NPP Monitoring Missions via a Multi-Fleet of Drones

2020 ◽  
pp. 458-473
Author(s):  
Herman Fesenko ◽  
Ihor Kliushnikov
Keyword(s):  
Reliability Assessment ◽  
Decentralized Systems ◽  
Reliability Models

A drone-based system of monitoring of severe NPP accidents is described. A structure of a multi-fleet of drones, consisting of main drone fleets and a reserve drone fleet, is considered. A matrix of drone fleet reliability assessment attributes is presented. Various structures for systems of control stations for the multi-fleet of drones are suggested. Reliability models for the multi-fleet of drones with centralized (irredundant), centralized (redundant), decentralized, and partially decentralized systems of control stations are developed and analyzed.

scholarly journals Mechanical Damage Assessment for Pneumatic Control Valves Based on a Statistical Reliability Model

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3307
Author(s):  
Nirbhay Mathur ◽  
Vijanth Sagayan Asirvadam ◽  
Azrina Abd Aziz
Keyword(s):  
Weibull Distribution ◽  
Reliability Assessment ◽  
Mechanical Damage ◽  
Control Valve ◽  
Reliability Models ◽  
Statistical Reliability ◽  
Processing Plants ◽  
Simulated Process ◽  
Pneumatic Control Valves ◽  
Log Normal

A reliability assessment is an important tool used for processing plants, since the facility consists of many loops and instruments attached and operated based on other availability; thus, a statistical model is needed to visualize the reliability of its operation. The paper focuses on the reliability assessment and prediction based on the existing statistical models, such as normal, log-normal, exponential, and Weibull distribution. This paper evaluates and visualizes the statistical reliability models optimized using MLE and considers the failure mode caused during a simulated process control operation. We simulated the failure of the control valve caused by stiction running with various flow rates using a pilot plant, which depicted the Weibull distribution as the best model to estimate the simulated process failure.

The Multilevel Prognosis System Based on Matrices and Digraphs Methods

2013 ◽  
Vol 199 ◽  
pp. 79-84 ◽  
Author(s):  
Mariusz Piotr Hetmańczyk
Keyword(s):  
Error Analysis ◽  
Operational Reliability ◽  
Decentralized Systems ◽  
New Approach ◽  
Reciprocal Relationships ◽  
Reliability Models ◽  
Control Power ◽  
Distribution Of Elements ◽  
Mass Flows ◽  
Power Noise

The author of this article considers new approach based on operational reliability models, written in the form of matrices and digraphs methods. At a core of the method the author used the theory of systems and their decomposition consistent with the FMEA methodology [, that allows a simplification of the distribution of elements within the system into smaller parts having a greater susceptibility to the error analysis and forecasting of their states. The method mainly refers to decentralized systems, linked via reciprocal relationships (that can be applied to manufacturing work centres, transport lines, etc.), containing subsystems that use the control, power, noise and mass flows streams. Article includes also main assumptions of described method, realizability studies, application areas and significant restrictions.

scholarly journals Electrical insulation components reliability assessment and practical Bayesian estimation under a Log-Logistic model

2018 ◽  
Vol 7 (3) ◽  
pp. 1072 ◽  
Author(s):  
E Chiodo ◽  
L P. Di Noia ◽  
F Mottola
Keyword(s):  
Logistic Model ◽  
Reliability Assessment ◽  
Model Identification ◽  
Reliability Function ◽  
Electrical Insulation ◽  
Reliability Model ◽  
Reliability Models ◽  
Inverse Gamma ◽  
Past Data ◽  
Strength Models

This paper deals with the “physical reliability models” assessment and estimation for electrical insulation components. It is well known that the reliability model identification and estimation of most of the modern power system components, such as insulation components, may be better achieved, instead that using limited lifetime data, by the knowledge of the degradation mechanisms. Such mechanisms, which are responsible for component aging and failure, are indeed well established in the field of electrical insulation: this is also the case of the so called “Stress-Strength” models. In particular, the “Log-logistic” model, deduced by a suitable Weibull stress-strength probabilistic model, has found valid applications to the reliability assessment of the insulation components. In the framework of the estimation of such reliability model, a new Bayesian approach, based upon the “Odds Ratio” of the Log-logistic model is developed in this paper, based upon the properties that such information, being proportional to the reliability function, is available to the engineer on the basis of past data; moreover, being proportional to the Weibull scale parameter, allows to exploit known features of its conjugate prior Inverse Gamma distribution. Numerical examples and the results of extensive Monte Carlo simulations demonstrate the feasibility and efficiency of the proposed procedure.  

A Methodology for Model-Based Reliability Estimation

2014 ◽  
pp. 450-472
Author(s):  
Mohd Adham Isa ◽  
Dayang Norhayati Abang Jawawi
Keyword(s):  
Reliability Analysis ◽  
Reliability Assessment ◽  
Reliability Estimation ◽  
Reliability Model ◽  
Estimation Model ◽  
Domain Experts ◽  
Reliability Models ◽  
Model Based ◽  
Reliability Parameters ◽  
Estimate Reliability

In recent years, reliability assessment is an essential process in system quality assessments. However, the best practice of software engineering for reliability analysis is not yet of its matured stage. The existing works are only capable to explicitly apply a small portion of reliability analysis in a standard software development process. In addition, an existing reliability assessment is based on an assumption provided by domain experts. This assumption is often exposed to errors. An effective reliability assessment should be based on reliability requirements that could be quantitatively estimated using metrics. The reliability requirements can be visualized using reliability model. However, existing reliability models are not expressive enough and do not provide consistence-modeling mechanism to allow developers to estimate reliability parameter values. Consequently, the reliability estimation using those parameters is usually oversimplified. With this situation, the inconsistency problem could happen between different estimation stages. In this chapter, a new Model-Based Reliability Estimation (MBRE) methodology is developed. The methodology consists of reliability model and reliability estimation model. The methodology provides a systematic way to estimate system reliability, emphasizing the reliability model for producing reliability parameters which will be used by the reliability estimation model. These models are built upon the timing properties, which is the primary input value for reliability assessment.

BOOTSTRAP CONFIDENCE INTERVALS OF SOFTWARE RELIABILITY MEASURES BASED ON A GAMMA FUNCTION MODEL

2008 ◽  
Vol 15 (01) ◽  
pp. 55-66
Author(s):  
MITSUHIRO KIMURA
Keyword(s):  
Confidence Intervals ◽  
Gamma Function ◽  
Software Reliability ◽  
Reliability Assessment ◽  
Numerical Differentiation ◽  
Model Parameters ◽  
Function Model ◽  
Data Set ◽  
Reliability Models ◽  
Software Reliability Models

This paper focuses on the generalization of several software reliability models and the derivation of confidence intervals of reliability assessment measures. First we propose a gamma function model as a generalized model, and discuss how to obtain the confidence intervals from a data set by using a bootstrap scheme when the size of the data set is small. A two-parameter numerical differentiation method is applied to the data set to estimate the model parameters. We also show several numerical illustrations of software reliability assessment.

scholarly journals Fast Reliability Assessment of Neutral-Point-Clamped Topologies through Markov Models

2020 ◽  
Author(s):  
Sergio Busquets-Monge ◽  
Roya Rafiezadeh ◽  
Salvador Alepuz ◽  
Alber Filba-Martinez ◽  
Joan Nicolas-Apruzzese
Keyword(s):  
Fault Tolerance ◽  
Markov Models ◽  
Reliability Assessment ◽  
Open Circuit ◽  
Neutral Point ◽  
Time To Failure ◽  
Fast Calculation ◽  
Reliability Models ◽  
Minimum Number ◽  
Mean Time

This paper presents detailed Markov models for the reliability assessment of multilevel neutral-point-clamped (NPC) converter leg topologies, incorporating their inherent fault-tolerance under open-circuit switch faults. The Markov models are generated and discussed in detail for the three-level and four-level active NPC (ANPC) cases, while the presented methodology can be applied to easily generate the models for higher number of levels and for other topology variants. In addition, this paper also proposes an extremely fast calculation method to obtain the precise value of the system mean time to failure from any given formulated system Markov model. This method is then applied to quantitatively compare the reliability of two-level, three-level, and four-level ANPC legs under switch open-circuit-guaranteed faults and varying degrees of device paralleling. The comparison reveals that multilevel ANPC leg topologies inherently present a potential for a higher reliability than the conventional two-level leg, questioning the suitability of the traditional search for topologies with the minimum number of devices in order to improve reliability. Experimental results are presented to validate the fault-tolerance assumptions upon which the presented reliability models for the three-level and four-level ANPC legs are based.

scholarly journals Fast Reliability Assessment of Neutral-Point-Clamped Topologies through Markov Models

2020 ◽  
Author(s):  
Sergio Busquets-Monge ◽  
Roya Rafiezadeh ◽  
Salvador Alepuz ◽  
Alber Filba-Martinez ◽  
Joan Nicolas-Apruzzese
Keyword(s):  
Fault Tolerance ◽  
Markov Models ◽  
Reliability Assessment ◽  
Open Circuit ◽  
Neutral Point ◽  
Time To Failure ◽  
Fast Calculation ◽  
Reliability Models ◽  
Minimum Number ◽  
Mean Time

This paper presents detailed Markov models for the reliability assessment of multilevel neutral-point-clamped (NPC) converter leg topologies, incorporating their inherent fault-tolerance under open-circuit switch faults. The Markov models are generated and discussed in detail for the three-level and four-level active NPC (ANPC) cases, while the presented methodology can be applied to easily generate the models for higher number of levels and for other topology variants. In addition, this paper also proposes an extremely fast calculation method to obtain the precise value of the system mean time to failure from any given formulated system Markov model. This method is then applied to quantitatively compare the reliability of two-level, three-level, and four-level ANPC legs under switch open-circuit-guaranteed faults and varying degrees of device paralleling. The comparison reveals that multilevel ANPC leg topologies inherently present a potential for a higher reliability than the conventional two-level leg, questioning the suitability of the traditional search for topologies with the minimum number of devices in order to improve reliability. Experimental results are presented to validate the fault-tolerance assumptions upon which the presented reliability models for the three-level and four-level ANPC legs are based.

A Methodology for Model-Based Reliability Estimation

2017 ◽  
pp. 461-484
Author(s):  
Mohd Adham Isa ◽  
Dayang Norhayati Abang Jawawi
Keyword(s):  
Reliability Analysis ◽  
Reliability Assessment ◽  
Reliability Estimation ◽  
Reliability Model ◽  
Estimation Model ◽  
Domain Experts ◽  
Reliability Models ◽  
Model Based ◽  
Reliability Parameters ◽  
Estimate Reliability

In recent years, reliability assessment is an essential process in system quality assessments. However, the best practice of software engineering for reliability analysis is not yet of its matured stage. The existing works are only capable to explicitly apply a small portion of reliability analysis in a standard software development process. In addition, an existing reliability assessment is based on an assumption provided by domain experts. This assumption is often exposed to errors. An effective reliability assessment should be based on reliability requirements that could be quantitatively estimated using metrics. The reliability requirements can be visualized using reliability model. However, existing reliability models are not expressive enough and do not provide consistence-modeling mechanism to allow developers to estimate reliability parameter values. Consequently, the reliability estimation using those parameters is usually oversimplified. With this situation, the inconsistency problem could happen between different estimation stages. In this chapter, a new Model-Based Reliability Estimation (MBRE) methodology is developed. The methodology consists of reliability model and reliability estimation model. The methodology provides a systematic way to estimate system reliability, emphasizing the reliability model for producing reliability parameters which will be used by the reliability estimation model. These models are built upon the timing properties, which is the primary input value for reliability assessment.

scholarly journals Fast Reliability Assessment of Neutral-Point-Clamped Topologies through Markov Models

2020 ◽  
Author(s):  
Sergio Busquets-Monge ◽  
Roya Rafiezadeh ◽  
Salvador Alepuz ◽  
Alber Filba-Martinez ◽  
Joan Nicolas-Apruzzese
Keyword(s):  
Fault Tolerance ◽  
Markov Models ◽  
Reliability Assessment ◽  
Open Circuit ◽  
Neutral Point ◽  
Time To Failure ◽  
Fast Calculation ◽  
Reliability Models ◽  
Minimum Number ◽  
Mean Time

This paper presents detailed Markov models for the reliability assessment of multilevel neutral-point-clamped (NPC) converter leg topologies, incorporating their inherent fault-tolerance under open-circuit switch faults. The Markov models are generated and discussed in detail for the three-level and four-level active NPC (ANPC) cases, while the presented methodology can be applied to easily generate the models for higher number of levels and for other topology variants. In addition, this paper also proposes an extremely fast calculation method to obtain the precise value of the system mean time to failure from any given formulated system Markov model. This method is then applied to quantitatively compare the reliability of two-level, three-level, and four-level ANPC legs under switch open-circuit-guaranteed faults and varying degrees of device paralleling. The comparison reveals that multilevel ANPC leg topologies inherently present a potential for a higher reliability than the conventional two-level leg, questioning the suitability of the traditional search for topologies with the minimum number of devices in order to improve reliability. Experimental results are presented to validate the fault-tolerance assumptions upon which the presented reliability models for the three-level and four-level ANPC legs are based.

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