Bayesian Decision Analysis of the Hazard Rate for a Two-Parameter Weibull Process

A two-parameter Weibull distribution is assumed to be the appropriate statistical life-model of an engineering device. The hazard rate of this device is the relevant quantity in terms of which statistical decisions are to be made. A Bayesian decision model is constructed around a conjugate probability density function for the Weibull hazard rate. Prior, posterior, and preposterior analysis of this decision model are discussed. The results indicate the rational decision before and after sampling, and permit the optimization of sequential single-item sampling schemes. Such schemes are of particular importance in the reliability testing of high-cost equipment.     

融合多源信息的维纳过程性能退化产品的可靠性评估

 针对维纳过程性能退化产品,提出了一种有效融合先验退化信息、寿命数据以及现场退化数据的可靠性评估方法.首先利用Expectation-Maximization(EM)算法基于先验退化信息和寿命数据信息确定参数的先验分布;其次利用贝叶斯方法对参数进行更新,并在此基础上进行可靠性评估.该方法能根据现场退化数据不断地对可靠性进行更新,实现对产品可靠性的实时评估.最后通过金属化膜电容器可靠性评估实例验证了该方法的适用性和有效性.     

Bayes credibility intervals for the left-truncated exponential distribution

In this paper, a Bayes approach for statistical inference on life characteristics is proposed, when the underlying lifetime distribution has the left-truncated exponential density function. The proposed Bayes procedure provides credibility intervals on several life characteristics of great interest to the applied reliability engineer, when the experimental data are collected under a randomly censored sampling. The prior technical knowledge is expressed in the form of a prior density on the reliability level at a prefixed time in conjunction with an upper bound on the location parameter. The statistical properties of the proposed Bayes procedure are compared, via Monte Carlo simulation, with those of the Bayes procedure under the noninformative prior, when both correct and uncorrect prior information on the reliability is available. A numerical example is used for illustration and comparison.     

Cooperative Spectrum Sensing Scheme with Hard Decision Based on Location Information in Cognitive Radio Networks

Without an efficient way to achieve the reliability of the decision, the implementation of weighted data fusion is limited in the hard decision combination for cooperative spectrum sensing. To address this problem, a new cooperative spectrum sensing scheme based on the location information of the primary user (PU) and cognitive radio (CR) is proposed. In the new scheme, depending on the location information, the channel condition between the PU and each CR is obtained at the fusion center (FC), with which the local sensing reliability is first achieved. Then we calculate the transmission reliability between the CR and FC. Based on both the local sensing reliability and the transmission reliability, the combining weighting factor is determined for optimal data fusion. On the basis of this proposed scheme, we study the global sensing false alarm and detection probabilities, derive the expressions to obtain the optimal local sensing threshold, and perform an error analysis that demonstrates the impact of imperfect channel knowledge. Using both analytical and simulation methods, we find that the proposed scheme achieves better performance compared with the conventional logical fusion rules in the hard decision combination for cooperative spectrum sensing.     

Reliability analysis of a finite range failure model

The Bayes estimates of reliability and hazard rate functions of the finite range failure model (1) have been developed based on life tests that are terminated at a preassigned time point taking the order of observations into consideration. For the parameter involved, the priors gamma, Weibull and log normal densities have been considered. The importance of the distributions, considered here as priors, in the theory of reliability has led the authors to use them as prior distributions.     

Bayesian可靠性评估中多源信息融合的概率模型方法

在Bayesian可靠性评估理论中,验前分布的获取和表示是一个关键问题.针对工程实践中遇到的验前信息的多源性.给出了一种基于概率模型的多源异总体验前分布的融合方法,并通过仿真实例证明了该方法的有效性.     

基于ATSC接收机的双模盲均衡算法设计

提出一个新的双模盲均衡算法,这个算法在传统的双模恒模算法(DMCMA)的基础上引入维特比软判决器输出可信度信息.根据这个可信度,动态调整在DMCMA的两个模式之间切换的判决区域,进一步提高模式切换的准确性.仿真结果表明动态判决区域双模盲均衡算法的性能有较大的提高.     

Life Distributions Derived from Stochastic Hazard Functions

Most of the familiar time-to-failure distributions used today are derived from hazard functions whose parameters are assumed constant. An unconditional time-to-failure distribution is derived here by assuming that a parameter of a classical failure distribution (viz., exponential and Weibull) is a random variable with a known distribution. With the use of the derived compound distributions and Bayesian techniques, it is possible to join the test data with prior information to arrive at a combined, and possibly superior, estimate of reliability. The prior distributions considered here are the two-point, the uniform, and the gamma. Conceptually, such a scheme may be a more realistic model for describing failure patterns under specific conditions.     

The Philosophy and Mathematics of Bayes' Equation

The rudiments of Bayesian philosophy are introduced, and the mathematics of its application are surveyed; there is no uniformity of thought concerning either. The more extreme Bayesian philosophy, which allows subjective probabilities, is a means of plausible reasoning, or of making inferences, through inductive logic. Because inferences concerning reliability concepts are important in the decision process, this philosophy has a place in the reliability field. The difficulties of interpreting the probability function and of assigning prior distributions restrict the presentation of a unified philosophy. Thus, only techniques for describing prior probabilities under various circumstances can be given. Application of the Bayesian approach depends on how the reliability decision is conceptualized.     

Dynamic Reliability Model of Components Under Random Load

The dynamic reliability model of components is developed using order statistics, and probability differential equations. The relationship between reliability and time, and that between the hazard rate and time, are discussed in this paper. First, according to the statistical meaning of random load application, the cumulative distribution function, and probability density function of equivalent load, when random load is applied at multiple times, are derived. Further, the reliability model of components under repeated random load, is developed. Then, the loading process described under a Poisson process, the dynamic reliability model of components without strength degeneration, and that with strength degeneration are developed respectively. Finally, the reliability, and the hazard rate of components are discussed. The result shows that, when strength doesn't degenerate, the reliability of components decreases over time, and the hazard rate of components decreases over time, too. When strength degenerates, the reliability of components decreases over time more obviously, and the hazard rate curve is bathtub-shaped.      

A multistage motion vector processing method for motion-compensated frame interpolation.

In this paper, a novel, low-complexity motion vector processing algorithm at the decoder is proposed for motion-compensated frame interpolation or frame rate up-conversion. We address the problems of having broken edges and deformed structures in an interpolated frame by hierarchically refining motion vectors on different block sizes. Our method explicitly considers the reliability of each received motion vector and has the capability of preserving the structure information. This is achieved by analyzing the distribution of residual energies and effectively merging blocks that have unreliable motion vectors. The motion vector reliability information is also used as a prior knowledge in motion vector refinement using a constrained vector median filter to avoid choosing identical unreliable one. We also propose using chrominance information in our method. Experimental results show that the proposed scheme has better visual quality and is also robust, even in video sequences with complex scenes and fast motion.     

Modelling human performance reliability in a two stage combined manual and decision task

Based on an experimental study in a two stage combined manual and decision task, a stochastic model for the controllability function of human performance is presented. This measure of human performance is formulated from the random variables which led to the formulation of the reliability and correctability functions. Experimental studies show that the time to committing error follows exponential distribution and the time to error correction follows log normal distribution. Accordingly variation in human performance measures in terms of reliability, correctability and controllability are explained at various levels (3 levels of information load (H) and 3 levels of time lag (TL))of experimental conditions.     

基于序列检测的块判决辅助Turbo均衡器

该文针对高斯分布假设条件下逐符号检测均衡器的不足,提出了一种基于序列检测的块判决辅助Turbo均衡器(Turbo-BDAE)。新算法利用译码全信息估计发送序列,提高了序列估计的可靠性,引入软判决可以降低硬判决引起的错误扩散,同时结合序列检测为均衡器输出的后验概率(APP)估计提供了更可靠的信息。仿真表明,该均衡器在保持相近复杂度的同时,进一步提升了均衡系统性能,优于逐符号LMMSE均衡器和硬反馈BDFE。     

Customer-Rush Near Warranty Expiration Limit, and Nonparametric Hazard Rate Estimation From Known Mileage Accumulation Rates

Time or mileage data obtained from warranty claims are generally more accurate for hard failures than for soft failures. For soft failures, automobile users sometimes delay reporting the warranty claim until the warranty coverage is about to expire. This results in an unusually high number of warranty claims near the end of warranty coverage. Because such a phenomenon of customer-rush near the warranty expiration limit occurs due to user behavior rather than due to the vehicle design, it creates a bias in the warranty dataset. Design improvement activities that use field reliability studies based on such data can potentially obtain a distorted picture of the reality, and lead to unwarranted, costly design changes. Research in the area of field reliability studies using warranty data provides several methods for warranty claims resulting from hard failures, and assumes reported time or mileage as actual time or mileage at failure. In this article, the phenomenon of customer-rush near the warranty expiration limit is addressed for arriving at nonparametric hazard rate estimates. The proposed methodology involves situations where estimates of mileage accumulation rates in the vehicle population are available. The claims influenced by soft failures are treated as left-censored, and are identified using information in technician comments about the repair carried out plus, if required, a more involved engineering analysis of field returned parts. Maximum likelihood estimates for the hazard function and their confidence limits are then obtained using Turnbull's iterative procedure. An application example illustrates use of the proposed methodology.     

Optimal design of reliable network systems in presence of uncertainty

In practice, network designs can be based on multiple choices of redundant configurations, and different available components which can be used to form links. More specifically, the reliability of a network system can be improved through redundancy allocation, or for a fixed network topology, by selection of highly reliable links between node pairs, yet with limited overall budgets, and other constraints as well. The choice of a preferred network system design requires the estimation of its reliability. However, the uncertainty associated with such estimates must also be considered in the decision process. Indeed, network system reliability is generally estimated from estimates of the reliability of lower-level components (nodes & links) affected by uncertainties. The propagation of the estimation uncertainty from the components degrades the accuracy of the system reliability estimation. This paper formulates a multiple-objective optimization approach aimed at maximizing the network reliability estimate, and minimizing its associated variance when component types, with uncertain reliability, and redundancy levels are the decision variables. In the proposed approach, Genetic Algorithms (GA) and Monte Carlo (MC) simulation are effectively combined to identify optimal network designs with respect to the stated objectives. A set of Pareto optimal solutions are obtained so that the decision-makers have the flexibility to choose the compromised solution which best satisfies their risk profiles. Sample networks are solved in the paper using the proposed approach. The results indicate that significantly different designs are obtained when the formulation incorporates estimation uncertainty into the optimal design problem objectives.     

Weibull分布下的系统可靠性评估方法研究

在Weibull分布的定时截尾样本中,对可靠性、可靠寿命和失效率这3种参数的验前分布及形状参数的验前信息进行了分析。论述了结合熵损失函数来求得系统可靠度及寿命的Bayes点估计和置信下限,为大型系统的可靠性评估提供了一种重要的理论依据。     

A Unified Method for Analyzing Mission Reliability for Fault Tolerant Computer Systems

A reliability model is proposed and evaluated for a fault tolerant computer system which consists of multiple classes of modules and allows for degraded modes of performance. Each module of a given class has both an active and a passive hazard rate; constant hazard rates are assumed for active and dormant failures, and the given class may operate either in N Modular Redundancy (NMR: n + 1 out of 2n + 1 = N) or as a standby sparing system. The model allows for mission-phase changes at deterministic time points when the numbers of modules per class can be changed. The analysis proceeds by generalizing the notions of standby and NMR redundancy, which for N = 3 is TMR (Triple Modular Redundancy), into a concept called hybrid-degraded redundancy. The probabilistic evaluation of the unified redundancy concept is then developed to yield, for a given modular class, the joint distribution of success and the number of nonfailed modules from that class, at special times. With this information, a Markov chain analysis gives the reliability of an entire sequence of phases (mission profile).     

Bayes' Equation, Reliability, and Multiple Hypothesis Testing

The rudiments of applying Bayes' Equation to hypotheses concerning reliability are introduced in a simple manner. The application is a means of obtaining posterior probabilities, for the reliability hypotheses, which are consistent with the prior beliefs and the available test results. The posterior distributions, from which decision theory could formally arrive at optimal estimates, are greatly dependent on the prior distributions. Thus, the discussion centers about the desired properties of a prior and its effects on the posterior for various data situations. Formulations for both continuous-conjugate and discrete representations of the prior beliefs are discussed and contrasted. The use of discrete priors offers many advantages over the use of continuous-conjugate priors.     

Bayesian estimation of reliability function and hazard rate

The Bayes estimates of reliability function and hazard rate function of the finite range failure model have been developed based on life tests that are terminated at a preassigned time point or after a certain number of failures have occurred, taking the order of observations into consideration. For the prior distribution of the parameter involved, the uniform, exponential and inverted gamma densities have been considered. As an example, failure data for a V600 indicator tube used in aircraft radar sets, which fit well the finite range failure model, have been considered as the current distribution for obtaining the Bayes estimates of the reliability function.     

基于决策树算法的信息系统数据挖掘研究

为了提高数据挖掘准确性和效率,文中提出了基于决策树算法的信息系统数据挖掘方法.以C4.5决策树算法计算属性的信息增益率和属性值的信息熵为基础,提出基于余弦相似度改进的C4.5决策树算法,若任意两个属性值的信息熵之差在阈值范围内,通过计算其余弦相似度合并在阈值范围内的属性值,并重新计算合并后属性的信息增益率,实现信息系统...