Measuring local and global vibration modes in model plants

Model plants are extensively used in biological studies, and their mechanical behaviour needs to be better understood, in relation to studies in mechanoperception for instance. We present here the first approach to derive experimentally the modal parameters of two of these plants, Arabidopsis thaliana and Populus tremula × alba. A classical sinusoidal sweep excitation is used, with a measurement of displacements based on LKT optical flow tracking, followed by a bi-orthogonal decomposition (BOD). This allows us to estimate several modal frequencies for each plant, as well as the corresponding spatial localizations of deformation. Analyzing the modal frequencies, we show that global and local modes correspond to distinct ranges of frequencies and depend differently on plant size. Possible phenotyping applications are then discussed.     

使用离轴光学系统的气体切伦科夫探测器

基于探测器的测量原理,并针对卡塞格林光学系统的不足,分析了一种新型气体切伦科夫探测器的光学结构。该探测器采用3片90°离轴抛物镜和1片平面反射镜组成的离轴光学系统以减少对光线的阻挡,并将探测窗口置于光学系统的出瞳以提高光收集效率。分析了光学系统的光束限制和光线追迹结果。设计了探测器的集成结构,从提高探测器效率和减少信号干扰等角度分析了探测器的关键设计和制造要求。     

Measurement of edge residual stresses in glass by the phase-shifting method

Control and measurement of residual stress in glass is of great importance in the industrial field. Since glass is a birefringent material, the residual stress analysis is based mainly on the photoelastic method. This paper considers two methods of automated analysis of membrane residual stress in glass sheets, based on the phase-shifting concept in monochromatic light. In particular these methods are the automated versions of goniometric compensation methods of Tardy and Sénarmont. The proposed methods can effectively replace manual methods of compensation (goniometric compensation of Tardy and Sénarmont, Babinet and Babinet-Soleil compensators) provided by current standards on the analysis of residual stresses in glasses.     

Study of improved Otsu algorithm and its ration evaluation analysis for PCB photoelectric image segmentation

The algorithm of maximum variance between clusters (traditional Otsu algorithm) is discussed, and its advantage is given also. In order to segment the PCB photoelectric image better, on the basis of the traditional Otsu algorithm, considering the different influence of image segmentation about the factors of the distance between target and background as well as each kind of cohesion, an improved Otsu algorithm is proposed, and its basic principle and segmentation advantages are analyzed in detail. In order to evaluate these segmentation results impersonally by using different algorithms, the quantitative criteria of gray-level contrast and district interior uniformity are adopted to evaluate these segmentation results impersonally. Finally, the different segmentation experiment contrasts of PCB photoelectric image between our algorithm and other algorithms is executed, the results of experiment indicate that our algorithm has relatively better segmentation quality.     

Adaptive neuro-fuzzy fusion of sensor data

A framework is proposed, which consolidates the benefits of a fuzzy rationale and a neural system. The framework joins together Kalman separating and delicate processing guideline i.e. ANFIS to structure an effective information combination strategy for the target following framework. A novel versatile calculation focused around ANFIS is proposed to adjust logical progressions and to weaken the questionable aggravation of estimation information from multisensory. Fuzzy versatile combination calculation is a compelling device to make the genuine quality of the leftover covariance steady with its hypothetical worth. ANFIS indicates great taking in and forecast proficiencies, which makes it a productive device to manage experienced vulnerabilities in any framework. A neural system is presented, which can concentrate the measurable properties of the samples throughout the preparation sessions. Reproduction results demonstrate that the calculation can successfully alter the framework to adjust context oriented progressions and has solid combination capacity in opposing questionable data. This sagacious estimator is actualized utilizing Matlab/Simulink and the exhibitions are explored.     

Interest point detection in images using complex network analysis

This paper presents a new application of complex network theory and tools to digital image analysis and computer vision problems in order to detect interest points in digital images. We associate a weighted geometrical and fast computable complex network to each image and then we propose two different methods to locate these feature points based on both local and global (spectral) centrality measures of the corresponding network.     

MIMU/GPS组合导航系统数据同步与融合方法研究

给出了以DSP为核心的MIMU/GPS组合导航系统中数据同步与融合的方法,简要介绍了仿真、调试过程中DSP程序的实现方法。采用GPS接收机输出的1PPS脉冲,结合CPLD产生的时序,实现MIMU和GPS数据的同步采集。由于系统噪声难于准确统计,因此采用模糊自适应卡尔曼滤波组合算法进行数据融合。     

惯性/重力匹配组合导航系统与可视化仿真

根据惯性/重力匹配组合导航系统的工作原理和特点,提出了基于 RANSA 思想的重力图匹配方法,采用此方法实现了重力图的鲁棒匹配。通过建立组合导航系统的数学模型,采用最优滤波技术实现了组合导航系统的信息融合。在此基础上,采用多种高级语言混合编程,设计实现了一套可视化的仿真软件,对该系统进行了可视化仿真研究。仿真实验结果表明,惯性/重力匹配组合系统相对于无辅助的惯性导航系统,其定位精度、速度精度均有较大的提高,也就是说采用重力匹配方法达到了校正惯导系统,实现高精度导航的目的。     

基于不同局部模型的联合滤波算法研究

从组合导航系统研究的角度出发，提出了一种基于不同局部模型的联合滤波算法，并对INS/GPS/Doppler组合导航系统进行了仿真。结果表明：该算法不要求局部模型一致，增强了系统的通用性，提高了运算速度。