含温度补偿的便携式土壤水分测定仪研制

针对现有土壤水分测定仪的不足,研制了一种新型的便携式土壤水分测定仪。传感器快速测量出土壤温、湿度数据,GPS自动获取时间、经纬度信息,数据既可临时保存在仪器的存储芯片中,又可通过GPRS/GSM将数据及时发送到后台数据库和手机用户。通过温度补偿和野外验证实验得出,温度补偿项为Δy=0.0002 t3-0.011 t2+0.444 1 t-6.423 2,仪器所有功能运行正常,测量绝对误差为-3.64%~3.82%,平均绝对误差为2.24%,精度较高,适合在地方农技和水利部门推广应用,有助于农业水利信息化水平的提高。     

Novel one-step formed composite reinforcement of "Spider web like" SiCnw networks and "Z-pins like" SiC rods for ablation resistance improvement of C/C-ZrC-SiC

A novel composite reinforcement with horizontal multilayer "Spider web like" SiC nanowire networks and vertical interconnected "Z-pins like" SiC rods was designed and prepared by facile one-step figuration. The linear ablation rate of "Spider web like" SiC nanowire networks and "Z-pins like" SiC rods collectively reinforced C/C-ZrC-SiC composites at 2610 ± 20 ℃ was 0.4 ± 0.03 μm/s with a 74.19 % reduction. The improved ablation resistance was attributed to a denser gradient oxide layer composed of central ZrO₂ layer, transitional ZrO₂-SiO₂ layer and marginal SiO₂ layer generated under the initial sticky net effect from SiCnw networks and subsequent oxide compensation from "Z-pins like" SiC rods.     

超声波传感器在沙子料位检测中的应用

为提高混凝土的质量,配比很重要,其中沙子精确计量是关键因素之一。提出并设计了超声波系统测量沙子料位;为保证测量精度,采取自动增益控制电路和温度补偿。经实验证明:该方法简单、可行,为沙子质量的检测提供了一种新的参考方法。     

基于集成温度传感器的硅微陀螺仪数字化温度补偿研究

提出了一种基于集成温度传感器的硅微陀螺仪数字化温度补偿方法。首先,介绍了集成温度传感器的硅微陀螺仪基本结构原理,分析了硅微陀螺仪动力学方程以及温度变化对硅微陀螺仪谐振频率、品质因数、标度因数和零偏的影响。然后,设计了基于FPGA的硅微陀螺仪数字化补偿电路。最后,经过温度特性实验得到标度因数和零偏随温度变化曲线,建立了温度补偿模型,提出分段温度补偿方法。经过温度补偿后,标度因数和零偏的温度系数分别由316.66×10-6/℃和366.22°/(h·℃)减小为69.67×10-6/℃和115.25°/(h·℃),证明了补偿方法的正确性和可行性。     

一种基于灰色系统理论的控制系统参数辨识算法的仿真研究

灰色预测补偿是一种对灰色系统进行白化的算法,该算法需要的信息少、计算量小。它可以克服常规PID控制存在超调的缺点。根据灰色PID控制算法,对系统不确定部分建立灰色模型,进行灰色预测补偿。通过仿真研究,该算法具有较强的鲁棒性,可以提高控制质量,减小控制系统的误差。     

有源电力滤波器在工业供电系统中的应用

目前我国工业供电系统中越来越多地使用电力电子设备,这些设备会导致供电系统谐波含量增多,电能质量下降,并对其他用电设备造成不良影响。鉴于此,本文阐述了电网谐波抑制的重要性、紧迫性及谐波抑制方法,分析了有源滤波器的工作原理,并通过具体实例介绍其应用情况。     

在文明寨地区的高精度地震资料处理实践

文明寨地区构造复杂，断块多，岩性变化大，一些地质问题不明，需要高精度三维资料处理来提高资料的纵、横向分辨率^[1][2]及为储层、油藏研究提供精确的依据。针对东濮文明寨地区高精度处理过程中的关键技术进行了大量分析试验，形成了一套适合东濮地区的较为完整的3D高精度地震资料处理流程。实际资料处理表明效果较好。     

Stability analysis and controller synthesis for discrete uncertain singular fuzzy systems with distinct difference matrices in the rules

This paper mainly studies an extended discrete singular fuzzy model incorporating the multiple difference matrices in the rules and discusses its stability and design issues. By embracing additional algebraic constraint, traditional discrete Takagi-Sugeno (T-S) fuzzy model can be extended to a generalised discrete singular Takagi-Sugeno (GDST-S) model with individual difference matrices E_i in the locally singular models, where it can describe a larger class of physical or non-linear systems. Based on the linear matrix inequality (LMI) approach, we focus on deriving some explicit stability and design criteria expressed by the LMIs for the regarded system. Thus, the stability verification and controller synthesis can be performed by the current LMI tools. Finally, some illustrative examples are given to illustrate the effectiveness and validity of the proposed approach.     

3D soft-tissue tracking using spatial-color joint probability distribution and thin-plate spline model

Visual tracking techniques based on stereo endoscope are developed to measure tissue motion in robot-assisted minimally invasive surgery. However, accurate 3D tracking of tissue surfaces remains challenging due to complicated deformation, poor imaging conditions, specular reflections and other dynamic effects during surgery. This study employs a robust and efficient 3D tracking scheme with two independent recursive processes, namely kernel-based inter-frame motion estimation and model-based intra-frame 3D matching. In the first process, target region is represented in joint spatial-color space for robust estimation. By defining a probabilistic similarity measure, a mean-shift-based iterative algorithm is derived for location of the target region in a new image. In the second process, the thin-plate spline model is used to fit the 3D shape of tissue surfaces around the target region. An iterative algorithm based on an efficient second-order minimization technique is derived to compute optimal model parameters. The two processes can be computed in parallel. Their outputs are combined to recover 3D information about the target region. The performance of the proposed method is validated using phantom heart videos and in vivo videos acquired by the daVinci^®${\mathrm{daVinci}}^{\circledR }$ surgical robotic platform and a synthesized data set with known ground truth.     

Discriminative multi-task objects tracking with active feature selection and drift correction

In this paper, we propose a discriminative multi-task objects tracking method with active feature selection and drift correction. The developed method formulates object tracking in a particle filter framework as multi-Task discriminative tracking. As opposed to generative methods that handle particles separately, the proposed method learns the representation of all the particles jointly and the corresponding coefficients are similar. The tracking algorithm starts from the active feature selection scheme, which adaptively chooses suitable number of discriminative features from the tracked target and background in the dynamic environment. Based on the selected feature space, the discriminative dictionary is constructed and updated dynamically. Only a few of them are used to represent all the particles at each frame. In other words, all the particles share the same dictionary templates and their representations are obtained jointly by discriminative multi-task learning. The particle that has the highest similarity with the dictionary templates is selected as the next tracked target state. This jointly sparsity and discriminative learning can exploit the relationship between particles and improve tracking performance. To alleviate the visual drift problem encountered in object tracking, a two-stage particle filtering algorithm is proposed to complete drift correction and exploit both the ground truth information of the first frame and observations obtained online from the current frame. Experimental evaluations on challenging sequences demonstrate the effectiveness, accuracy and robustness of the proposed tracker in comparison with state-of-the-art algorithms.