Dynamic reliability indices for parallel, series and k-out-of-n multi-state systems

2006 ◽  
Author(s):  
E. Zaitseva ◽  
V. Levashenko
Keyword(s):  
Dynamic Reliability ◽  
Reliability Indices ◽  
Parallel Series

scholarly journals Decomposition and Estimation of Multi-State Systems by Dynamic Reliability Indices

2008 ◽  
Vol 4 (1) ◽  
pp. 353-361
Author(s):  
Zaitseva Elena ◽  
Levashenko Vitaly ◽  
Matiaško Karol
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
Parallel Systems ◽  
State System ◽  
Reliability Estimation ◽  
Technical System ◽  
Dynamic Reliability ◽  
Reliability Indices ◽  
Multiple Valued Logic

Decomposition and Estimation of Multi-State Systems by Dynamic Reliability IndicesSome typical configurations of Multi-State System and their mathematical descriptions are considered in paper with relation to Reliability Analysis. Multiple-Valued Logic is applied for these descriptions synthesis and Dynamic Reliability Indices are used for Multi-State System reliability estimation. We concentrate on series and parallel systems, because these structures are basic for most of the technical system. We get measures of reliability for the failure and restoration of this system.

New Indices for Measure of Parallel and Series Multi-State System Reliability

2005 ◽  
Author(s):  
Kailash Kapur ◽  
Elena Zaitseva ◽  
Vitaly Levashenko
Keyword(s):  
System Reliability ◽  
Differential Calculus ◽  
Parallel Systems ◽  
State System ◽  
System Component ◽  
Dynamic Reliability ◽  
Reliability Indices ◽  
Multiple Valued Logic ◽  
Technical Systems ◽  
Definition Of

The reliability of multi-state system is analyzed in this paper. In a multi-state system, both the system and its components may experience more than two reliability states. We propose dynamic reliability indices for reliability analysis of this system. Mathematical tools of the multiple-valued logic (the Logical Differential Calculus in particular) are exploited for definition of these indices. These indices estimate the effect on the multi-state system reliability by the state of a system component. We concentrate on series and parallel systems, because these structures are basic for many technical systems and get measures of reliability for the failure and restoration of these systems.

Time-Dependent Reliability Prediction of Bridge Member Based on MGPF and SHM Data

2016 ◽  
Vol 15 ◽  
pp. 119-132 ◽  
Author(s):  
Xue Ping Fan ◽  
Yue Fei Liu
Keyword(s):  
Particle Filter ◽  
Real Time ◽  
Dynamic Model ◽  
Health Monitoring ◽  
Structural Reliability ◽  
Filter Method ◽  
Dynamic Reliability ◽  
Reliability Indices ◽  
Distribution Parameters

In the long-term monitoring period, the structural health monitoring (SHM) system produces a huge amount of monitoring data. It becomes a very important thing that how to real-timely predict structural reliability indices from such huge number of monitored data. In this paper, To real-timely predict reliability of bridge members with real-time monitoring information, with the long-term mass monitored data of health monitoring system, the data-based dynamic model including observation equation and state equation is built, and then the mixed Gaussian particle filter (MGPF) is introduced. With particle filter method, Bayesian method and dynamic model, the posteriori distribution parameters of state variable and one-step forward prediction distribution parameters of monitored data are predicted. Through resampling technique, with MGPF, the prediction precision of dynamic model can generally increase. Based on the dynamic monitored data, the weights of resampled particles can be constantly updated. Therefore the problem of particle degradation is solved. Finally based on the real-time predicted distribution parameters, with the first order second moment (FOSM) method, the dynamic reliability of bridge member is predicted, and an actual example is provided to illustrate the application and feasibility of the proposed models and methods.

Assessing Stressors Related to Migration in Patients With Psychiatric Disorders

2012 ◽  
Vol 28 (4) ◽  
pp. 262-269 ◽  
Author(s):  
Matthias Johannes Müller ◽  
Suzan Kamcili-Kubach ◽  
Songül Strassheim ◽  
Eckhardt Koch
Keyword(s):  
Interrater Reliability ◽  
Item Analysis ◽  
Global Assessment Of Functioning ◽  
Family Conflicts ◽  
Response Options ◽  
Reliability Indices ◽  
Dsm Iv ◽  
Functional Relevance ◽  
Sum Scores ◽  
Gaf Scores

A 10-item instrument for the assessment of probable migration-related stressors was developed based on previous work (MIGSTR10) and interrater reliability was tested in a chart review study. The MIGSTR10 and nine nonspecific stressors of the DSM-IV Axis IV (DSMSTR9) were put into a questionnaire format with categorical and dimensional response options. Charts of 100 inpatients (50 Turkish migrants [MIG], 50 native German patients [CON]) with affective or anxiety disorder were reviewed by three independent raters and MIGSTR10, DSMSTR9, and Global Assessment of Functioning scale (GAF) scores were obtained. Interrater reliability indices (ICC) of items and sum scores were calculated. The prevalence of single migration-related stressors in MIG ranged from 15% to 100% (CON 0–92%). All items of the MIGSTR10 (ICC 0.58–0.92) and the DSMSTR9 (ICC 0.56–0.96) reached high to very high interrater agreement (p < .0005). The item analysis of the MIGSTR10 revealed sufficient internal consistency (Cronbach’s α = 0.68/0.69) and only one item (“family conflicts”) without substantial correlation with the remaining scale. Correlation analyses showed a significant overlap of dimensional MIGSTR10 scores (r² = 0.25; p < .01) and DSMSTR9 scores (r² = 9%; p < .05) with GAF scores in MIG indicating functional relevance. MIGSTR10 is considered a feasible, economic, and reliable instrument for the assessment of stressors potentially related to migration.

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