Ad hoc网络时钟同步研究*

为解决时钟同步方案存在依赖特殊节点以及算法精度不高等问题,在组网过程与自组网互同步相结合的基础上,完成网络节点的时钟同步,并通过测量网络延迟以提高同步精度.方案在一跳场景下验证,可将误差维持在15μs左右,提高了同步精度,并且本方案不需要特殊节点,各个节点只需要收到一个同步帧就可以自发地调整时钟,同步帧的开销小、实现简单,适用于多跳和灵活易变的Ad hoc网络.     

A pair of parallel differential magnetic‐field probes with high measurement accuracy and high electric‐field suppression ratio

Magnetic‐field probes can be used for electromagnetic interference measurement of high‐speed circuits. The main magnetic probe performance includes sensitivity, spatial resolution, electric‐field suppression ratio (EFSR), and measurement accuracy. In this article, a pair of differential magnetic‐field probes is proposed to improve measurement accuracy without reducing sensitivity. The proposed differential probes consist of two asymmetric loop probes, which are designed in the same plane and separated by a row of periodic vias. The proposed differential probes are fabricated under PCB process. High accuracy can be achieved by measuring difference between outputs of the two probes. In addition, EFSR can be improved by size optimization of the differential magnetic‐field probes. Simulation and measurement results show the operating bandwidth is from 100 MHz to 12 GHz, the measurement error is 3.4% and the EFSR is about 40 dB. The proposed probes have higher measurement accuracy and higher EFSR than the conventional single probe, and larger operation bandwidth than the stacked differential probes.     

10 kV用无源电子式电压传感器的应用研究

针对传统技术中采用电磁式CT互感器存在的不足,提出了适用于10 kV的无源电子式电压互感器。根据电压互感器的工作原理,介绍了10 kV无源电子式电压互感器在电能表检定装置方面的意义。进一步分析了无源电子式电压互感器在电力设备中应用的重要性和必要性,该技术能够有效地避免传统技术在电力线路信号传输和处理时带来附加误差,大大提高电能计量、保护和测量系统的精度,推进了电力系统朝向数字化、电子化、自动化、网络化的方向发展。实验表明,采用10 kV的无源电子式电压传感器与传统CT互感器相比,误差精度提高了10%以上。     

Conditional diagnosability and strong diagnosability of shuffle-cubes under the comparison model

The growing size of multiprocessor systems increases the vulnerability to component failures. It is crucial to locate and replace faulty processors to maintain the system's high reliability. Processor fault diagnosis is essential to the reliability of a multiprocessor system and the diagnosabilities of many well-known networks (such as hierarchical hypercubes and crossed cubes [S. Zhou, L. Lin and J.-M. Xu, Conditional fault diagnosis of hierarchical hypercubes, Int. J. Comput. Math. 89(16) (2012), pp. 2152–2164 and S. Zhou, The conditional diagnosability of crossed cubes under the comparison model, Int. J. Comput. Math. 87(15) (2010), pp. 3387–3396]) have been investigated in the literature. A system is t-diagnosable if all faulty nodes can be identified without replacement when the number of faults does not exceed t, where t is some positive integer. Furthermore, a system is strongly t-diagnosable if it is t-diagnosable and can achieve (t+1)-diagnosability except for the case where a node's neighbours are all faulty. In addition, conditional diagnosability has been widely accepted as a new measure of diagnosability by assuming that any fault-set cannot contain all neighbours of any node in a multiprocessor system. In this paper, we determine the conditional diagnosability and strong diagnosability of an n-dimensional shuffle-cube SQ_n, a variant of hypercube for multiprocessor systems, under the comparison model. We show that the conditional diagnosability of shuffle-cube SQ_n (n=4k+2 and k≥2) is 3n?9, and SQ_n is strongly n-diagnosable under the comparison model.     

深度信念网络在故障指示器检测中的应用

电子产品在生产过程中需进行产品检测,以故障指示器的检测为例,结合深度信念网络(DBN)技术实现了自动检测.深度信念网络由于其具有无监督预训练的优势,将其应用于实际系统,对现场的故障指示器视频图像的动作状态进行了分类实验.实验结果表明:深度信念网络分类算法相比于支持向量机(SVM)分类算法和BP分类算法有明显的优势,正确识别率达到了100％.该算法在产品检验的应用中满足生产测试的要求,且降低了人工测试的劳动强度,缓解了视觉疲劳问题.     

基于马尔可夫链的可信软件动态评估模型

软件可信度评估受主观经验、主观决策及有限理性的影响,评估结果的精确性和客观性无法得到全面保证。为了解决上述问题,本文利用马尔科夫连,以经典可信软件属性指标体系为基础,从软件层次属性的动态变化考虑提出了一种时间情境下的动态评估模型。通过模糊综合评判和层次分析法进行量化以确定子属性的权重和元属性的相对权重,应用马尔科夫过程构建各层级属性的内部定向转化概率模型,通过模糊算法得出最终的可信评估结果。结论表明,本文构建的模型,在一定程度上更加符合软件应用的实际情形,在逻辑上更具有说服力。实例也说明了本模型的科学性和有效性。     

30万吨横切生产线堆垛机控制程序优化

随着钢材市场的竞争日趋激烈,对产品质量的要求越来越高,首钢京唐热轧板厂横切30万吨生产线堆垛机的控制精度已不能满足目前的质量要求。为此对其自动化控制程序进行了优化、打包。经过自动控制程序的优化后,横切机组堆垛机自动控制程序及堆垛机运行正常,设备冲击缺陷和产品缺陷同时得到了控制,在提高生产率和产品质量的同时,获得了良好的经济效益。     

一种基于EEMD的新型谐波误差分析策略

针对电力系统中严重的谐波干扰问题,为提高其运行的安全有效性,去除谐波干扰并提高系统稳定性能成为研究热点。电网中常存在频率强烈波动或者白噪声强烈干扰的现象,虽说三谱线插值的FFT算法(基于Kaiser窗)的抗干扰能力很强,谐波参数估计也可以有较高的精准度,但是远不及使其与平均经验模态的总体水平来分解谐波的检测算法(EEMD)与直线度误差分析相结合。应用直线度误差来分析信号的谐波成分,有机结合了三谱线插值的FFT(基于Kaiser窗的)谐波检测分析法。通过对整体谐波分量的在线监测,不仅能够提高稳态信号的检测精度,还能提高系统的动态性能。本分析策略大限度地提高了计算精度以及系统稳定性。通过仿真分析得知,所述方法可以使系统具有较强的抑制频谱泄露能力,并能够显著降低栅栏效应的发生概率,进而使电力谐波信号的幅值误差、初相位误差和频率误差分别低于0.004 1%、0.002 4%和0.003 9%。     

协同过滤技术的改进研究

协同过滤算法应用于个性化推荐系统中取得了巨大成功,它是通过用户项目评分数据,以用户之间或者项目之间相互协作的方式来产生推荐。然而,邻居用户的相似度计算不精确一直是阻碍推荐系统推荐精度进一步提高的主要因素。从提高用户间相似度计算精度出发,提出了一种改进算法,该算法通过考虑不同特征、加强平均值影响、惩罚热门项目的比重,对用户的相似度计算方法进行改进,以期生成更加合理的邻居用户集,最后,根据评分预测公式进行预测,最终产生推荐。在MovieLens数据集上的实验表明,改进算法计算用户间的相似度更加精确,推荐算法的预测精确度有了显著提高。     

Comparing interpolation techniques for monthly rainfall mapping using multiple evaluation criteria and auxiliary data sources: A case study of Sri Lanka

Interpolating climatic variables such as rainfall is challenging due to the highly variable nature of meteorological processes, the effects of terrain and geography, and the difficulty in establishing a representative network of stations. While interpolation models are being adapted to include these effects, often the rainfall data contain significant gaps in coverage. In this paper, we evaluated rainfall data from an agro-ecological monitoring network for producing maps of total monthly rainfall in Sri Lanka. We compared four spatial interpolation techniques: inverse distance weighting, thin-plate splines, ordinary kriging, and Bayesian kriging. Error metrics were used to validate interpolations against independent data. Satellite data were used to assess the spatial pattern of rainfall. Results indicated that Bayesian kriging and splines performed best in low and high rainfall, respectively. Rainfall maps generated from the agro-ecological network were found to have accuracies consistent with previous studies in Sri Lanka.