Comparative evaluation of five global gravity models over a part of the Bay of Bengal

Several global gravity models (GGMs) are freely available in the public domain, which can be utilised to study the earth's gravity field in almost every part of the globe. The present study compared the free-air gravity anomalies calculated from the five GGMs EGM2008, EIGEN6C4, GECO, XGM2019e_2159, and SGG-UGM-2 archived by the International Centre for Global Earth Models (ICGEM) with respect to shipborne gravity in the Bay of Bengal. The average correlation coefficient and covariance are ～ 96 % and ～ 450mGal². The mean difference between the shipborne and the modelled gravity is ? 5 mGal. Relatively higher amplitude gravity differences observed at the continental-oceanic transition, the 85°E and Ninetyeast ridges, and the western basin are possibly due to high gradient, dominant density contrasts, and rugged topography. The average standard deviation and root-mean-square-error (RMSE) of the differences are ～ 6.5 mGal and ～ 7.5 mGal. A significantly lower standard deviation and RMSE found for the models generated at higher degree/order compared to lower degree/order is due to diminishing omission error of the GGMs with increasing degrees of truncation. The spectral analysis and coherence estimation of the modelled gravity demonstrate excellent correspondence for anomalies wider than ～ 25 km. The agreement between anomaly amplitudes and shapes and calculated statistics indicates that the accuracy and resolution of the modelled gravity data are certainly good enough for regional-scale studies aiming to map Moho topography and mantle structures. However, the delineation of shorter wavelength features originating from the shallow-level basement/sedimentary might be uncertain and requires further validations. The present study confirms that all five models show promising results in terms of their accuracy and resolution. Moreover, the SGG-UGM-2 and XGM2019e_2159 models compare favourably with respect to the GECO, EIGEN6C4 and EGM2008 models in the Bay of Bengal.     

Influence of land surface parameters on the spatio-seasonal land surface temperature regime in rural West Bengal,India

The magnitude and causes of changes in the land surface temperature of rural areas have not been extensively studied. The thermal band of Landsat imagery is taken to extract winter, summer, and monsoon season land surface temperature (LST) and relate it to surface parameters over a 30-year period. From the extracted parameters constructed a prospective surface temperature (PST) model using Multivariate Adaptive Regression Splines. The Chandrabhaga river basin in West Bengal of the lateritic Rarh Tract at the Chota Nagpur Plateau fringe was chosen as the study area because it is far from urban influences, to avoid the well-known heat island effect. Over the study period, summer and winter average LST increased linearly by 0.085?°C/y and 0.016?°C/y respectively. These results were validated with air temperature (RMSE?=?x and y, respectively). Over time more of the area is in the higher temperature zones, e.g., in April 2011, 4% area exceeded >32°, whereas in 2015 this proportion reached 52%. PST models of all the seasons were moderate to highly correlate (0.57–0.87) with actual LST, showing the value of this model. It also revealed the relative importance of the regional factors. Based on this information factor management is a scientific step to restrict or minimize the temperature rise effect.     

Methods to determine stress profile in ALT based on theoretical life models

With the recent products being more reliable,engineers cannot obtain enough failure or degradation information through the design period and even the product lifetime,therefore,accelerated life test(ALT)has become the most popular way to quantify the life characteristics of products.Test design is the most essential topic,such as testing duration,stress profile,data inference,etc.In this paper,a method and procedure based on theoretical life models is proposed to determine the accelerated stress profile.Firstly,the method for theoretical life calculation is put forward based on the main failure mechanism analysis and the theoretical life models.Secondly,the method is provided to determine the accelerated stress profile,including the method to determine the accelerated stress types and the stress range on the basis of the main failure mechanism analysis,the method to determine the acceleration factor and the accelerated stress level based on life quantitative calculation models,and the collaborative analysis method of the accelerated test time while taking the multiple failure mechanisms into consideration.Lastly,the actuator is taken as an example to describe the procedure of the method and the engineering applicability and the validity are verified.     

套索驱动柔性细长机器人视觉运动系统建模与分析

运动和感官进程之间紧密的相互作用,是生物视觉系统进行目标距离估计和观察周围环境的重要特征.为了建立适合套索驱动柔性细长机器人视觉系统模型,分析了通过生物眼球运动策略,以获得准确距离估计和环境信息的机理.此外,探讨了在摄像机系统中通过模拟生物眼球运动策略进行距离估计和周围环境观察的可能性,以及通过纯机械方式,模拟基于Listing法则眼球扫视运动的可能性.最后,提出Listing平面应是套索驱动机器人视觉测量和空间姿态控制结合点的观点.     

双马来酰亚胺树脂化学流变特性研究

在粘度实验的基础上 ,根据双阿累尼乌斯方程对用于 RTM工艺的双马来酰亚胺树脂体系的化学流变特性进行了研究 ,建立了树脂体系的流变模型。通过 DSC热分析实验研究树脂体系的固化反应规律 ,验证了双阿累尼乌斯模型。研究表明 ,模型与实验结果具有良好的一致性。模型可揭示树脂体系在不同工艺条件下的粘度变化规律 ,定量预报 RTM工艺树脂的低粘度平台工艺窗口 ,为合理制定 RTM工艺参数、保证产品质量和实现工艺参数的全局优化提供必要的科学依据     

一种基于滑动库的多模自适应控制方法

针对系统参数跳变时常规自适应控制闭环系统暂态响应差的问题,论文提出了一种基于滑动库的多模自适应控制方法。该控制器由多个参数已知的固定模型,一个自适应模型和一个滑动模型库构成。固定模型由被控对象在特定环境下的特征模型直接映射获得,其参数和其邻域一起覆盖被控对象的参数集;自适应模型对被控对象进行在线参数辨识,其参数被用来动态更新固定模型库;滑动模型库根据当前的工作点从固定模型库中选择离工作点较近的部分模型参与控制,优化控制模型集,减少计算量。仿真实验的结果表明了该方法的有效性。     

(鱼参)科类鱼尾模型的巡游推进特性实验研究

通过对不同形状运动尾鳍模型的测力实验,研究了鱼 参科鱼类巡游时尾鳍的推进特性.结果表明:模型转动与平动间的相位差对模型受到推力的大小及方向有显著影响,在转动滞后平动90°附近模型受到较大推力.对于五种不同的尾鳍模型,虽然形状各异,但它们受到的平均推力正比于无量纲二阶矩与模型面积的乘积.     

Quick identification of guidance law for an incoming missile using multiple-model mechanism

A guidance law parameter identification model based on Gated Recurrent Unit (GRU) neural network is established. The scenario of the model is that an incoming missile (called missile) attacks a target aircraft (called aircraft) using Proportional Navigation (PN) guidance law. The parameter identification is viewed as a regression problem in this paper rather than a classification problem, which means the assumption that the parameter is in a finite set of possible results is discarded. To increase the training speed of the neural network and obtain the nonlinear mapping relationship between kinematic information and the guidance law parameter of the incoming missile, an output processing method called Multiple-Model Mechanism (MMM) is proposed. Compared with a conventional GRU neural network, the model established in this paper can deal with data of any length through an encoding layer in front of the input layer. The effectiveness of the proposed Multiple-Model Mechanism and the performance of the guidance law parameter identification model are demonstrated using numerical simulation.     

Distributed UAV swarm based on spatial grid model

Unmanned Aerial Vehicle(UAV) swarm has become the inevitable trend of development, which will enjoy broad prospects to be applied in the future. However, the change of UAV application mode will certainly bring new technical challenges in the flight management, environmental perception, collaborative control as well as other fields. This paper considers that it can be an effective solution to realize the unified management of spatial information on the UAV platform by adopting the spatial grid mo...     

集模式分散滤波及其应用

把集模式的思想用到了分散滤波中，并针对有关文献中加权因子的选取存在的必须凭经验进行的问题、对集模式分散滤波的加权因子的确定提供了一种方法，即利用状态量的误差协方差的特征值平方来确定加权因子。利用本文介绍的集模式分散滤波方法对INS/GPS/TAN组合导航系统进行了仿真。仿真结果表明，本文介绍的滤波方法具有较高的精度，因而不失为一种可行的滤波方法。