Bayesian Assessment for Reliability of Binomial Components Based on Information Fusion of Similar Products

A modified Bayesian reliability assessment method of binomial components was proposed by fusing prior information of similar products.The traditional Bayesian method usually directly used all the prior data,ignoring the differences between them,which might decrease the credibility level of reliability evaluation and result in data submergence.To solve the problem,a revised approach was derived to calculate groups of prior data's quantitative credibility,used for weighted data fusion.Then inheritance factor was introduced to build a mixed beta distribution to illustrate the innovation of new products.However,in many cases,inheritance factor was determined by Chi-square test that could not give out exact result with respect to rare failures.To make the model more precise,Barnard's exact test was suggested being used to calculate the inheritance factor.A numerical example is given to demonstrate that the modified method is successful and rational,while the classical method is too conservative and the traditional Bayesian method is too risky.

System reliability assessment based on Wiener process and competing failure analysis

Considering the dependence and competitive relation-ship between traumatic failure and degradation,the reliability assessment of products based on competing failure analysis is studied.The hazard rate of traumatic failure is regarded as a Weibull distribution of the degradation performance,and the Wiener process is used to describe the degradation process.The parameters are estimated with the maximum likelihood estimation（MLE）method.A reliability model based on competing failure analysis is proposed.A case study of the GaAs lasers is given to validate the effectiveness of the model and its solving method.The results indicate that if only the degradation failure is considered,the estimated result will be comparably optimistic.Meanwhile,the correlation between the degradation and traumatic failure has a great influence on the accuracy of reliability assessment.

Data processing of small samples based on grey distance information approach

Data processing of small samples is an important and valuable research problem in the electronic equipment test. Because it is difficult and complex to determine the probability distribution of small samples, it is difficult to use the traditional probability theory to process the samples and assess the degree of uncertainty. Using the grey relational theory and the norm theory, the grey distance information approach, which is based on the grey distance information quantity of a sample and the average grey distance information quantity of the samples, is proposed in this article. The definitions of the grey distance information quantity of a sample and the average grey distance information quantity of the samples, with their characteristics and algorithms, are introduced. The correlative problems, including the algorithm of estimated value, the standard deviation, and the acceptance and rejection criteria of the samples and estimated results, are also proposed. Moreover, the information whitening ratio is introduced to select the weight algorithm and to compare the different samples. Several examples are given to demonstrate the application of the proposed approach. The examples show that the proposed approach, which has no demand for the probability distribution of small samples, is feasible and effective.

Bayesian-based information extraction and aggregation approach for multilevel systems with multi-source data

The ever-increasing complexity of industry facilities has made the reliability analysis and assessment an imperative yet tough work. Motivated by practical engineering requirement, this paper develops a Bayesian-based information extraction and aggregation (BIEA) approach for system level reliability estimation of a complex system. It takes both subjective judgments and objective field outputs into consideration. Novel features of this approach is a unique information content based aggregation process, which allows a flexible application of this framework in separated modules on account for purpose. The coherency of which is guaranteed by the objective information content calculation. This work goes beyond the alternatives that deal with solely attributed data under ideal information circumstance, and investigates a more generic tool for real engineering application. Limitations embedded in traditional statistical modeling methods have been eliminated in a nature manner by information transition and integration. In addition, a double axis driving mechanism (DADM) for erecting the antenna of a satellite is demonstrated as case study for benefit illustration and effectiveness verification. © 2017 Beijing Institute of Aerospace Information.

A Modified Multi-data Fusion Method Based on D-S Theory

The D-S evidential reasoning algorithm is invalid when the evidence is completely contradicted. Therefore,a modified algorithm is proposed based on the elemental correlation and the influence of elemental weights in the evidence. The modified algorithm is more powerful ability to rectify errors and less computational complexity in the circumstance of multi-evidence fusion processing than those of the D-S evidential reasoning algorithm.

基于OBE理念的农业信息数智化处理研究

基于OBE理念,设计了农业信息系统。首先,基于ZigBee技术设计传感器网络,传感器检测数据通过ZigBee网络和运营商基站上传到农田信息服务器,对同类传感器数据进行融合后,得到同类传感器数据表征值;然后,对6类传感器的表征值进行融合,得到农田环境综合评估结果。设计微信小程序,显示农田中6类传感器的表征值,进而显示农田环境综合评估结果。对传感器上传数据可靠性进行测试,与实地测试对比,误差区间为[0,0.3℃];对微信小程序显示效果进行验证,小程序可以清晰地将农田环境综合评估结果展示给用户。

The Credit-Risk Decision Mechanism on Fixed Loan Interest Rate with Imperfect Information

In this paper, decision mechanism of credit-risk for banks is studied when the loan interest rate is fixed with asymmetry information in credit market. We give out the designs of rationing and non-rationing on credit risky decision mechanism when collateral value provided by an entrepreneur is not less than the minimum demands of the bank. It shows that under the action of the mechanism, banks could efficiently identify the risk size of the project. Finally, the condition of the project investigation of bank is given over again.

The Combination Operator of Information Sources by a New Expressive Matrix

The multi-sensors fusion refers to the synergistic combination of sensory data from multiple sensors to provide more accurate and reliable information. The potential benefits of the Fusion are multi-sensors’ redundancy and extra information acquired. The fusion of redundant information can reduce the overall uncertainty and thus helps to provide information specified more precisely. Several sensors providing redundant information can also be used to increase reliability in the case of error, omission or failure of sensors. The combination operators are exponential and are more complex in terms of calculation;the Dempster-Shafer operator is exponential for more than three (3) information sources?[1] [2]. Our work focuses on the definition of another formulation of this operation, and puts it in a matrix form to illuminate the computational complexity, more precision guaranty and a minimal execution time. We propose to use each information source in a form of a matrix, which contains 0 value in lines that do not contain the masses (m(Ai) = 0) or once m(Ai) is not null (m(Ai) ≠ 0). The use of this expressed matrix attempts to ameliorate Dempster-Shafer operator via initialing either a criterion or criteria sources’ solution, increasing the efficiency of the Dempster-Shafer operator and facilitates the combination among the sources. We evaluate our approach by conducting a case study for showing the effectiveness of this matrix.

Algorithm for Multi-laser-target Tracking Based on Clustering Fusion

Multi-laser-target tracking is an important subject in the field of signal processing of laser warners. A clustering method is applied to the measurement of laser warner, and the space-time fusion for measurements in the same cluster is accomplished. Real-time tracking of multi-laser-target and real-time picking of multi-laser-signal are introduced using data fusion of the measurements. A prototype device of the algorithm is built up. The results of experiments show that the algorithm is very effective.

基于知识与AW-ESN融合的烧结过程FeO含量预测

氧化亚铁(FeO)含量是衡量烧结矿强度和还原性的重要指标,烧结过程FeO含量的实时准确预测对于提升烧结质量、优化烧结工艺具有重要意义.然而烧结过程热状态参数缺失、过程参数波动频繁给FeO含量的高精度预测带来巨大的挑战,为此,提出一种基于知识与变权重回声状态网络融合(Fusion of data-knowledge and adaptive weight echo state network, DK-AWESN)的烧结过程FeO含量预测方法.首先,针对烧结过程热状态参数缺失的问题,建立烧结料层最高温度分布模型,实现基于料层温度分布特征的FeO含量等级划分;其次,针对烧结过程参数波动频繁的问题,提出基于核函数高维映射的多尺度数据配准方法,有效抑制离群点的影响,提升建模数据的质量;最后,针对烧结过程数据驱动模型缺乏机理认知致使模型预测精度不高的问题,将过程数据中提取得到的FeO含量等级知识与AW-ESN (Adaptive weight echo state network)结合,建立DK-AWESN模型,有效提升复杂工况下FeO含量的预测精度.现场工业数据试验表明,所提方法能实时准确地预测烧结过程FeO含量,为烧结过程的智能化调控提供实时有效的FeO含量反馈信息.

某型舰载电子产品小子样可靠性评估研究

可靠性评估是对产品可靠性水平进行评价,对产品可靠性要求进行验证的重要方法与手段。为解决装备研制过程中遇到的小子样可靠性评估问题,引入环境因子和信息融合的概念,提出一种确定环境因子的方法和步骤。首先,给出指数分布产品基于手册预计法的环境因子计算方法和步骤;然后,结合工程实例展示了产品环境因子具体的计算过程;最后,借助环境因子达到了不同环境条件下可靠性数据信息融合的目的,实现了产品的可靠性综合评估,解决了产品小子样可靠性评估的问题。实例结果表明,所提可靠性评估方法能有效融合不同环境下的可靠性数据信息,有效提高可靠性评估的准确度,方法合理可行,便于工程应用。

航天发射特征事件综合和弹道融合策略优化研究与应用

特征事件综合和弹道融合是航天发射过程中最为重要的一项工作,通过特征事件发生时间和火箭飞行弹道可直观地反映出运载火箭的飞行状态。因此,为了进一步提高特征事件综合和弹道融合效果,基于遥、外测量信息,分别对参与特征事件综合和弹道融合的信息源进行分类及其影响因素进行分析,并提出了相应的信息融合策略。通过采用优化的融合策略,可进一步提高特征事件时间解算的准确性和实效性,提升弹道融合的效果,满足航天发射飞行态势显示和安全控制的任务需求。

基于多传感器信息融合的AGV自主无轨导航技术

传统的物料搬运AGV机器人不能进行自主规划行走路径,也不能满足智能制造和数字化工厂对AGV进行科学调度、自动避障、安全可靠且不发生阻设的要求。因此,文章基于多模态传感器数据处理、SLAM地图构建等多重信号融合的原理和方法,提出了一种多传感器信息融合的AGV自主无轨导航技术,设计了AGV实物样机,并进行实验验证。结果表明,在无轨复杂场景情况下,AGV机器人的导航定位精度优于1 mm,重复定位精度优于2 mm,满足智能制造和数字化工厂对AGV的自主导航控制要求。

基于多源数据的郑州市内涝风险评估

城市内涝风险评估是防控与管理城市内涝灾害、减少灾害损失的有效手段。基于内涝风险评估框架“H(危险性)-E(暴露性)-V(脆弱性)”,选取了12个评估指标,包括遥感数据、POI数据与传统的社会经济与人口数据等多源数据。结合层次分析法(AHP)和地理信息系统(GIS)空间分析方法,构建了基于多源数据的城市内涝风险评估模型。结果表明:郑州市中心城区内涝风险整体上呈现出从中心区域的高风险逐渐向四周降低的趋势。高风险和次高风险区主要分布在郑州市主城区中心区域、中原区中部和金水区东部。次低风险和低风险区主要分布在惠济区北部和二七区西南部的山区。

面向实时多源信息融合的分布式系统设计与实现

随着信息技术的快速发展,实时多源信息融合已成为学术界和工业界的研究热点。文中针对传统信息融合系统存在的响应延迟高、可扩展性差等问题,提出了一种面向实时多源信息融合的分布式系统设计方案。该方案集成了高性能数据采集、实时数据传输、分布式数据处理和可视化等关键模块。文中详细阐述了各模块的设计原理和技术实现,并通过实验对系统性能进行了全面评估。实验结果表明,该系统在低延迟、高吞吐等方面显著优于主流的分布式流处理框架,充分验证了所提方案的有效性,为实时多源信息融合领域提供了新的思路和技术支撑。

基于多源激光点云融合的建筑物BIM建模

阐述了激光点云技术的基本原理,强调了多源数据的融合对提高模型精度的重要性,分析了建筑信息模型(Building Information Modeling,BIM)的定义、发展及其与激光点云的结合。并提出了一种系统的BIM建模方法,包括点云数据的获取、融合、建模流程及精度评估。通过应用案例,验证了该方法的有效性和实际应用效果,以期为推动建筑信息化进程的智能化发展提供参考。

信息融合技术在可靠性评估中的应用

针对复杂大系统可靠性评估中所遇到的困难 ,提出了采用信息融合技术解决该问题的思路 ,并就其实现形式及途径加以探讨。通过分析信息融合技术和可靠性评估有关的特点 ,得出了信息融合技术必将推动可靠性评估发展的结论。

机械设备性能退化评估与预测研究综述

机械设备性能退化评估技术在提高设备的可靠性和利用率、缩短停机维修时间、实现设备主动维护和智能维护方面有着重要的意义,是故障诊断技术的重要组成部分。综述国内外机械设备性能退化评估与预测的理论和方法,将这些方法分为两类,基于物理模型的方法和基于数据驱动的方法,重点论述基于数据驱动的方法及取得的进展,主要包括基于统计理论方法和人工智能方法等,总结比较每种方法的优缺点,并对机械设备性能退化评估与预测技术的发展方向进行展望。

非线性步进加速退化数据的可靠性评估方法

针对步进应力加速退化试验(SSADT)场合下的非线性退化数据,考虑个体之间的性能退化差异,提出了基于Wiener过程的退化数据可靠性评估方法。首先,分析了步进应力加速退化试验过程及其性能退化数据模型。然后,运用非线性Wiener过程描述产品的非线性退化过程,采用时间尺度变换模型进行线性变换;将Wiener过程的漂移系数随机化处理,提出考虑了个体差异的非线性退化数据建模;根据所收集的步进应力加速退化数据,采用两步极大似然估计法确定模型中的未知参数。最后,结合某激光器的实例对比分析表明,所建模型的拟合性较好,评估结果真实准确。

空中炸点三基阵声学定位技术研究

多基阵联合定位有助于提高声学定距的精度。采用3个立体五元阵、数据处理器、GPS时间标记器和无线传输设备的声学子站建立了三基阵定位系统,对空中炸点进行定位。立体五元阵能去除声速的影响,具有良好的方位角和俯仰角测量精度,将各个子站方向线在中心站进行数据融合得到空中炸点的位置。三基阵孔径与最佳定位高度关系的仿真结果表明最佳定位高度约是三基阵孔径的1/3.已开展的实验计算结果显示该系统定距相对误差小于3%,定距精度比单基阵有较大提高。