Bayesian and Multiple Bayesian Analysis of the Reliability Performances for Series System with Cold Standby Units

By using Bayesian and multiple Bayesian method, the failure probability, reliability and mean time to failure(MTTF) of series system with cold standby units are estimated. At last, we compare the two estimators by means of Monte_Carlo simulation.

Derivation of Reliability Index Vector Formula for Series System and Its Application

In this study, a reliability index vector formula is proposed for series system with two failure modes in term of the concept of reliability index vector and equivalent failure modes. Firstly, the reliability index vector is introduced to determine the correlation coefficient between two failure modes, and then, the reliability index vector of a series system can be obtained. Several numerical cases and an analysis on offshore platform are performed, and the results show that this scheme provided here has better computational accuracy, and its calculation process is simpler for the series systems reliability calculations compared with the other methods. Also this scheme is more convenient for the engineering applications.

Reliability of a Large Series-parallel System in Variable Operating Conditions

In this paper, a semi-Markov model of system operation processes is proposed and its selected parameters are determined. A series-parallel multi-state system is considered, and its reliability and risk characteristics found. Subsequently, a joint model of system operation process and system multi-state reliability and risk is constructed. Moreover, the asymptotic approach to reliability and risk evaluation of a multi-state series-parallel system in its operation process is applied to a port grain transportation system.

Reliability Optimization of Entropy Based Series-Parallel System Using Global Criterion Method

In this paper, we have considered a series-parallel system to find out optimum system reliability with an additional entropy objective function. Maximum system reliability of series-parallel system is depending on proper allocation of redundancy component in different stage. The goal of entropy based reliability redundancy allocation problem is to find optimal number of redundancy component in each stage such a manner that maximize the system reliability subject to available total system cost. Global criterion method is used to analyze entropy based reliability optimization problem with different weight function of objective functions. Numerical examples have been provided to illustrate the model.

A Neural Network Method for Reliability Optimizations of Complex Systems

The main task of system reliability design is to find the best layout of components to maximize reliability or to minimize cost. A reliability optimization approach using neural networks to identify the choice of components in series-parallel systems with multiple constraints is presented in this paper. The McCullochPittes neural network model is used in this approach. The design methods of the neural network construction and its energy function are described in detail. The optimal solutions of the reliability problem are obtained by minimizing the energy function of the neural networks. Simulation results show the reliability optimization approach using neural networks can find the optimal or near-optimal solutions for most of the problems in a relatively short time, it is a useful alternative for system reliability design of complex systems.

Reliability model of organization management chain of South-to-North Water Diversion Project during construction period

In order to analyze the indispensability of the organization management chain of the South-to-North Water Diversion Project （SNWDP）, two basic forms （series connection state and mixed state of both series connection and parallel connection） of the organization management chain can be abstracted. The indispensability of each form has been studied and is described in this paper. Through analysis of the reliability of the two basic forms, reliability models of the organization management chain in the series connection state and the mixed state of both series connection and parallel connection have been set up.

Sensitivity Test and Data Analysis for Storage Reliability Assessment of Explosive Initiator

The explosive initiator is one kind of sensitivity products with long life and high reliability.In order to improve the storage reliability assessment,the method of storage reliability assessment for explosive initiator was proposed based on time series model using the sensitivity test data.In the method,the up and down test was used to estimate the distribution parameters of threshold.And an approach to design the up and down test was present to draw better estimations.Furthermore,the method of shrinkage estimation was introduced to get a better estimation of scale parameter by combining the sample information with prior information.The simulation result shows that the shrinkage estimation is better than traditional estimation under certain conditions.With the distribution parameters estimations,the time series models were used to describe the changing trends of distribution parameters along with storage time.Then for a fixed storage time,the distribution parameters were predicted based on the models.Finally,the confidence interval of storage reliability was obtained by fiducial inference.The illustrative example shows that the method is available for storage reliability assessment of the explosive initiator with high reliability.

Data analytics approach for travel time reliability pattern analysis and prediction

Travel time reliability(TTR)is an important measure which has been widely used to represent the traffic conditions on freeways.The objective of this study is to develop a systematic approach to analyzing TTR on roadway segments along a corridor.A case study is conducted to illustrate the TTR patterns using vehicle probe data collected on a freeway corridor in Charlotte,North Carolina.A number of influential factors are considered when analyzing TTR,which include,but are not limited to,time of day,day of week,year,and segment location.A time series model is developed and used to predict the TTR.Numerical results clearly indicate the uniqueness of TTR patterns under each case and under different days of week and weather conditions.The research results can provide insightful and objective information on the traffic conditions along freeway segments,and the developed data-driven models can be used to objectively predict the future TTRs,and thus to help transportation planners make informed decisions.

A New Analysis Concept in Applying Software Reliability Growth Models and Tool Implementation: The SafeMan

In recent years, many software development organizations have been assessing and analyzing their software product’s reliability/quality and judging whether the software product is releasable by using Software Reliability Growth Models (SRGMs) at the final stage of software development. The usage of SRGMs originates in the advantage that various reliability analysis results based on the SRGMs can be acquired easily. However, it is very difficult for general software project managers to grasp the achievement level of reliability/quality based on its analysis results because some sort of professional knowledge is required in order to understand the information on the attainment progress of software product’s reliability/quality. Moreover, it is also difficult for software project managers and inspectors who do not deeply comprehend the details of their project to evaluate the degree of software reliability and quality, if they assess it without grasping the live development situation and only see the documents submitted from their staff. In this paper, we propose a new analysis concept for assessing the software product’s reliability/quality, and illustrate the output results obtained by a tool, the SafeMan.

Load Dependent Series-Parallel Systems with Common Bus Performance Sharing Mechanism

A series-parallel system was proposed with common bus performance sharing in which the performance and failure rate of the element depended on the load it was carrying. In such a system,the surplus performance of a sub-system can be transmitted to other deficient sub-systems. The transmission capacity of the common bus performance sharing mechanism is a random variable. Effects of load on element performance and failure rate were considered in this paper. A reliability evaluation algorithm based on the universal generating function technique was suggested. Numerical experiments were conducted to illustrate the algorithm.

Time-dependent reliability analysis of aerospace electromagnetic relay considering hybrid uncertainties quantification of probabilistic and interval variables

Reliability is a crucial metric in aerospace engineering.The results of reliability assessments for components like aerospace electromagnetic relays directly impact the development and operational reliability of aerospace engineering systems.Current methods for analyzing the reliability of aerospace electromagnetic relays have limitations,such as neglecting the combined effects of multiple uncertain factors,degradation of key component properties,and the influence of fluctuations in aerospace environments.Additionally,these methods often assume a single-type uncertainty in the manufacturing process,leading to significant deviations between the analysis results and actual measurement results.To address these issues,this study proposes an efficient timedependent reliability analysis method based on the HL-RF algorithm,considering a hybrid of probabilistic and interval uncertainty that accounts for degradation and environmental conditions.The proposed method is applied to the reliability analysis of actual aerospace electromagnetic relay products and compared with traditional methods,demonstrating significant advantages.The proposed method has been applied to the time-dependent reliability analysis of actual aerospace electromagnetic relay products under different environmental conditions.The analysis results exhibit an error margin within 5.12% compared to actual measurement results.Compared to analysis methods solely based on probabilistic uncertainty quantification or interval uncertainty quantification,this method reduces the analysis error by 52% and 67% respectively.When compared to two other state-of-the-art methods that integrate probabilistic and interval uncertainty quantification,the error reduction is 23%.These demonstrate the superiority of the proposed method and validates its effectiveness.The presented approach has the potential to be extended for reliability analysis in other aerospace electromechanical systems.

Optimal Redundancy Allocation in Hierarchical Series-Parallel Systems Using Mixed Integer Programming

Reliability optimization plays an important role in design, operation and management of the industrial systems. System reliability can be easily enhanced by improving the reliability of unreliable components and/or by using redundant configuration with subsystems/components in parallel. Redundancy Allocation Problem (RAP) was studied in this research. A mixed integer programming model was proposed to solve the problem, which considers simultaneously two objectives under several resource constraints. The model is only for the hierarchical series-parallel systems in which the elements of any subset of subsystems or components are connected in series or parallel and constitute a larger subsystem or total system. At the end of the study, the performance of the proposed approach was evaluated by a numerical example.

System reliability analysis for kinematic performance of planar mechanisms

Based on the reliability and mechanism kinematic accuracy theories, we propose a general methodology for system reliability analysis of kinematic performance of planar mechanisms. The loop closure equations are used to estimate the kinematic performance errors of planar mechanisms. Reliability and system reliability theories are introduced to develop the limit state functions (LSF) for failure of kinematic performance qualities. The statistical fourth moment method and the Edgeworth series technique are used on system reliability analysis for kinematic performance of planar mechanisms, which relax the restrictions of probability distribution of design variables. Finally, the practicality, efficiency and accuracy of the proposed method are demonstrated by numerical examples.

Time Series Analysis for Vibration-Based Structural Health Monitoring:A Review

Structural health monitoring(SHM)is a vast,interdisciplinary research field whose literature spans several decades with focusing on condition assessment of different types of structures including aerospace,mechanical and civil structures.The need for quantitative global damage detection methods that can be applied to complex structures has led to vibration-based inspection.Statistical time series methods for SHM form an important and rapidly evolving category within the broader vibration-based methods.In the literature on the structural damage detection,many time series-based methods have been proposed.When a considered time series model approximates the vibration response of a structure and model coefficients or residual error are obtained,any deviations in these coefficients or residual error can be inferred as an indication of a change or damage in the structure.Depending on the technique employed,various damage sensitive features have been proposed to capture the deviations.This paper reviews the application of time series analysis for SHM.The different types of time series analysis are described,and the basic principles are explained in detail.Then,the literature is reviewed based on how a damage sensitive feature is formed.In addition,some investigations that have attempted to modify and/or combine time series analysis with other approaches for better damage identification are presented.

An Analysis of Reliability and Competitiveness of a Corporation in China

This paper, by using the theory of reliability, studies operating of a corporation in China. Firstly, the paper clarifies new characteristics of a corporation in China. Secondly, the paper analyses three kinds of systems that include series connection model, parellel connection model and mixed connection model. In the end, the paper studies four kinds of corporations and makes a forecast that are market-oriented corporation, innovation-oriented market, scale-oriented market and power-oriented market in China.

一种基于蒙特卡洛方法的配电网概率可靠性快速计算方法

配电网的概率可靠性能够弥补传统可靠性指标的期望值仅从均值角度衡量系统可靠性的不足,但随着配电网规模扩大以及数据量的剧增,能够同时兼顾计算准确性与计算速度的概率可靠性计算方法是亟待研究的。为此,提出一种基于蒙特卡洛方法的配电网概率可靠性快速计算方法,利用改进三点估计法以及三阶多项式正态变换,在保留输入变量相关性的同时有效缩减输入样本点规模,并采用级数展开得到概率可靠性。首先采用改进三点估计法,在独立标准正态空间内选取样本点,再通过三阶多项式正态变换将其转换为原始变量空间的样本点;接着采用序贯蒙特卡洛方法,在考虑孤岛划分的情况下对样本点进行可靠性计算;最后通过Edgeworth级数展开,得到可靠性指标的概率分布。对改进的IEEE-RBTS Bus6的F4馈线进行算例分析,结果表明:该文所提方法与传统蒙特卡洛方法的配电网系统可靠性计算结果之间仅存在2.195%的最大偏差,而该文所提方法计算时间仅为传统蒙特卡洛方法的1.05%,证明该文所提方法在保证较高精度的同时可以显著提升计算速度。

串联系统小样本可靠度直接评估方法

建立了一种串联系统小样本可靠度直接评估方法,能够根据子系统的可靠度置信限直接给出串联系统的可靠度置信限,解决了目前常用的LM法和MML法等传统方法需将信息量较大的连续型分布的子系统试验数据转换为信息量较小的成败型数据,造成试验信息大量丢失,导致可靠度评估精度不高或偏于危险的问题。在此基础上,针对工程上许多成败型试验转计量型试验的机构都是正态分布串联系统的情况,建立了正态分布串联系统小样本可靠度直接评估方法,该方法能够根据子系统的小样本计量型数据对串联系统可靠度进行高精度评估。大量的Monte Carlo模拟验证和实例计算结果表明,传统方法在小样本情况下误差较大,甚至无法满足置信度要求,本文方法则不仅能够满足置信度要求,而且评估精度更高。此外,本文方法对工程上常用的指数分布、 Weibull分布和正态分布等连续分布均适用。

基于贝叶斯网络时序模拟的综合能源系统可靠性评估

针对现有可靠性评估方法存在的计算量大以及系统薄弱环节难以识别的问题,提出一种基于贝叶斯网络时序模拟的综合能源系统可靠性评估方法。针对热力子系统网络热能流传输延时及负荷侧热惯性,建立“动态-延时”逻辑关系模型,分析该逻辑下贝叶斯网络时序模拟过程,通过算例验证所建热力子系统贝叶斯网络的正确性。根据电-气-热多能耦合的综合能源系统各元件的逻辑关系,运用改进的贝叶斯网络时序模拟推理算法对综合能源系统的可靠性指标进行评估,并分析多能互补及储能装置对系统可靠性的影响。结果表明:相较于单一运行子系统,在多能流子系统耦合形成的综合能源系统中,各子系统经耦合元件互相进行能量转化,其整体运行可靠性更高。同时可借助贝叶斯网络模型能实现反向诊断的特点,判断出综合能源系统结构弱点所在。

滚动轴承振动性能保持可靠度及其影响因素的试验分析

振动性能时间序列的波动指标影响滚动轴承最佳振动性能状态的变异概率,进而影响其振动性能保持可靠度。将振动性能时间序列平分为多段,找出轴承最佳振动性能状态时间序列(本征序列),基于统计学理论计算时间序列数据样本的各个波动指标,运用泊松计数原理计算各个时间序列对应时间段内轴承最佳振动性能状态的变异概率和振动性能保持可靠度;分析变异概率、振动性能保持可靠度与各个波动指标的线性相关性及均值化灰关联度,对影响变异概率和振动性能保持可靠度的波动指标进行排序;基于主成分分析法确定主变量的波动指标,建立多因素回归分析模型,根据检验结果判定这些指标对变异概率和振动性能保持可靠度的影响。案例1和2的结果表明,有些波动指标对变异概率和振动性能保持可靠度的影响既有线性的也有非线性的,而且其相互作用也有一定的影响。