轮式水下无人探测器姿态估计仿真研究

轮式水下无人探测器在水下信息战、海底资源开发方面具有广阔的发展和应用前景。针对轮式水下无人探测器的姿态估计问题,提出了1种基于Stirling多元插值的DD1型滤波算法。仿真结果表明,该算法具有滤波精度高、数值稳定好的特点,能够更好地估计轮式水下无人探测器的姿态。     

红岩HY320桥壳机动传送线设计

某公司生产重卡铸钢桥壳,设计建设了一条桥壳自动传送线。桥壳热压装作业后,放入传送线专用托架小车,采用变频电机和摆线减速机提供动力,由链条带动实现桥壳传送和空小车从下方自动返回循环运行。本传送线采用了一种特别的结构方式,小车利用同一组滚轮在上下两层轨道中运行,且始终与链条相连,在传送线两端,空小车能够自动跟随传动链条作180°回转,小车滚轮自动脱离之前轨道然后进入到另一层轨道中运行。本传送线结构优化,占用空间少,经过实际生产验证反响良好。     

固定型交通检测器配置密度优化模型

分析检测器布设主要有2个目标,即数量最少、利用率最高;由于这2个目标间存在着“不可公度性”和“矛盾性”,构成了多目标决策问题,以此建立相应的多目标规划模型。此模型避免传统布设方法中存在的局限性和盲目性,可以较好地解决固定型检测器配置密度优化问题。     

Long short-term memory neural network for traffic speed prediction using remote microwave sensor data

Neural networks have been extensively applied to short-term traffic prediction in the past years. This study proposes a novel architecture of neural networks, Long Short-Term Neural Network (LSTM NN), to capture nonlinear traffic dynamic in an effective manner. The LSTM NN can overcome the issue of back-propagated error decay through memory blocks, and thus exhibits the superior capability for time series prediction with long temporal dependency. In addition, the LSTM NN can automatically determine the optimal time lags. To validate the effectiveness of LSTM NN, travel speed data from traffic microwave detectors in Beijing are used for model training and testing. A comparison with different topologies of dynamic neural networks as well as other prevailing parametric and nonparametric algorithms suggests that LSTM NN can achieve the best prediction performance in terms of both accuracy and stability.     

Data fusion algorithm for macroscopic fundamental diagram estimation

A promising framework that describes traffic conditions in urban networks is the macroscopic fundamental diagram (MFD), relating average flow and average density in a relatively homogeneous urban network. It has been shown that the MFD can be used, for example, for traffic access control. However, an implementation requires an accurate estimation of the MFD with the available data sources.Most scientific literature has considered the estimation of MFDs based on either loop detector data (LDD) or floating car data (FCD). In this paper, however, we propose a methodology for estimating the MFD based on both data sources simultaneously. To that end, we have defined a fusion algorithm that separates the urban network into two sub-networks, one with loop detectors and one without. The LDD and the FCD are then fused taking into account the accuracy and network coverage of each data type. Simulations of an abstract grid network and the network of the city of Zurich show that the fusion algorithm always reduces the estimation error significantly with respect to an estimation where only one data source is used. This holds true, even when we account for the fact that the probe penetration rate of FCD needs to be estimated with loop detectors, hence it might also include some errors depending on the number of loop detectors, especially when probe vehicles are not homogeneously distributed within the network.     

A data fusion approach for real-time traffic state estimation in urban signalized links

Real-time estimation of the traffic state in urban signalized links is valuable information for modern traffic control and management. In recent years, with the development of in-vehicle and communication technologies, connected vehicle data has been increasingly used in literature and practice. In this work, a novel data fusion approach is proposed for the high-resolution (second-by-second) estimation of queue length, vehicle accumulation, and outflow in urban signalized links. Required data includes input flow from a fixed detector at the upstream end of the link as well as location and speed of the connected vehicles. A probability-based approach is derived to compensate the error associated with low penetration rates while estimating the queue tail location, which renders the proposed methodology more robust to varying penetration rates of connected vehicles. A well-defined nonlinear function based on traffic flow theory is developed to attain the number of vehicles inside the queue based on queue tail location and average speed of connected vehicles. The overall scheme is thoroughly tested and demonstrated in a realistic microscopic simulation environment for three types of links with different penetration rates of connected vehicles. In order to test the efficiency of the proposed methodology in case that data are available at higher sampling times, the estimation procedure is also demonstrated for different time resolutions. The results demonstrate the efficiency and accuracy of the approach for high-resolution estimation, even in the presence of measurement noise.     

海上油气平台可燃气体探测器的布置、选型、安装和维护

在海上平台油气生产中，有效地利用可燃气体探测器来检测海上生产设备的泄漏状况，并及时采取相应的保护措施，是保证油气生产和人身安全的重要一环。但目前对海上油气平台可燃气体探测器工程设计的系统研究却鲜见于国内外的工程文献中，针对这一现状，在研究国内外现有规范和标准以及工程设计经验的基础上，通过分析可能产生泄漏的工艺设备、可燃气体性质和外部环境等因素来确定可燃气体探测器的物理位置，同时完成可燃气体探测器的选型，并根据现场的工作环境合理安装可燃气体探测器，最后总结探测器使用维护中需要注意的问题。对可燃气体探测器的布置、选型、安装和维护的系统总结和分析研究为海上平台火气系统的设计提供了技术支持，从而进一步保障海上油气平台的生产安全。     

道岔外锁闭装置在线探伤仪的研制

道岔外锁闭装置是重要的信号基础设备,直接关系到铁路运输的安全。介绍了一种外锁闭装置在线探伤仪,采用超声波探伤原理,能够实现外锁闭装置在线探伤,可智能选择预置探点并判定结果,是电务维护人员对在用外锁闭装置进行在线无损检测的专用工具。     

隧道火灾探测器的应用与测试技术

概述了国内外目前常见的几种隧道火灾探测器的工作原理和应用现状,归纳了他们在实际应用中的普遍优势、常见问题和存在缺陷。在介绍感温火灾探测器产品检测方法的基础上,结合传统工程检测方法和工程现场情况,对高速公路隧道火灾探测器的检验方法和思路进行了一定的创新和开拓,介绍了可应用于隧道火灾探测器工程现场检测的新方法,探讨了简单易行的检测方案,确保检测内容能够真实反映系统运行情况。现场实际应用表明,这些方法具有实用和推广价值,希望能对隧道火灾探测器的初期选型、后期维护以及工程检测过程有所帮助。     

基于CCD的增压锅炉火焰温度及辐射率检测

为实现对炉内火焰温度分布进行实时监测和有效控制以提高锅炉运行的可靠性和经济性,通过接口与密封装置,将3支彩色火焰图像探测器分别布置在增压锅炉前后墙的观火孔内,通过专业采集软件采集炉内火焰图像并保存至计算机中,运用图像处理技术以及基于双色法的火焰温度检测方法得到火焰的辐射温度和辐射率分布图像,实测结果与数值模拟结果吻合较好。不同负荷下试验表明:辐射温度与过热蒸汽温度、烟气压差和燃油压力的变化趋势表现很好的一致性,辐射率的变化趋势则与之相反。