Nonlinear Mixed-Effects Models for Repairable Systems Reliability

Mixed-effects models,also called random-effects models,are a regression type of analysis which enables the analyst to not only describe the trend over time within each subject,but also to describe the variation among different subjects.Nonlinear mixed-effects models provide a powerful and flexible tool for handling the unbalanced count data.In this paper,nonlinear mixed-effects models are used to analyze the failure data from a repairable system with multiple copies.By using this type of models,statistical inferences about the population and all copies can be made when accounting for copy-to-copy variance.Results of fitting nonlinear mixed-effects models to nine failure-data sets show that the nonlinear mixed-effects models provide a useful tool for analyzing the failure data from multi-copy repairable systems.     

Optimal Age Replacement Policy with Replacement Occurrence While the Warranty is in Effect

This study considers an age replacement policy(ARP) for a repairable product with an increasing failure rate with and without a product warranty. As for the warranty policy to consider in association with such an age replacement policy, we adapt a renewable minimal repair-replacement warrant(MRRW) policy with 2D factors of failure time of the product and its corresponding repair time. The expected cost rate during the life cycle of the product is utilized as a criterion to find the optimal policies for both with and without the product warranty. We determine the optimal replacement age that minimizes the objective function which evaluates the expected cost rate during the product cycle and investigate the impact of several factors on the optimal replacement age. The main objective of this study lies on the generalization of the classical age replacement policy to the situation where a renewable warranty depending on 2D factors is in effect. We present some interesting observations regarding the effect of relevant factors based on numerical analysis.     

���ڻ�ɫ�в�GM(1,N)ģ�͵Ľ�ͨ�����ݻָ��㷨

交通检测器采集的原始交通数据的质量会直接影响智能交通系统的后续效益.本文针对采集的交通数据普遍存在的故障问题,以交叉口检测器的交通流数据为研究对象,提出基于灰色残差GM(1,N)模型的数据修复算法.首先针对交叉口四个路口的交通流进行灰色相关分析,然后建立灰色GM(1,N)模型对故障数据进行预测修复,并进行了残差修正,提高了修复数据的精度.分析结果表明,提出的故障数据灰色残差GM(1,N)模型算法是可行的,可以更好地解决因为数据故障而对后续处理带来的困难,同时也为其他领域的故障数据修复提供借鉴.     

Numerical simulation to reliability analysis of fault-tolerant repairable system

In the traditional method for the reliability analysis of fault-tolerant system, the system structure is described by means of binary decision diagram (BDD) and Markov process, and then the reliability indexes are calculated. However, as the size of system augments, the size of state space will increase exponentially. Additionally, Markov approach requires that the failure and repair time of the components obey an exponential distribution. In this study, by combining dynamic fault tree (DFT) and numerical simulation based on the minimal sequence cut set (MSCS), a new method to evaluate reliability of fault-tolerant system with repairable components is proposed. The method presented does not depend on Markov model, so that it can effectively solve the problem of the state-space combination explosion. Moreover, it is suitable for systems whose failure and repair time obey an arbitrary distribution. Therefore, our method is more flexible than the traditional method. At last, an example is given to verify the method.     

Reliability analysis of multi-state repairable system with dynamic transition probabilities

Inadequate maintenance decisions lead to incremental overall costs. In order to minimize costs in maintenance of the multi-state repairable system, we model a preventive maintenance (PM) scheme of the multistate repairable system using non-Markov process. The periodically decreasing reliability model of the non-Markov dynamic system with dynamic transition probabilities is established to satisfy the probability change. The diesel engine system is taken as an example to illustrate the model. The reliability of the diesel engine is analyzed and its PM scheme is worked out. RENO software is used to simulate the diesel engine system. The maintenance cost of components and the optimal PM interval data of the system are obtained by using the minimal average cost as the objective function. The adaptability of PM is judged, and the optimal PM scheme is presented.     

工艺数字化产品售后工艺服务子系统

阐明了面向产品全生命周期的工艺数字化系统和售后工艺服务于系统的重要意义，提供了售后工艺服务子系统模型，并讨论了产品使用与保养，故障诊断，折装与维修，报废与回收等方面的相关工艺工作及其管理问题。     

���ܽ�ͨ���������ۺϽ�ͨ��Ϣ����——“��ͨ7+1��̳”����ʮ�λ����ʵ

本次论坛针对城市交通的发展需要,探讨了智能交通物联网和综合交通信息服务问题,认为智能交通物联网就是将技术实用、理念先进的物联网技术,融合各种先进的智能交通技术以及人工智能等技术,运用于交通管理、信息服务和车辆控制等智能交通领域,以达到人、车、路和环境之间的和谐统一,从而形成高效、准时、舒适、低碳的城市综合运输系统.在综合交通信息服务方面,强调服务内容的深刻性和个性化,以及服务模式的人性化、智能化.强调使综合交通物联网信息最大限度地与其他各类相关信息系统实现互联互通,进而催生新的应用和服务.     

VRS动态随机模型建模方法的综合比较与分析

为寻求一种最优的VRS(虚拟参考站)动态随机模型建模方法,阐述了实时动态数据处理系统中4种随机模型——标准随机模型、高度角相关模型、SNR(信噪比)模型和自适应模型的建模原理;从验后单位权方差、ADOP(模糊度精度因子)、模糊度有效性检验(F-ratio)和滤波残差等多个角度综合分析了各模型在VRS系统中的有效性及其优劣,并从统计学的角度和基于模型自身缺陷的分析,提出了模型改进的方案.结果表明,自适应模型的滤波残差和验后单位权方差分别在0和1附近波动,具有明显的白噪声特性,其在ADOP的计算能力上也有明显优势,但在F-ratio的计算能力上与其它模型相当.综合而言,自适应模型应作为VRS实时动态随机模型建模首选.     

���������ھ�ij��н�ͨ��Ϣ������άģ��

经过规范化的发展,已经涌现出不少成熟的企业信息集成(EII)模型,而城市交通信息集成（UTII）方面还缺乏规范、成熟的模型。基于此,本文从流程再造、数据交互以及数据挖掘三个方面,提出了一种城市交通信息集成三维模型（3D-UTII)。这三个维度的集成即为：基于流程再造的交通信息系统内部的深度集成（DDII）,基于异构数据库技术的交通信息系统间的广度集成（EDII）,以及基于数据挖掘技术的分析式集成（ADII）。本文对这三个维度的实施框架和具体实现技术分别做出了进一步阐述,最后使用北京市奥运交通应急系统的信息集成方案为实例对模型的实施做出了说明和验证。     

西南地区海港竞争力对贵州陆港的引力分析

陆港建设可以完善西南地区的外贸运输体系,改变西南地区出口集装箱选择海港的行为,为了分析贵州陆港建设后,西南地区出口集装箱选择海港的行为,基于万有引力定律,开发了海港对陆港的吸引力模型,建立了海港综合竞争力评价体系,并基于层次分析法提出了计算海港综合竞争力的方法。以西南地区可利用的港口为对象,分析了西南地区出口集装箱经由贵阳陆港选择海港的概率,为西南地区的出海通道建设和海港的市场营销提供了理论依据。     

大型基础设施系统设计中的风险及概率

在大型基础设施系统中,不可避免地会出现重大的不确定性,因而,无法确保已建系统的安全性和可靠性.有功能失效甚至破坏的可能,同时也有相应的规避风险的措施.从实用角度出发,不确定性可以分为两大类:数据型(又称偶然型)不确定性和知识型(又称认知型)不确定性.前者可以通过对数据的观察来评估,而后者则需要主观判断.系统地分析了这两...     

随机选择修理工且修理延迟的可修系统的可靠性分析

研究了可随机选择修理工且修理延迟的可修系统．假定系统的寿命、延迟修理时间和修理时间均为广义指数分布．通过引进补充变量法并利用广义马尔可夫过程和拉普拉斯变换方法求出了系统的可用度、可靠度、维修频度和系统等待修理的概率等重要可靠性指标．     

ITS����ᾭ�÷�չЭ���������о�

智能交通系统（ITS）与社会经济发展协调度是ITS建设投资的重要参考依据. 由于ITS与社会经济发展数据是非参数化数据,因此本文选择数据包络分析方法评价ITS与社会经济发展的协调性. 结合交通系统和社会经济系统特性,本文提出了ITS与社会经济发展协调性评价的初始指标体系框架;接着根据数据包络分析方法的要求及相关数据的可采集性,从初始指标体系框架中选择关键指标构建了最终的评价指标体系. 最后,结合北京市的实际数据,验证了评价方法和评价模型的可行性,指出北京市ITS与社会经济发展之间的关系,并提出了加强ITS建设的建议.     

Bayesian reliability assessment and degradation modeling with calibrations and random failure threshold

A degradation model with a random failure threshold is presented for the assessment of reliability by the Bayesian approach. This model is different from others in that the degradation process is proceeding under pre-specified periodical calibrations. And here a random threshold distribution instead of a constant threshold which is difficult to determine in practice is used. The system reliability is defined as the probability that the degradation signals do not exceed the random threshold. Based on the posterior distribution estimates of degradation performance, two models for Bayesian reliability assessments are presented in terms of the degradation performance and the distribution of random failure threshold. The methods proposed in this paper are very useful and practical for multi-stage system with uncertain failure threshold. This study perfects the degradation modeling approaches and plays an important role in the remaining useful life estimation and maintenance decision making.     

Nonlinear Modeling and Neuro-Fuzzy Control of PEMFC

The proton exchange membrane generation technology is highly efficient, and clean and is considered as the most hopeful “green” power technology. The operating principles of proton exchange membrane fuel cell （PEMFC） system involve thermodynamics, electrochemistry, hydrodynamics and mass transfer theory, which comprise a complex nonlinear system, for which it is difficult to establish a mathematical model and control online. This paper analyzed the characters of the PEMFC; and used the approach and self-study ability of artificial neural networks to build the model of nonlinear system, and adopted the adaptive neural-networks fuzzy infer system to build the temperature model of PEMFC which is used as the reference model of the control system, and adjusted the model parameters to control online. The model and control were implemented in SIMULINK environment. The results of simulation show the test data and model have a good agreement. The model is useful for the optimal and real time control of PEMFC system.     

Polling algorithm based on traffic burst characteristics of broadband wireless access systems

In this paper, we propose a novel polling algorithm to decrease the number of idle slots and collission slots during the polling cycle by evaluating the bandwidth request of the subscribe stations (SSs) in the next polling cycle for broadband wireless access (BWA) systems. We firstly analyze the feature of silent time intervals and deduce the Hurst index which symbolizes the degree of self-similarity and long-relative nature. Then we represent the inactive OFF time intervals by the Pareto model and estimate the shape parameter α by the group measured data. Finally we can evaluate the transmission probability of a silent SS before the next polling cycle. By this algorithm, we can find the optimal transmission opportunities for the base station (BS) to achieve the least collision or void timeslots in order to achieve the largest bandwidth efficiency. The theoretical analysis and simulation results show that this polling algorithm can improve the performance for BWA system.     

ITS共用信息平台的研究

针对目前智能交通各子系统独立应用,存在大量信息孤岛,信息无法充分利用的现状,分析了共用信息平台在数据交换、数据共享以及数据融合挖掘等方面的功能,提出了一种共用信息平台的体系结构,并着重分析了平台各模块的功能。该共用信息平台在实现智能交通系统各子系统的集成上具有良好的灵活性和可扩展性。     

ITS共用信息平台的研究

针对目前智能交通各子系统独立应用,存在大量信息孤岛,信息无法充分利用的现状,分析了共用信息平台在数据交换、数据共享以及数据融合挖掘等方面的功能,提出了一种共用信息平台的体系结构,并着重分析了平台各模块的功能。该共用信息平台在实现智能交通系统各子系统的集成上具有良好的灵活性和可扩展性。     

�Զ�������λϵͳ��GPRS��·���ܷ���

介绍了基于GPRS的自动车辆定位系统的数据链路，并结合GPRS数据用户的工作流程，介绍了实现链路的关键技术。从语音传输和数据传输两个方面给出了基于GPRS数据链路的自动车辆定位系统（AVLS）系统模型。着重对数据接入延时与语音负载、数据长度、数据发送间隔、系统容量等参数之间的关系进行了仿真分析。仿真结果表明,对于语音负载小、数据长度小的自动车辆定位系统，GPRS可以用来实现系统的大容量。