Probability distributions in reliability evaluation

1992 ◽  
pp. 155-220 ◽  
Author(s):  
Roy Billinton ◽  
Ronald N. Allan
Keyword(s):  
Probability Distributions ◽  
Reliability Evaluation

scholarly journals Reliability Evaluation for Aviation Electric Power System in Consideration of Uncertainty

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1175
Author(s):  
Yao Wang ◽  
Xinqin Gao ◽  
Yuanfeng Cai ◽  
Mingshun Yang ◽  
Shujuan Li ◽  
...  
Keyword(s):  
Power System ◽  
Electric Power ◽  
System Reliability ◽  
Probability Distributions ◽  
Rapid Development ◽  
Reliability Evaluation ◽  
Electric Power System ◽  
Traditional System ◽  
Electric Aircraft ◽  
System Time

With the rapid development of more electric aircraft (MEA) in recent years, the aviation electric power system (AEPS) has played an increasingly important role in safe flight. However, as a highly reliable system, because of its complicated flight conditions and architecture, it often proves significant uncertainty in its failure occurrence and consequence. Thus, more and more stakeholders, e.g., passengers, aviation administration departments, are dissatisfied with the traditional system reliability analysis, in which failure uncertainty is not considered and system reliability probability is a constant value at a given time. To overcome this disadvantage, we propose a new methodology in the AEPS reliability evaluation. First, we perform a random sampling from the probability distributions of components’ failure rates and compute the system reliability at each sample point; after that, we use variance, confidence interval, and probability density function to quantify the uncertainty of system reliability. Finally, we perform the new method on a series–parallel system and an AEPS. The results show that the power supply reliability of AEPS is uncertain and the uncertainty varies with system time even though the uncertainty of each component’s failure is quite small; therefore it is necessary to quantify system uncertainty for safer flight, and our proposed method could be an effective way to accomplish this quantization task.

Reliability assessment of stochastic networks with ER connectivity and ER dependency

2021 ◽  
pp. 1748006X2110019
Author(s):  
Heping Jia ◽  
Rui Peng ◽  
Dunnan Liu ◽  
Yanbin Li ◽  
Yi Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Probability Distributions ◽  
Reliability Assessment ◽  
Reliability Evaluation ◽  
Stochastic Networks ◽  
Evaluation Framework ◽  
Stochastic Network ◽  
Time To Failure ◽  
Numerical Examples ◽  
Mdd Method

In stochastic networks, nodes usually function dependently and interact with other nodes through connectivity links or dependency links. In this paper, the model for stochastic networks considering sub-networks with connectivity and dependency links of Erdös-Rényi (ER) topology is proposed, which is defined as networks with arbitrary pair of nodes randomly connected/depended by a constant probability. The reliability evaluation framework for the proposed networks is developed, where both of the extended multi-valued decision diagram (MDD) method and Monte Carlo simulation (MCS) are involved. The MDD method is proposed to assess the reliability of deterministic stochastic networks with ER connectivity and dependency, where arbitrary time to failure distributions of nodes are allowed. Based on the reliability evaluation for a stochastic network with a deterministic structure, the MCS is employed to achieve the reliability analysis of corresponding stochastic networks. Numerical examples are presented to demonstrate the proposed stochastic network model and reliability evaluation framework, where the probability distributions for the reliability of stochastic networks are provided.

scholarly journals Reliability Evaluation for the Running State of the Manufacturing System Based on Poor Information

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Xintao Xia ◽  
Wenhuan Zhu ◽  
Bin Liu
Keyword(s):  
Probability Distribution ◽  
Product Quality ◽  
Manufacturing System ◽  
Evaluation Method ◽  
Probability Distributions ◽  
Bootstrap Method ◽  
Maximum Entropy Principle ◽  
Reliability Evaluation ◽  
Small Sample ◽  
Inspection Data

The output performance of the manufacturing system has a direct impact on the mechanical product quality. For guaranteeing product quality and production cost, many firms try to research the crucial issues on reliability of the manufacturing system with small sample data, to evaluate whether the manufacturing system is capable or not. The existing reliability methods depend on a known probability distribution or vast test data. However, the population performances of complex systems become uncertain as processing time; namely, their probability distributions are unknown, if the existing methods are still taken into account; it is ineffective. This paper proposes a novel evaluation method based on poor information to settle the problems of reliability of the running state of a manufacturing system under the condition of small sample sizes with a known or unknown probability distribution. Via grey bootstrap method, maximum entropy principle, and Poisson process, the experimental investigation on reliability evaluation for the running state of the manufacturing system shows that, under the best confidence levelP=0.95, if the reliability degree of achieving running quality isr>0.65, the intersection area between the inspection data and the intrinsic data isA(T)>0.3and the variation probability of the inspection data isPB(T)≤0.7, and the running state of the manufacturing system is reliable; otherwise, it is not reliable. And the sensitivity analysis regarding the size of the samples can show that the size of the samples has no effect on the evaluation results obtained by the evaluation method. The evaluation method proposed provides the scientific decision and suggestion for judging the running state of the manufacturing system reasonably, which is efficient, profitable, and organized.

Asteroid and Comet Impact Speeds upon Mars: Significance for Panspermia and the Supply of Organics

1997 ◽  
Vol 161 ◽  
pp. 197-201 ◽  
Author(s):  
Duncan Steel
Keyword(s):  
Probability Distributions ◽  
Regions Of Interest ◽  
Significant Fraction ◽  
Organic Chemicals ◽  
Impact Speed ◽  
The Mean ◽  
The Impact

AbstractWhilst lithopanspermia depends upon massive impacts occurring at a speed above some limit, the intact delivery of organic chemicals or other volatiles to a planet requires the impact speed to be below some other limit such that a significant fraction of that material escapes destruction. Thus the two opposite ends of the impact speed distributions are the regions of interest in the bioastronomical context, whereas much modelling work on impacts delivers, or makes use of, only the mean speed. Here the probability distributions of impact speeds upon Mars are calculated for (i) the orbital distribution of known asteroids; and (ii) the expected distribution of near-parabolic cometary orbits. It is found that cometary impacts are far more likely to eject rocks from Mars (over 99 percent of the cometary impacts are at speeds above 20 km/sec, but at most 5 percent of the asteroidal impacts); paradoxically, the objects impacting at speeds low enough to make organic/volatile survival possible (the asteroids) are those which are depleted in such species.

Reliability evaluation of substation control systems

1999 ◽  
Vol 146 (6) ◽  
pp. 626 ◽  
Author(s):  
L.R. Castro Ferreira ◽  
P.A. Crossley ◽  
J. Goody ◽  
R.N. Allan
Keyword(s):  
Control Systems ◽  
Reliability Evaluation

Reliability Evaluation for a Wet-Plated Electrode with a Al/Al2O3/Cu Insulated Metal Substrate

2013 ◽  
Vol 51 (7) ◽  
pp. 523-527 ◽  
Author(s):  
Su-Jeong Suh ◽  
Chang-Hyoung Lee ◽  
Young-Lae Cho ◽  
Hwa-Sun Park ◽  
Won-Pyo Lee ◽  
...  
Keyword(s):  
Reliability Evaluation ◽  
Metal Substrate
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