基于分时方法的高精度反射绝对式纳米时栅位移传感器设计

本文提出了一种反射绝对式纳米时栅位移传感器的传感方法。采用反射单列式传感器作为反射绝对式传感器的精密测量部分,记为传感器A。为了实现绝对位移测量,设计了一个与传感器A相差一个周期的反射单列式传感器,记为传感器B,利用传感器A与传感器B相位作差实现绝对位移测量。采用标准印刷电路板技术制作了传感器样机,搭建了实验平台,进行了实验测试。测试结果表明,激励电极引线方式对接收电极带来干扰,从而造成一次谐波误差。为了抑制误差,提出了交叉反射结构和分时方法,交叉反射结构将感应电极与另一端的反射电极引线相连,增大激励电极和接收电极的距离,分时方法通过不同时间段对传感器A和传感器B施加激励信号,并把不工作的电极接地。实验表明该结构和方法相互配合有效的抑制了干扰,最终在400 mm范围内,补偿后实现了±300 nm的测量精度。

基于区域性气候条件的建筑节能供热分时控制方法

我国区域性气候条件多变,不同地区可以采用不同的方式实现建筑供热,降低建筑能耗,因此,提出基于区域性气候条件的建筑节能供热分时控制方法。根据我国不同区域条件的供热能耗负荷,获取建筑能耗负荷比重;设计模糊自适应的PID控制器,将建筑的供热负荷值输入控制器中计算,依据控制器的输出结果,实现建筑节能供热的分时控制;建立不同的控制方案。实验结果表明,设计方法可将建筑供热能耗节能率提升5%~8.7%,节能效果显著。

一种可操作的需求侧管理峰谷分时电价定价方法

运用经济学原理研究了峰谷分时电价的市场效应,建立了基于电力需求价格弹性矩阵的峰谷分时电价数学模型,提出了电网总售电收入(用户电费支出)对电网负荷变化的反应灵敏度概念。通过对该模型的目标函数进行优化,得到了一种可操作的峰谷分时电价定价方法。算例仿真分析表明所提出的分时电价定价方法是切实可行的,它有利于减小电网的高峰负荷,改善负荷曲线,提高系统运行的可靠性和经济性,实现资源的优化配置和电力工业的可持续发展。

基于FPGA技术的DRAM分时存取方法

介绍了一种基于现场可编程技术对DRAM进行读写和刷新操作的方法,根据现场可编程器件设计的特点,结合DRAM读写和刷新时序的要求,提出了同步化操作DRAM的思想,给出了具体同步化操作DRAM的实现方法,针对现场可编程器件设计中经常有多模块同时存取DRAM芯片的需求,提出了对DRAM芯片进行分时存取的方法,讨论了该方法的实现机制,结合具体的项目设计,给出了分时存取方法的关键时序,避开了复杂的DRAM控制器,节省了设计资源,简单方便地解决了DRAM操作的仲裁问题。

一种分时复用的绝对式纳米时栅位移传感器设计

现代高端装备制造对精密位移检测技术提出了绝对位置测量、高精度和大量程的需求,针对绝对式位移量程与编码的矛盾,提出了一种基于分时复用方法的绝对式纳米时栅位移传感器。采用单列式时栅位移传感器作为绝对式传感器的精测部分,记为传感器A。为了实现绝对位移测量,增加一个周期数比传感器A少且互为质数的对射增量式时栅位移传感器,记为传感器B。利用传感器A与传感器B输出行波的相位值,通过查找表和定位计算实现绝对位移测量。提出了一种分时复用的方法,通过分时间段为传感器A与传感器B提供激励信号,可以有效降低传感器功耗。此外,传感器A与传感器B的感应电极在内部用引线连接,共用1组感应信号处理接口,减少了1组感应信号处理器件,节约了电路空间。采用多层PCB工艺制造了传感样机,搭建了实验平台并对样机性能进行测试。最终实验结果表明:在450 mm范围内,非线性测量误差达到±3μm。

基于LoRa的农田信息无线采集方案设计

针对传统的农业WSN存在距离近、功耗高的问题,提出一种基于LoRa技术的农田信息无线采集系统。通过分析无线网络构成,给出了网络参数的设计原则,优化网络结构、降低组网难度、提高组网效率;选择以STM32L053处理器、SX1276无线芯片和SHT11温湿度传感器组成精简的低功耗节点硬件电路;设计了低功耗、低碰撞的星型无线网络结构,该系统采用分时方法周期性地对传感器数据进行采集和发送;通过实验分析了节点的功耗,时隙长度的选择,对包接收率和接收信号强度指示(RSSI,received signal strength indication)的关系进行研究;结果表明该系统具有通用性强、功耗低、距离远、组网便捷、稳定可靠等特点,能够满足农田信息采集的应用需求。

可搬运锶光晶格钟系统不确定度的评估

可搬运光学原子钟在科学研究和工程应用中具有重要意义.本文测量了可搬运87Sr光晶格钟系统的主要频移,包括黑体辐射频移、碰撞频移、晶格光交流斯塔克频移、二阶塞曼频移等.首先实验上测量了磁光阱腔体表面的温度分布,分析了不同热源对原子团的影响,得到黑体辐射总的相对频移修正量为50.4×10^-16.相对不确定度为5.1×10^-17.然后利用分时自比对方法,评估了碰撞频移、晶格光交流斯塔克频移和二阶塞曼频移.结果表明,由黑体辐射引起的频移量最大,晶格光交流斯塔克频移的不确定度最大,系统总的相对频移修正量为58.8×10^-16,总不确定度为2.3×10^-16.该工作为可搬运87Sr光晶格钟之后的性能提升和应用提供了条件.

Multi-Component Signal Processing for the Short Range Radar

To study the measurement of distance under the condition of the frequency modulation (FM) multi component signal of a short range radar, the multi points scattering model of a target, the TLS ESPRIT (total least square estimation of signal parameters via rotational invariance techniques) and the mathematical statistics methods were used. The method of computing single frequency signal's instantaneous frequency (IF) is unsuitable to the multi component signal. By using the method of the TLS ESPRIT combined with the mathematical statistics, the multi component signal's IF can be obtained. The computer simulation has shown that the method has the high accuracy for measuring the distance.

Effects of Storage Methods and Time on Content of Nutrients in Biogas Slurry of Straw

To study the effects of different storage methods and time on content of nutrients in biogas slurry of straw, two storage methods were carried out on biogas slurry between open storage and airtight storage conditions at normal atmospheric temperature. The contents of N, P, K, and organic matter in biogas slurry of straw were determined in different storage times. The results showed that： during the pro-cess of biogas slurry storage, little change occurred in the content of the organic matter while the total content of N, P, K significantly declined; up to 50 days, the total content of N, P, K reduced to nearly 80%-90%. Because the contents of N, P, K in biogas slurry reduced less in airtight storage conditions so that a better re-sult was found on airtight storage methods than open storage methods in fertilizer field of biogas slurry of straw.

A packet loss avoidance handoff scheme

The basic mobile IP protocol is simple but only suitable for wide area and low speed networks. In this paper, we propose a novel micro-mobile IP handoff scheme, that is the packet loss avoidance handoff scheme. By using an additional cache at the base station and distinguishing packets with packet IDs, the proposed scheme minimizes the number of lost packets during handoff. Network architecture and detailed handoff procedures are given. We also analyze the cache size at the base station, the associated network load with the handoff procedure, and the handoff delay. The scheme is investigated by computer simulations. Simulation results show that the proposed scheme is suitable for environments with fast mobility and frequent handoff.

Multi-scale Chaotic Analysis of the Characteristics of Gas-Liquid Two-phase Flow Patterns

Using the high-speed camera the time sequences of the classical flow patterns of horizontal gas-liquid pipe flow are recorded, from which the average gray-scale values of single-frame images are extracted. Thus obtained gray-scale time series is decomposed by the Empirical Mode Decomposition (EMD) method, the various scales of the signals are processed by Hurst exponent method, and then the dual-fractal characteristics are obtained. The scattered bubble and the bubble cluster theories are applied to the evolution analysis of two-phase flow patterns. At the same time the various signals are checked in the chaotic recursion chart by which the two typical characteristics (diagonal average length and Shannon entropy) are obtained. Resulting term of these properties, the dynamic characteristics of gas-liquid two-phase flow patterns are quantitatively analyzed. The results show that the evolution paths of gas-liquid two-phase flow patterns can be well characterized by the integrated analysis on the basis of the gray-scale time series of flowing images from EMD, Hurst exponents and Recurrence Plot (RP). In the middle frequency section (2nd, 3rd, 4th scales), three flow patterns decomposed by the EMD exhibit dual fractal characteristics which represent the dynamic features of bubble cluster, single bubble, slug bubble and scattered bubble. According to the change of diagonal average lengths and recursive Shannon entropy characteristic value, the structure deterministic of the slug flow is better than the other two patterns. After the decomposition by EMD the slug flow and the mist flow in the high frequency section have obvious peaks. Anyway, it is an effective way to understand and characterize the dynamic characteristics of two-phase flow patterns using the multi-scale non-linear analysis method based on image gray-scale fluctuation signals.

Robust SLAM localization method based on improved variational Bayesian filtering

Aimed at the problem that the state estimation in the measurement update of the simultaneous localization and mapping(SLAM)method is incorrect or even not convergent because of the non-Gaussian measurement noise,outliers,or unknown and time-varying noise statistical characteristics,a robust SLAM method based on the improved variational Bayesian adaptive Kalman filtering(IVBAKF)is proposed.First,the measurement noise covariance is estimated using the variable Bayesian adaptive filtering algorithm.Then,the estimated covariance matrix is robustly processed through the weight function constructed in the form of a reweighted average.Finally,the system updates are iterated multiple times to further gradually correct the state estimation error.Furthermore,to observe features at different depths,a feature measurement model containing depth parameters is constructed.Experimental results show that when the measurement noise does not obey the Gaussian distribution and there are outliers in the measurement information,compared with the variational Bayesian adaptive SLAM method,the positioning accuracy of the proposed method is improved by 17.23%,20.46%,and 17.76%,which has better applicability and robustness to environmental disturbance.

Short-term forecasting optimization algorithms for wind speed along Qinghai-Tibet railway based on different intelligent modeling theories

To protect trains against strong cross-wind along Qinghai-Tibet railway, a strong wind speed monitoring and warning system was developed. And to obtain high-precision wind speed short-term forecasting values for the system to make more accurate scheduling decision, two optimization algorithms were proposed. Using them to make calculative examples for actual wind speed time series from the 18th meteorological station, the results show that: the optimization algorithm based on wavelet analysis method and improved time series analysis method can attain high-precision multi-step forecasting values, the mean relative errors of one-step, three-step, five-step and ten-step forecasting are only 0.30%, 0.75%, 1.15% and 1.65%, respectively. The optimization algorithm based on wavelet analysis method and Kalman time series analysis method can obtain high-precision one-step forecasting values, the mean relative error of one-step forecasting is reduced by 61.67% to 0.115%. The two optimization algorithms both maintain the modeling simple character, and can attain prediction explicit equations after modeling calculation.

如何完善制定峰谷分时电价方法

运用需求弹性理论,通过对边际成本定价法和会计成本定价法的分析,联系内蒙古蒙西电网的实际,对如何完善制定峰谷分时电价的方法问题提出个人见解;

An Improved Water-filled Pulse Tube Method Using Time Domain Pulse Separation Method

Based on existing low-frequency water-filled impedance tube testing facilities, which is a part of the Low Frequency Facility of the Naval Undersea Warfare Center in Beijing, an improved water-filled pulse tube method is presented in this short paper. This proposed study is significantly different from the conventional pulse tube method because of the capability for a single plane damped sine pulse wave to generate in the water-filled pulse tube with a regular waveform and short duration time of about 1ms. During the generation process of the pulse, an inverse filter principle was adopted to compensate the transducer response. The effect of the characteristics of tube termination can be eliminated through the generation process of the pulse. Reflection coefficient from a water/air interface was measured to verify the proposed method. When compared with the expected theoretical values, a relatively good agreement can be obtained in the low frequency range of 500-2 000 Hz.

A new process monitoring method based on noisy time structure independent component analysis

Conventional process monitoring method based on fast independent component analysis(Fast ICA) cannot take the ubiquitous measurement noises into account and may exhibit degraded monitoring performance under the adverse effects of the measurement noises. In this paper, a new process monitoring approach based on noisy time structure ICA(Noisy TSICA) is proposed to solve such problem. A Noisy TSICA algorithm which can consider the measurement noises explicitly is firstly developed to estimate the mixing matrix and extract the independent components(ICs). Subsequently, a monitoring statistic is built to detect process faults on the basis of the recursive kurtosis estimations of the dominant ICs. Lastly, a contribution plot for the monitoring statistic is constructed to identify the fault variables based on the sensitivity analysis. Simulation studies on the continuous stirred tank reactor system demonstrate that the proposed Noisy TSICA-based monitoring method outperforms the conventional Fast ICA-based monitoring method.

A Precision-Positioning Method for a High-Acceleration Low-Load Mechanism Based on Optimal Spatial and Temporal Distribution of Inertial Energy

High-speed and precision positioning are fundamental requirements for high-acceleration low-load mechanisms in integrated circuit （IC） packaging equipment. In this paper, we derive the transient nonlinear dynamicresponse equations of high-acceleration mechanisms, which reveal that stiffness, frequency, damping, and driving frequency are the primary factors. Therefore, we propose a new structural optimization and velocity-planning method for the precision positioning of a high-acceleration mechanism based on optimal spatial and temporal distribution of inertial energy. For structural optimization, we first reviewed the commonly flexible multibody dynamic optimization using equivalent static loads method （ESLM）, and then we selected the modified ESLM for optimal spatial distribution of inertial energy; hence, not only the stiffness but also the inertia and frequency of the real modal shapes are considered. For velocity planning, we developed a new velocity-planning method based on nonlinear dynamic-response optimization with varying motion conditions. Our method was verified on a high-acceleration die bonder. The amplitude of residual vibration could be decreased by more than 20% via structural optimization and the positioning time could be reduced by more than 40% via asymmetric variable velocity planning. This method provides an effective theoretical support for the precision positioning of high-acceleration low-load mechanisms.

Seasonal variation of the Taiwan Warm Current Water and its underlying mechanism

Based on the historical observed data and the modeling results,this paper investigated the seasonal variations in the Taiwan Warm Current Water(TWCW)using a cluster analysis method and examined the contributions of the Kuroshio onshore intrusion and the Taiwan Strait Warm Current(TSWC)to the TWCW on seasonal time scales.The TWCW has obviously seasonal variation in its horizontal distribution,T-S characteristics and volume.The volume of TWCW is maximum(13746 km^3)in winter and minimum(11397 km^3)in autumn.As to the contributions to the TWCW,the TSWC is greatest in summer and smallest in winter,while the Kuroshio onshore intrusion northeast of Taiwan Island is strongest in winter and weakest in summer.By comparison,the Kuroshio onshore intrusion make greater contributions to the Taiwan Warm Current Surface Water(TWCSW)than the TSWC for most of the year,except for in the summertime(from June to August),while the Kuroshio Subsurface Water(KSSW)dominate the Taiwan Warm Current Deep Water(TWCDW).The analysis results demonstrate that the local monsoon winds is the dominant factor controlling the seasonal variation in the TWCW volume via Ekman dynamics,while the surface heat fl ux can play a secondary role via the joint ef fect of baroclinicity and relief.

The modulation recognition based on decision-making mechanism and neural network integrated classifier

A neural network integrated classifier(NNIC) designed with a new modulation recognition algorithm based on the decision-making tree is proposed in this paper.Firstly,instantaneous parameters are extracted in the time domain by the coordinated rotation digital computer(CORDIC) algorithm based on the extended convergence domain and feature parameters of frequency spectrum and power spectrum are extracted by the time-frequency analysis method.All pattern identification parameters are calculated under the I/Q orthogonal two-channel structure,and constructed into the feature vector set.Next,the classifier is designed according to the modulation pattern and recognition performance of the feature parameter set,the optimum threshold is selected for each feature parameter based on the decision-making mechanism in a single classifier,multi-source information fusion and modulation recognition are realized based on feature parameter judge process in the NNIC.Simulation results show NNIC is competent for all modulation recognitions,8 kinds of digital modulated signals are effectively identified,which shows the recognition rate and anti-interference capability at low SNR are improved greatly,the overall recognition rate can reach 100%when SNR is12dB.

Lie Group Classifications and Non-differentiable Solutions for Time-Fractional Burgers Equation

Lie group method provides an efficient tool to solve nonlinear partial differential equations. This paper suggests Lie group method for fractional partial differential equations. A time-fractional Burgers equation is used as an example to illustrate the effectiveness of the Lie group method and some classes of exact solutions are obtained.