CMOS图像传感器辐照损伤效应仿真模拟研究进展

CMOS图像传感器(CIS)工作在空间辐射或核辐射环境中遭受的辐照损伤问题备受关注。对CIS辐照损伤效应进行仿真模拟研究有助于深入揭示辐照损伤机理,进而开展抗辐射加固设计,有效提升CIS抗辐照能力。文章通过梳理国内外开展CIS辐照损伤效应仿真模拟研究方面的进展情况,结合课题组已开展的电子元器件辐照效应仿真模拟和实验研究基础,从CIS器件建模、时序驱动电路建模、辐照损伤效应建模、仿真模拟结果校验等方面探讨了CIS辐照损伤效应的仿真模拟方法,分析总结了当前CIS辐照效应仿真模拟研究中亟待解决的关键技术问题。     

Anticipating Cutoff Diameters in Deterministic Lateral Displacement (DLD) Microfluidic Devices for an Optimized Particle Separation

Deterministic lateral displacement (DLD) devices enable to separate nanometer to micrometer‐sized particles around a cutoff diameter, during their transport through a microfluidic channel with slanted rows of pillars. In order to design appropriate DLD geometries for specific separation sizes, robust models are required to anticipate the value of the cutoff diameter. So far, the proposed models result in a single cutoff diameter for a given DLD geometry. This paper shows that the cutoff diameter actually varies along the DLD channel, especially in narrow pillar arrays. Experimental and numerical results reveal that the variation of the cutoff diameter is induced by boundary effects at the channel side walls, called the wall effect. The wall effect generates unexpected particle trajectories that may compromise the separation efficiency. In order to anticipate the wall effect when designing DLD devices, a predictive model is proposed in this work and has been validated experimentally. In addition to the usual geometrical parameters, a new parameter, the number of pillars in the channel cross dimension, is considered in this model to investigate its influence on the particle trajectories.     

The Grid Method for In‐plane Displacement and Strain Measurement: A Review and Analysis

The grid method is a technique suitable for the measurement of in‐plane displacement and strain components on specimens undergoing a small deformation. It relies on a regular marking of the surfaces under investigation. Various techniques are proposed in the literature to retrieve these sought quantities from images of regular markings, but recent advances show that techniques developed initially to process fringe patterns lead to the best results. The grid method features a good compromise between measurement resolution and spatial resolution, thus making it an efficient tool to characterise strain gradients. Another advantage of this technique is the ability to establish closed‐form expressions between its main metrological characteristics, thus enabling to predict them within certain limits. In this context, the objective of this paper is to give the state of the art in the grid method, the information being currently spread out in the literature. We propose first to recall various techniques that were used in the past to process grid images, to focus progressively on the one that is the most used in recent examples: the windowed Fourier transform. From a practical point of view, surfaces under investigation must be marked with grids, so the techniques available to mark specimens with grids are presented. Then we gather the information available in the recent literature to synthesise the connection between three important characteristics of full‐field measurement techniques: the spatial resolution, the measurement resolution and the measurement bias. Some practical information is then offered to help the readers who discover this technique to start using it. In particular, programmes used here to process the grid images are offered to the readers on a dedicated website. We finally present some recent examples available in the literature to highlight the effectiveness of the grid method for in‐plane displacement and strain measurement in real situations.     

基于CCD的垂线坐标仪的设计

针对矿井井壁变形引起的径向位移测量问题,提出了一种基于CCD的垂线坐标仪的设计方案,给出了垂线坐标仪的结构及其在井壁变形监测系统中的布置,详细介绍了垂线坐标仪的软、硬件设计。该垂线坐标仪利用CCD采集光信号并将其转换为视频信号,采用LPC932对采集的视频信号进行二值化处理及计数,并将处理结果发送至地面计算机进行分析,从而得到矿井井壁变形引起的径向位移量。测试结果验证了该垂线坐标仪的稳定性和精确性。     

Prediction of landslide displacement with controlling factors using extreme learning adaptive neuro-fuzzy inference system (ELANFIS)

Landslide is a major geo-environmental hazard which imparts serious threat to lives and properties. The slope failures are due to adverse inherent geological conditions triggered by an external factor. This paper proposes a new method for the prediction of displacement of step-like landslides, by accounting the controlling factors, using recently proposed extreme learning adaptive neuro-fuzzy inference system (ELANFIS) with empirical mode decomposition (EMD) technique. ELANFIS reduces the computational complexity of conventional ANFIS by incorporating the theoretical idea of extreme learning machines (ELM). The rainfall data and reservoir level elevation data are also integrated into the study. The nonlinear original landslide displacement series, rainfall data, and reservoir level elevation data are first converted into a limited number of intrinsic mode functions (IMF) and one residue. Then decomposed displacement data are predicted by using appropriate ELANFIS model. Final prediction is obtained by the summation of outputs of all ELANFIS sub models. The performance of proposed the technique is tested for the prediction Baishuihe and Shiliushubao landslides. The results show that ELANFIS with EMD model outperforms other methods in terms of generalization performance.     

基于无线传感器网络的坡面异常信号检测方法研究

提出了一种适用于硬件资源受限的传感器节点的坡面异常信号检测方法,数据的采集和异常检测在节点前端完成,能提高监测实时性,降低数据传输的通信能耗.传感器节点采集坡面加速度数据,通过对训练数据进行经验模态分解得到本征模函数的上包络,并对该包络数据进行高斯建模自适应学习确定检测阈值.对监测数据经验模态分解得到上包络数据,运用3α原则与检测阈值进行比较实现异常信号判别.通过算法仿真和实际部署测试得到该方法检测精度为98%,具有一定的实用价值.     

平行梁式电容传感器极板耦合角位移计算和分析

为了解决平行梁式电容称重传感器极板耦合角位移带来的输出电容值与输入载荷之间的非线性问题,运用力法对平行梁式弹性体超静定结构进行了计算分析,得出了与上下极板夹角关联的主要结构参数,通过内力对极板角度进行了解析,并在有限元软件中验证了计算的正确性。此结果为平行梁通过结构参数设计优化耦合角位移提供了理论方法,并根据非平行板电容计算公式,构建了更加精确的载荷与电容的数学模型,为传感器输出输入特性曲线的拟合提供了依据。     

滑坡体临滑声发射监测主机的设计

基于滑坡体临滑时因岩石断裂、岩石摩擦而产生声发射的特点,提出一种基于声发射监测的滑坡体临滑监测主机的设计方案。系统能监测的声发射频率范围为1Hz～20kHz,能监测的最小声压为0.002Pa。通过安装在滑坡体附近的声发射传感器,连续监测和记录滑坡体临滑时产生的声发射,可用于分析其变化规律和特征,从而实现对滑坡灾害的预测预报。     

光针式位移传感器聚焦伺服控制系统的设计

通过对光针式位移传感器的执行机构即音圈电机的静动成特怀的分析和测试,在伺服控制系统因路中引入ＰＩＤ校正器,使聚焦伺服系统的稳定性、快速性和准确性等性能都达到良好的应用要求。     

一种智能光纤位移传感器

介绍一种用神经网络实现无级查表功能的光纤位移传感器。其非线性误差小于0．3％FS。具体介绍了硬件原理和使用神经网络的方法。