基于HMM-SVR的船舶动力设备故障模式识别与状态预测研究

船舶动力设备因故障监测信号样本少、变化缓慢且数据特征呈非线性,使得设备故障模式的准确识别和状态预测比较难。鉴于此,文章研究了基于隐马尔科夫模型的故障模式识别方法,利用该模型将微弱变化的信号特征转换为变化较大的对数似然概率对故障模式实现有效识别。在此基础上进一步提出基于HMM-SVR的设备状态预测模型,将遗传算法用于支持向量回归模型参数寻优,并结合隐马尔科夫模型,实现对设备状态的预测。对船用柴油机进行仿真,结果表明上述模型具有较高的识别率,能准确预测船舶动力设备的当前状态。     

Soil Body Deformation Caused by Construction of a Double-Line Shield Tunnel with Multiple Factors北大核心CSCD

Considering the influence of many factors (soil loss, frontal additional thrust, the friction force of the shield shell and the additional grouting force), a method for improving the uniform soil body movement model is pro-posed, and a mechanical calculation model is established to study the calculation method for soil body deformation caused by double-line parallel shield driving. Based on the Mindlin solutions of elastic mechanics, the theoretical solutions for soil body deformations caused by the last three factors are calculated; considering the uniform soil body movement model, the theoretical solutions for soil body deformations caused by soil loss are calculated, then the to-tal theoretical solutions for soil body deformations under multiple factors are obtained by means of superposition. The vertical surface settlement, vertical horizontal displacement, and vertical displacements of the soil body at different depths of Hangzhou Metro Line 1 are calculated to analyze the variation laws. Meanwhile the influential factors for horizontal displacement variation are studied. The research shows that with a change of depth, the settlement of the soil body changes within the scope of 10 to 13 m in the horizontal direction near where the maximum settlement occurs;the direction of the horizontal displacement of the soil body changes with a change of the positional relationship be-tween the calculation points and the tunnel; and with an increase of interval J for the two tunnels, the horizontal dis-placement of the soil body of a deep double-line tunnel decreases while the displacement near the surface changes slightly. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Long-term impact of the Shinkansen on rail and air demand: analysis with data from Northeast Japan

This paper analyses how the high-speed rail construction in Northeast Japan (Tohoku) has affected total demand and interregional travel patterns. We use annual interregional passenger data from 1989 to 2012 and apply regression analysis with the demand between Tokyo and the Tohoku prefectures as the dependent variable. We distinguish particularly between the ‘Full-’ and the ‘Mini-’ Shinkansen, where the latter are branch services running with reduced speed. We find that the ‘Full-Shinkansen’ quickly increases rail and total public transport trips and generates additional rail demand year on year. The ‘Mini-Shinkansen’ impacts are less pronounced. Furthermore, our analysis shows that the Shinkansen has shifted some demand from air to rail once it started operation and increased rail share gradually. We therefore suggest that predictions of demand impacts should carefully distinguish immediate from gradual impacts. We also discuss differences in regional demand in that not all prefectures have gained equally from Shinkansen construction.     

复合动力超长续航无人艇系统的设计与实现

为实现无人艇在海上追踪、搜救、巡逻、反潜等任务中的超长续航,避免因油料限制而被迫任务中断,设计了一套以风能、太阳能为动力的无人艇系统,利用风帆为无人艇推进,太阳能为船上电控设备提供电能。该系统由无人艇和岸基监控平台组成,无人艇可通过python开发的数据采集模块和算法模块实时采集环境数据、计算、生成并下达控制指令,在风区内可超长续航自主航行,实现全风向利用;岸基监控平台可实时监控无人艇状态,并进行自主/遥控模式切换。对系统进行了测试,通讯连接试验的可靠性高;无人艇航行试验验证了全风向自主航行的可行性,运行轨迹与仿真结果基本重合;太阳能供电分析理论上验证了风区超长续航的可实现性。     

基于粒子群算法的水下多元线阵阵形有源校正方法

针对存在阵元位置误差的水下多元线阵,提出一种基于粒子群优化算法的远场有源阵形校正方法.该方法选用2个辅助源分时工作方式,利用无条件最大似然方位估计算法构建目标函数,并通过粒子群算法对阵元位置进行寻优.利用该方法对均匀线阵进行性能仿真实验.结果表明:该方法稳健性好、校正精度高,具有一定的应用前景.     

囊式空气弹簧机械阻抗特性研究

根据小幅振动的线性叠加原理将囊式空气弹簧分成几个简单的可解析计算的规则区域,结合线性空气波动理论求解出空气弹簧内部声压场的分布。根据弹性薄壳无矩理论推导出旋转壳体状态向量的一阶常微分矩阵方程,利用齐次扩容精细积分法推导出壳体的传递矩阵,结合动力平衡方程求出空气弹簧在位移谐波激励下所受到的激励力,进而得出其机械阻抗。算例结果表明该方法合理可行,为运用近似解析法分析空气弹簧的阻抗特性提供了一种新的思路。     

基于最优回归理论的舰船辐射噪声指向性统计模型及分析方法研究

文章在已有单航次的舰船噪声空间特性建模分析方法等研究成果的基础上,进一步研究了若干航次条件下的统计建模及分析方法。该研究主要以单一部位垂向剖面的噪声指向性为例,建立了基于最优回归理论的舰船目标辐射噪声特性的统计模型及分析方法,并开展了海上实测研究,验证了该模型及分析方法的正确性和可行性。该项成果为深入分析不同航行工况下各类舰船目标的噪声空间特性及其统计规律等创造了条件。     

一种水下非均质拖曳线列阵动力学仿真方法及试验验证

基于Ablow和Schechter经典差分方法,分析水下非均质拖曳线列阵的受力特性,建立其空间运动控制方程.采用中心差分法和牛顿迭代法对运动控制方程进行离散及时间和空间上的迭代求解,获得水下非均质拖曳线列阵的动力学特性.在此基础上,结合非均质线列阵实尺度模型,设计并开展湖中的实航拖曳试验,分析比较了试验数据与仿真结果.研究表明,本文提出的数学仿真方法有效可靠,可为水下非均质拖曳线列阵动力学特性分析提供一种有效的技术手段.