Self-alignment of full skewed RSINS：observability analysis and full-observable Kalman filter

Traditional orthogonal strapdown inertial navigation sys-tem （SINS） cannot achieve satisfactory self-alignment accuracy in the stationary base： taking more than 5 minutes and al the iner-tial sensors biases cannot get ful observability except the up-axis accelerometer. However, the ful skewed redundant SINS （RSINS） can not only enhance the reliability of the system, but also improve the accuracy of the system, such as the initial alignment. Firstly, the observability of the system state includes attitude errors and al the inertial sensors biases are analyzed with the global perspective method： any three gyroscopes and three accelerometers can be assembled into an independent subordinate SINS （sub-SINS）;the system state can be uniquely confirmed by the coupling connec-tions of al the sub-SINSs;the attitude errors and random constant biases of al the inertial sensors are observable. However, the ran-dom noises of the inertial sensors are not taken into account in the above analyzing process. Secondly, the ful-observable Kalman filter which can be applied to the actual RSINS containing random noises is established; the system state includes the position, ve-locity, attitude errors of al the sub-SINSs and the random constant biases of the redundant inertial sensors. At last, the initial self-alignment process of a typical four-redundancy ful skewed RSINS is simulated： the horizontal attitudes （pitch, rol ） errors and yaw error can be exactly evaluated within 80 s and 100 s respectively, while the random constant biases of gyroscopes and accelero-meters can be precisely evaluated within 120 s. For the ful skewed RSINS, the self-alignment accuracy is greatly improved, mean-while the self-alignment time is widely shortened.     

LEARNING CAUSAL GRAPHS OF NONLINEAR STRUCTURAL VECTOR AUTOREGRESSIVE MODEL USING INFORMATION THEORY CRITERIA

Detection and clarification of cause-effect relationships among variables is an important problem in time series analysis. Traditional causality inference methods have a salient limitation that the model must be linear and with Gaussian noise. Although additive model regression can effectively infer the nonlinear causal relationships of additive nonlinear time series, it suffers from the limitation that contemporaneous causal relationships of variables must be linear and not always valid to test conditional independence relations. This paper provides a nonparametric method that employs both mutual information and conditional mutual information to identify causal structure of a class of nonlinear time series models, which extends the additive nonlinear times series to nonlinear structural vector autoregressive models. An algorithm is developed to learn the contemporaneous and the lagged causal relationships of variables. Simulations demonstrate the effectiveness of the nroosed method.     

Evidence for self-organized criticality in unscheduled downtime data of equipment

How to reduce downtime and improve availability of the complex equipment is very important. Although the unscheduled downtime（USDT） issues of the equipment are very complex, the self-organized criticality（SOC） is the right theory to study complex systems evolution and opens up a new window to the investigation of disasters, such as the sudden failure of the equipment. Firstly,SOC theory and its validation method are introduced. Then an SOC validation method for USDT of the equipment is proposed based on the above theory. Case study is done on bottleneck equipment in a factory and corresponding data pre-process work is done. The rescaled-range（R/S） analysis method is used to calculate the Hurst exponent of USDT time-series data in order to determine the long-range correlation of USDT data on time scale;at the same time the spatial power-law characteristic of USDT time series data is studied. The result shows that the characteristics of SOC are revealed in USDT data of the equipment according to the criterion of SOC. In addition, based on the characteristics of SOC,the overall framework of the prediction method for major sudden failure of the equipment is proposed based on SOC.     

自反应式暖贴持续时间的研究

自反应式暖贴持续时间的长短直接影响着产品质量,铁粉粒度、水、吸水性材料等是影响自反应式暖贴持续时间的关键因素。本文通过改变铁粉的粒度,加入高吸水性材料,控制各种材料配比度来控制自反应式暖贴的持续时间,提高成品机器生产效率等。     

微生物自模板法制备多孔中空微球及应用

微生物作为一种生物质资源不仅具有种类繁多、生物量巨大、易于再生且廉价易得的特点,而且微生物本身就具有高度复杂的微/纳米构造和丰富的功能基团,经过修饰和处理就可以得到结构和功能多样的微/纳米材料.微生物自模板法直接利用微生物天然的球形构造并以其自身物质为主要原料经过一定的处理形成多孔中空微球,具有无需制备模板、反应步骤少和化学试剂消耗量低等优点,与传统的软、硬模板法相比有了较大的进步.本文将利用微生物自模板法制备多孔中空微球的主要合成方法归纳为:溶剂顺序抽提法、高温碳化法和水热碳化法.微生物通过上述3种方法并结合表面修饰可以得到组成丰富、功能多样的多孔中空微球,使其在活性物质封装、控释给药、核磁成像、电极材料、催化及环境等领域有着广泛的应用.在高度重视环境保护和强调可持续发展的当今时代,发展微生物自模板法制备多孔中空微球有着更为深远的现实意义.     

神秘的三角洲特种兵

正在理想世界里,一个三角洲特种部队的指挥官应该像只变色龙,能随时融入人群之中,既不丑得过分,也不美得出挑,而现在已经成为一名作家的戴顿·弗里就是这样一只变色龙。弗里出过一本自传和几本惊险小说。他最著名的作品那本自传《猎杀本·拉登》,讲述了美军策划托拉博拉战役以杀死"基地组织"首脑本·拉登的来龙去脉。弗里作     

老鼠也知道悔过

正在最近的一项研究中,科学家用电极监测老鼠的大脑活动,重点聚焦大脑参与决策的两个重要区域。科学家让老鼠花1小时(设定这个时间限制是为了让老鼠觅食的效率最高)在一个复杂迷宫中玩耍。这个迷宫由1个圆圈及4根辐射自圈上的轮辐组成,其中3根轮辐末端放着香蕉、樱桃或巧克力风味的美食,另1根轮辐末端则放着没有任何风味的食物。当1只老鼠到达1根轮辐后,它在得到食物之前会听到1个音调,音调高低与它在得到食物之前不得不等待的时长(1     

企业集成创新系统自组织演化机理浅析

面对技术与市场均不确定条件下的竞争环境,集成创新模式被提出.企业集成创新已成为企业重要的创新方式,通过运用自组织理论分析了企业集成创新系统的演化动因和过程.     

自平衡深层平板载荷试验在大直径端承桩中的应用

一、概述 随着高层建筑的迅速发展,上部结构对基础的承载力和变形要求越来越高,桩基础应用越来越广泛,由于合肥地区部分地段基岩埋藏较浅,因此许多工程桩都将持力层选在基岩上,这样的基桩单桩承载力高达数千吨,且总阻力的大部分由端阻力提供.在工程实践中,基桩承载力一般通过单桩竖向抗压静荷载试验来确定.这种方法虽然直接可靠,但对于大吨位端承桩由于反力装置、检测周期和检测费用的问题,静载方法往往不是很适用.     

工程水泥基复合材料自愈合过程与产物

借助环境扫描电镜(ESEM)对纤维表面以及15,30,50μm不同宽度裂缝自愈合产物的生长过程进行了连续观察,结合EDS(energy dispersive spectroscopy)、TEM(transmission electron microscopy,透射电镜)、XRD(X-raydiffraction)及FTIR(fourier transform infrared spectroscopy)等先进研究手段,对工程水泥基复合材料(ECC)裂缝自愈合产物的化学特性进行了分析.结果表明,体系中水泥基材料的进一步水化及C-S-H凝胶和CaCO3晶体的生成是裂缝自愈合的主要原因.宽度15μm裂缝的自愈合产物主要为C-S-H凝胶;宽度30μm裂缝的自愈合产物主要为C-S-H凝胶和CaCO3;观察周期内,宽度50μm形成的自愈合产物量无法填满裂缝.从微观层次上看,宽度30μm以下的裂缝几乎都能完全自愈合.同时,ECC材料中的PVA(聚乙烯醇)纤维有亲水特性,为自愈合产物的形成提供了成核点,有助于ECC材料自愈合产物的形成和生长.