scholarly journals A calibration-based method for interval reliability analysis of the multi-manipulator system

2021 ◽  
Vol 24 (1) ◽  
pp. 42-52
Author(s):  
Wei Wang ◽  
Shuangyao Liu ◽  
Jin Wang ◽  
Guodong Lu
Keyword(s):  
Reliability Analysis ◽  
Interval Reliability

Reliability Assessment for Small Sample Based on Interval Degradation Data

2011 ◽  
Vol 199-200 ◽  
pp. 534-537
Author(s):  
Wei Tao Zhao ◽  
Dong Lin Yao ◽  
Wei Ping Zhang
Keyword(s):  
Reliability Analysis ◽  
Reliability Assessment ◽  
Small Sample ◽  
Analysis Method ◽  
Numerical Example ◽  
Degradation Data ◽  
Analysis Theory ◽  
Interval Reliability ◽  
Improved Model ◽  
Assessment Results

Based on reliability analysis theory, traditional interval reliability analysis method is improved by take the smaller value of probability reliability and interval reliability as the results of reliability assessment, which makes the reliability assessment results more fit engineering cases. The improved model is applied to reliability assessment of small sample products with degradation characteristics, and results of assessment are compared with existing methods. A numerical example is considered, the results show that the assessment results by the method proposed in the paper is reasonable and believable.

Reliability analysis of complex repairable systems by means of marked point processes

1980 ◽  
Vol 17 (1) ◽  
pp. 154-167 ◽  
Author(s):  
Peter Franken ◽  
Arnfried Streller
Keyword(s):  
Reliability Analysis ◽  
Point Processes ◽  
Marked Point ◽  
Regenerative Process ◽  
Marked Point Processes ◽  
Marked Point Process ◽  
Repairable Systems ◽  
Interval Reliability ◽  
Repair Facility ◽  
Markovian Systems

Starting from the theory of point processes the concept of a process with an embedded marked point process is defined. It is shown that the known formula expressing the relation between the stationary and synchronous version of a regenerative process remains valid without the assumption of independence of cycles. General formulae for stationary availability and interval reliability of complex systems with repair are also obtained. In this way generalizations of Keilson's results for Markovian systems and Ross's results for systems with separately maintained elements are presented. The formulae are applied to a two-unit parallel system with a single repair facility.

scholarly journals A Sensitivity-Based Approach for Reliability Analysis of Randomly Excited Structures With Interval Axial Stiffness

2020 ◽  
Vol 6 (4) ◽  
Author(s):  
Alba Sofi ◽  
Giuseppe Muscolino ◽  
Filippo Giunta
Keyword(s):  
Reliability Analysis ◽  
Interval Analysis ◽  
Structural Reliability ◽  
Reliability Function ◽  
Extreme Value ◽  
Axial Stiffness ◽  
Engineering Practice ◽  
Stress Process ◽  
Rational Series ◽  
Interval Reliability

Abstract Reliability assessment of linear discretized structures with interval parameters subjected to stationary Gaussian multicorrelated random excitation is addressed. The interval reliability function for the extreme value stress process is evaluated under the Poisson assumption of independent up-crossing of a critical threshold. Within the interval framework, the range of stress-related quantities may be significantly overestimated as a consequence of the so-called dependency phenomenon, which arises due to the inability of the classical interval analysis to treat multiple occurrences of the same interval variables as dependent ones. To limit undesirable conservatism in the context of interval reliability analysis, a novel sensitivity-based procedure relying on a combination of the interval rational series expansion and the improved interval analysis via extra unitary interval is proposed. This procedure allows us to detect suitable combinations of the endpoints of the uncertain parameters which yield accurate estimates of the lower bound and upper bound of the interval reliability function for the extreme value stress process. Furthermore, sensitivity analysis enables to identify the most influential parameters on structural reliability. A numerical application is presented to demonstrate the accuracy and efficiency of the proposed method as well as its usefulness in view of decision-making in engineering practice.

Reliability analysis of complex repairable systems by means of marked point processes

1980 ◽  
Vol 17 (01) ◽  
pp. 154-167 ◽  
Author(s):  
Peter Franken ◽  
Arnfried Streller
Keyword(s):  
Reliability Analysis ◽  
Point Processes ◽  
Marked Point ◽  
Regenerative Process ◽  
Marked Point Processes ◽  
Marked Point Process ◽  
Repairable Systems ◽  
Interval Reliability ◽  
Repair Facility ◽  
Markovian Systems

Starting from the theory of point processes the concept of a process with an embedded marked point process is defined. It is shown that the known formula expressing the relation between the stationary and synchronous version of a regenerative process remains valid without the assumption of independence of cycles. General formulae for stationary availability and interval reliability of complex systems with repair are also obtained. In this way generalizations of Keilson's results for Markovian systems and Ross's results for systems with separately maintained elements are presented. The formulae are applied to a two-unit parallel system with a single repair facility.

Interval Reliability Analysis of Parameters of Section of Main Beam

2014 ◽  
Vol 644-650 ◽  
pp. 4991-4994
Author(s):  
Jian Fang Zhou ◽  
Guang Ran Lu
Keyword(s):  
Monte Carlo ◽  
Reliability Analysis ◽  
Optimization Algorithm ◽  
Reliability Index ◽  
Main Beam ◽  
One Dimensional ◽  
Advantages And Disadvantages ◽  
Interval Reliability ◽  
Dimensional Optimization

In the calculation of the reliability of hydraulic, due to extensive uncertainties, there are lots of errors in probabilistic reliability analysis. In this paper, by comparing the non-probabilistic reliability index of different function, we get the advantages and disadvantages of one-dimensional optimization algorithm and method of Monte Carlo, and compare the functions of each variable of main beam to obtain the influence of the precision of the variables.

Interval Reliability Analysis

2007 ◽  
Author(s):  
Xiaoping Du
Keyword(s):  
Reliability Analysis ◽  
Performance Characteristic ◽  
Extreme Values ◽  
Probability Distributions ◽  
Probability Of Failure ◽  
Interval Reliability ◽  
Interval Variables ◽  
Inverse Reliability Analysis ◽  
Reliability Method ◽  
A Performance

Traditional reliability analysis uses probability distributions to calculate reliability. In many engineering applications, some nondeterministic variables are known within intervals. When both random variables and interval variables are present, a single probability measure, namely, the probability of failure or reliability, is not available in general; but its lower and upper bounds exist. The mixture of distributions and intervals makes reliability analysis more difficult. Our goal is to investigate computational tools to quantify the effects of random and interval inputs on reliability associated with performance characteristics. The proposed reliability analysis framework consists of two components — direct reliability analysis and inverse reliability analysis. The algorithms are based on the First Order Reliability Method and many existing reliability analysis methods. The efficient and robust improved HL-RF method is further developed to accommodate interval variables. To deal with interval variables for black-box functions, nonlinear optimization is used to identify the extreme values of a performance characteristic. The direct reliability analysis provides bounds of a probability of failure; the inverse reliability analysis computes the bounds of the percentile value of a performance characteristic given reliability. One engineering example is provided.

Structural Reliability Analysis with Uncertainty-but-Bounded Parameters Based on Meshless Method

2010 ◽  
Vol 163-167 ◽  
pp. 3034-3041
Author(s):  
Wei Zhao ◽  
J.K. Liu ◽  
Qiu Wei Yang
Keyword(s):  
Reliability Analysis ◽  
Meshless Method ◽  
Reliability Index ◽  
Structural Reliability ◽  
Strain Analysis ◽  
Optimization Theory ◽  
Upper And Lower Bounds ◽  
Probability Method ◽  
Structural Reliability Analysis ◽  
Interval Reliability

The structural reliability analysis with uncertainty-but-bounded parameters is considered in this paper. Each uncertain-but-bounded parameter is represented as an interval number or vector, an interval reliability index is defined and discussed. Due to the wide application of the Meshless method, it is used in structural stress and strain analysis. The target variable of requiring reliability analysis is estimated via Taylor expansion. Based on optimization theory and vertex solution theorem, the upper and lower bounds of the target variables are obtained, and also the interval reliability index. A typical elastostatics example is presented to illustrate the computational aspects of interval reliability analysis in comparison with the traditional probability method, it can be seen that the result calculated by the vertex solution theorem is consistent with that calculated by probability method.

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