船舶主机故障巡回检测系统的自诊断技术

为了保证船舶主机故障巡回检测系统的自动化控制电路的可靠性,在系统采用容错技术的同时,还采用了自诊断技术.船舶主机故障巡回检测系统关系到船舶的安全航行,本文就系统自动化控制电路中的几个主要模块的诊断测试方法进行了研究.     

整合海事系统业务信息资源促进海事协同管理

海事系统提出了＂三个一＂和＂四型海事＂的建设目标。文章分析了海事业务信息系统现状与需求之间的差距,提出利用整合海事系统业务信息资源,全面提高信息化对海事协同监管、公共服务、决策支持的支撑水平。     

瓯江口航道海域溢油扩散数值模拟

首先建立了瓯江口海区平面二维潮流数学模型,根据现场实测资料对该数学模型进行验证.在此基础上对该海区的潮流场进行模拟,为溢油模型提供水动力基础数据,然后利用MIKE21 SA溢油模型对溢油泄露事故进行影响预测.研究结果表明,风的条件因素对油膜漂移轨迹的影响较大.在潮周期的不同阶段发生溢油事故时,溢油油膜漂移轨迹可能完全不...     

瓯江口航道二期治理潜堤工程三维潮流数值模拟

基于MIKE3技术平台,建立了瓯江口工程海域三维潮流数学模型.模型水平采用无结构的三角形网格系统,垂向采用(σ)坐标,较好地拟合了工程海域复杂的岛屿岸线和地形特征.采用现场实测水文资料,对瓯江口航道二期治理潜堤工程实施后的三维流场进行了模拟,并分析了工程实施后的影响.工程实施后,瓯江北口航道、沙头水道、小门水道、大门岛...     

高功率微波对无线电引信的效应分析

基于导弹无线电引信技术特点和工作机理,利用电磁耦合与相互作用基本理论,通过效应试验和理论分析相结合,研究高功率电磁脉冲对无线电引信干扰机理和效应。     

军用光电跟踪伺服控制技术分析

针对光电跟踪伺服系统所面对的新要求,在分析其控制原理及技术要求的基础上,从经典控制、现代控制和智能控制三个方面,对军用光电跟踪伺服系统中所采用的各种控制策略进行比较分析,阐述其各自的特点以及应用场合。在此基础上,探讨了光电跟踪伺服系统及其控制技术的发展趋势。这对于根据不同的技术要求选取合适的伺服控制方法,提供了理论参考,并具有一定的现实意义。     

螺旋桨桨叶宽度的双目视觉测量方法(英文)

Propeller blade width measurement has been extensively studied in the past using direct and indirect methods, and it plays a great role in determining the quality of the finished products. It has surveyed that previous techniques are usually time-consuming and erroneous due to a large number of points to be processed in blade width measurement. This paper proposes a new method of measuring blade width using two images acquired from different viewpoints of the same blade. And a new feature points matching approach for propeller blade image is proposed in stereo vision measurement. Based on these, pixel coordinates of contour points of the blade in two images are extracted and converted to real world coordinates by image algorithm and binocular stereo machine vision theory. Then, from the real world coordinates, the blade width at any position can be determined by simple geometrical method.     

基于AHP的港口安全风险模糊评判方法

针对我国港口安全风险的现状,从系统工程角度,采用层次分析法的基本原理,建立了港口安全风险分析模型,并运用模糊数学构建了隶属函数,求得港口安全风险的模糊评判矩阵,通过模糊评判获得了港口安全风险综合分数.结果表明,该评判方法能够科学合理地综合评价港口安全风险状况,为有关港口部门改善港口安全状况提供决策依据.     

Product substitution and dual sourcing under random supply failures

Product substitution can mitigate supply chain disruptions. However, it may not be very effective without multiple sourcing. In this paper, we consider a supply chain with two downward substitutable products. The products can be ordered from an unreliable supplier or a reliable but more expensive supplier. It is found that in an optimal sourcing policy the higher-grade product should be preferred over the lower-grade product. A sufficient condition is given for an optimal policy where only the higher-grade product is dual-sourced. The effect of substitution is contrasted with the non-substitution case. Numerical study shows the impact of demand variability and correlation on the effect of product substitution and the corresponding optimal sourcing policy.     

A bayesian dynamic linear model approach for real-time short-term freeway travel time prediction

This paper presents a Bayesian inference-based dynamic linear model (DLM) to predict online short-term travel time on a freeway stretch. The proposed method considers the predicted freeway travel time as the sum of the median of historical travel times, time-varying random variations in travel time, and a model evolution error, where the median is employed to recognize the primary travel time pattern while the variation captures unexpected supply (i.e. capacity) reduction and demand fluctuations. Bayesian forecasting is a learning process that revises sequentially the state of a priori knowledge of travel time based on newly available information. The prediction result is a posterior travel time distribution that can be employed to generate a single-value (typically but not necessarily the mean) travel time as well as a confidence interval representing the uncertainty of travel time prediction. To better track travel time fluctuations during non-recurrent congestion due to unforeseen events (e.g., incidents, accidents, or bad weather), the DLM is integrated into an adaptive control framework that can automatically learn and adjust the system evolution noise level. The experiment results based on the real loop detector data of an I-66 segment in Northern Virginia suggest that the proposed method is able to provide accurate and reliable travel time prediction under both recurrent and non-recurrent traffic conditions.