został zdefiniowany metamodel pozwalający na określenie współczynników wpływu na parametry eksploatacyjne (np. niezawodność czy gotowość). Ten metamodel został zbudowany w oparciu o rozwinięcie w chaos wielomianowy, wielowymiarowy modelu aproksymacji wielomianowej, gdzie współczynniki modelu są określane poprzez ewaluację modelu dla zredukowanego zbioru predefiniowanych wartości wejściowych. Zaproponowany sposób jest zilustrowany na przykładzie bloku elektroenergetycznego.
2
Content available Performance analysis of a power transmission system under uncertain load conditions and network configurations
Zio E., Piccinelli R., Delfanti M., Olivieri V., Pozzi M.
Journal of Polish Safety and Reliability Association
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2010
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Vol. 1, No. 1
279--284
EN
In this paper, the load flow problem in a power transmission network is studied in presence of load and Power generation uncertainties and transmission lines failures. Network performance indicators are computed and the importance of the different components is evaluated by a power flow betwenness centrality measure.
3
Content available Monte Carlo simulation-based reliability model for the PSA of a radioactive waste repository
Cadini F., Avram D., Zio E., Luce A., Taglioni A.
Journal of Polish Safety and Reliability Association
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2010
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Vol. 1, No. 1
43--50
EN
Disposal facilities for radioactive wastes comprise a series of engineered barriers whose purpose is to contain the radionuclides until their radiation hazard has decreased to acceptable levels. In this regard, it is required that the long-term functionality of the system of barriers be evaluated by a quantitative risk analysis procedure, also called performance assessment. In this paper, a Monte Carlo simulation-based reliability model is propounded for the preliminary analysis of the safety performance of a radioactive waste repository, accounting also for barrier degradation processes. The model strengths are: simplicity, chich allows ease of computation, and flexibility, which allows modification to account for various physical aspects and inter-comparison of their effects. An application to a case study of literature is presented to validate the approach and demonstrate its flexibility.
4
Content available Particle filtering for the estimation of system mode of operation
Cadini F., Avram D., Zio E.
Journal of Polish Safety and Reliability Association
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2009
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Vol. 1
77--86
EN
Efficient diagnosis and prognosis of system faults depend on the ability to estimate the system state on the basis of noisy measurements of the system dynamic variables and parameters. The system dynamics is typically characterized by transitions among discrete modes of operation, each one giving rise to a specific continuous dynamics of evolution. The estimation of the state of these hybrid dynamic systems is a particularly challenging task because it requires keeping track of the transitions among the multiple modes of system dynamics corresponding to the different modes of operation. In this paper a Monte Carlo estimation method is illustrated with an application to a case study of literature which consists of a tank filled with liquid, whose level is autonomously maintained between two thresholds. The system behavior is controlled by discrete mode actuators, whose states are estimated by a Monte Carlo-based particle filter on the basis of noisy level and temperature measurements.
5
Content available Multi-objective genetic algorithms for the reliability analysis and optimization of electrical transmission networks
Cadini F., Zio E., Golea L. R., Petrescu C. A.
Journal of Polish Safety and Reliability Association
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2009
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Vol. 1
87--94
EN
The results of two applications of multi-objective genetic algorithms to the analysis and optimization of electrical transmission networks are reported to show the potential of these combinational optimization schemes in the treatment of highly interconnected, complex systems. In a first case study, an analysis of the topological structure of an electrical power transmission system of literature is carried out to identify the most important groups of elements of different sizes in the network. The importance is quantified in terms of group closeness centrality. In the second case study, an optimization method is developed for identifying strategies of expansion of an electrical transmission network by addition of new lines of connection. The objective is that of improving the transmission reliability, while maintaining the investment cost limited.
6
Content available Importance measures in presence of uncertainties
Baraldi P., Zio E., Compare M.
Journal of Polish Safety and Reliability Association
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2008
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Vol. 1
33--39
EN
This paper presents a work on the study of importance measures in presence of uncertainties originating from the lack of knowledge and information on the system (epistemic uncertainties). A criterion is proposed for ranking the risk contributors in presence of uncertainties described by probability density functions.
7
Content available Soft computing methods applied to condition monitoring and fault diagnosis for maintenance
Zio E.
Journal of Polish Safety and Reliability Association
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2007
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Vol. 2
363--377
EN
Malfunctions in equipment and components are often sources of reduced productivity and increased maintenance costs in various industrial applications. For this reason, machine condition monitoring is being pursued to recognize incipient faults in the strive towards optimising maintenance and productivity. In this respect, the following lecture notes provide the basic concepts underlying some methodologies of soft computing, namely neural networks, fuzzy logic systems and genetic algorithms, which offer great potential for application to condition monitoring and fault diagnosis for maintenance optimisation. The exposition is purposely kept on a somewhat intuitive basis: the interested reader can refer to the copious literature for further technical details.
8
Content available Sensitivity analysis of a fuzzy expert system for modelling dependencies in human operators’ emergency tasks
Zio E., Baraldi P., Librizzi M., Podofillini L., Dang H. V.
Journal of Polish Safety and Reliability Association
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2007
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Vol. 2
379--389
EN
This paper analyzes the behaviour of a fuzzy expert system for evaluating the dependence among successive operator actions, through a sensitivity analysis on the fuzzy input partitioning and assessment. Preliminary results are presented with respect to a case study concerning two successive tasks of an emergency procedure in a nuclear reactor. Work is in progress to perform a thorough sensitivity analysis to generalize the results obtained.
9
Content available Recurrent neural networks for dynamic reliability analysis
Cadini F., Zio E., Pedroni N.
Journal of Polish Safety and Reliability Association
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2007
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Vol. 1
45--53
EN
A dynamic approach to the reliability analysis of realistic systems is likely to increase the computational burden, due to the need of integrating the dynamics with the system stochastic evolution. Hence, fast-running models of process evolution are sought. In this respect, empirical modelling is becoming a popular approach to system dynamics simulation since it allows identifying the underlying dynamic model by fitting system operational data through a procedure often referred to as ‘learning’. In this paper, a Locally Recurrent Neural Network (LRNN) trained according to a Recursive Back-Propagation (RBP) algorithm is investigated as an efficient tool for fast dynamic simulation. An application is performed with respect to the simulation of the non-linear dynamics of a nuclear reactor, as described by a simplified model of literature.
10
Content available Optimising a fuzzy fault classification tree by a single-objective genetic algorithm
Zio E., Baraldi P., Popescu I. C.
Journal of Polish Safety and Reliability Association
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2007
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Vol. 2
391--400
EN
In this paper a single-objective Genetic Algorithm is exploited to optimise a Fuzzy Decision Tree for fault classification. The optimisation procedure is presented with respect to an ancillary classification problem built with artificial data. Work is in progress for the application of the proposed approach to a real fault classification problem.
11
Content available Analysis of the safety efficiency of a road network : a real case study
Zio E., Sansavini G., Maja R., Marchionni G.
Journal of Polish Safety and Reliability Association
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2007
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Vol. 2
401--406
EN
In this paper, recently introduced topological measures of interconnection and efficiency of network systems are applied to the safety analysis of the road transport system of the Province of Piacenza in Italy. The vulnerability of the network is evaluated with respect to the loss of a road link, e.g. due to a car accident, road work or other jamming occurrences. Eventually, the improvement in the global and local safety indicators following the implementation of a road development plan is evaluated.
12
Content available remote The use of importance measures for the optimization of multi-state systems
Zio E., Podofillini L.
Eksploatacja i Niezawodność
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2006
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nr 2
33-36
EN
In this paper we propose an approach to the multiobjective optimization of a multi-state system (MSS) design, based on incorporating information from importance measures (IMs). More specifically, IMs come into play at the objective functions level in order to drive the search towards a MSS which, besides being optimal from the points of view of economics and safety, is also 'balanced' in the sense that all components have similar IMs values, without bottlenecks or unnecessarily high-performing components.
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