压力传感器实时校准技术探讨

介绍压力（压差）传感器静态特性的校准，各项误差指标规定和数据处理原理，翼型，叶栅国防科技重点实验内，近期已经建成并日趋完善的压力传感器实时校准系统，风洞实验中多只压力传感器和动态压力传感器的静态实时准提供了一条简单实用的校准途径。     

改善传感器特性的软件处理方法

讨论了改善传感器特性的一般方法，针对传感器的静态特性和动态特性提出了用软件处理方法改善特性的设计方法，并以灰法传感器的非线性和动态特性补偿为例进行了验证。理论和实验研究表明方法具有一定的实用价值，特别适用于利用单片机进行开发的智能传感器。     

信息系统动态过程建模的研究

本文提出了概念建模中的面向行动的层次网络模型（ＡＯＨＮＭ）．该模型不但描述了应用环境的静态特性，而且描述了应用环境的动态特性。静态特性是指现实世界的对象及其结构，动态特性是指动态的过程，两者的结合充分表述了系统的动态行为。ＡＯＨＮＭ提供了信息系统分析和设计的方法并便利了原型系统的建立。     

基于带电直导线周围磁场的磁传感器动静态特性标定方法

目前磁传感器多用于对静态或准静态磁场环境的测试,当被测磁场矢量快速变化时,磁传感器的动态特性成为影响其测量精度的关键因素。针对测试现场环境中难于产生标准的高频交变激励磁场源致使磁传感器动态特性无法准确快速标定的难题,提出一种基于带电直导线周围磁场的磁传感器动静态特性现场快速标定方法。首先提出并构建了一种基于带电直导线的标准宽频带磁场发生器,采用毕奥-萨伐尔定律分析了带电直导线周围磁场分布规律;其次通过在长直导线中加载典型交变激励电流,产生典型交变磁场,采用系统辨识方法实现对磁传感器动态特性标定;最后对某矢量磁传感器测量系统进行了时域、频域动态模型标定。实验表明所提出的磁传感器动态模型标定方法具有简便、快速、高效、准确的优点,便于工业现场对各类磁传感器进行动静态特性标定。     

倾角传感器稳定性测试与分析

为了进一步加强产品质量监管,更加全面地了解倾角传感器的稳定性,随机抽取了两款倾角传感器,针对倾角传感器的启动特性、动态特性和稳态特性进行测试与分析.为了更全面地展示出倾角传感器稳定性,结合倾角传感器在设备上面从启动到稳定工作的整个过程,文章给出较为合理的测试方法和步骤,重点分析了倾角传感器启动时的快速稳定性、动作时的动态跟随性和静态时的稳态特性.测试结果表明,动态特性好的倾角传感器启动时会更快地稳定,而稳态特性相对降低.     

MEMS微电容式传感器的传感特性研究

针对传统的传感器无法进行长期健康监测的不足,研发出一套新型的基于MEMS的硅微电容式传感器.对所研制的MEMS传感器的静态传感特性和动态特性进行了理论分析和对比实验研究.结果表明:MEMS硅微电容式传感器在反复加卸载实验中,线性拟和度均在0.999%F.S以上,灵敏度系数为6.9840με/kN,其重复性误差为1.43%F.S;其动态传感特性与传统的加速度计吻合的很好.     

改善传感器特性的软件处理方法

本文研究了改善传感器特性的一般方法,并针对传感器的静态特性和动态特性,提出了用软件处理方法来改善其特性的设计方法,理论和实验研究表明该方法具有一定的实用价值,特别适用于利用单片机进行开发的智能传感器。     

基于块联模型的动态非线性校正方法比较

针对以块联模型表示,且静态特性位于第一象限的饱和型非线性传感器,进行基于块联模型的动态非线性校正方法研究.块联模型包括Hammerstein和Wiener模型,虽然它们都是由静态非线性校正环节和动态线性补偿环节组成,但是由于位置不同,即对传感器输出信号进行处理的顺序不同,校正效果也就有所不同.根据传感器不同的阻尼比,分别研究Hammerstein和Wiener模型的动态非线性校正方法的实现,并比较它们的校正效果.结果表明,传感器模型或阻尼比不同时,动态非线性校正方法的选择也应有所不同.研究成果为以后设计同类型传感器的动态非线性校正系统提供了先验知识.     

一种十字梁结构多维力传感器结构优化

多维力传感器可以检测空间三个维度的力信息,要求传感器各方向的灵敏度高、维间耦合小、具有良好的静态和动态特性等。本文分析研究了一种自带过载保护的多维力传感器,采用面向任务法对弹性体关键结构参数优化。采用有限元软件（ANSYS）对多维力传感器的弹性体进行了静态、动态分析,获取弹性体在各方向受力时应力、应变的变化情况,结果表明传感器具备灵敏度高,线性度好的特点。     

银行账户交易复杂网络特性分析

首先基于银行账户交易的特点，建立了一个有向加权的银行账户交易网络通用模型。进而，根据复杂网络的定义，从网络结构和节点2个层面，验证了交易网络的复杂网络特性。其中，网络结构特性包括静态特性（即无标度特性和小世界特性）和动态演化特性（即自组织特性）。此外，使用吸引子特性验证了复杂网络节点的动力学特征。分析包含非法传销交易的真实银行交易数据，得出如下结论：该网络具有无标度特性、小世界特性、部分自组织特性和奇异吸引子。     

氧化锌基乙醇气体传感器研制及特性研究

利用水热法合成了不同形貌的ZnO基纳米结构气敏材料,利用X射线衍射仪(XRD)和扫描电子显微镜 (SEM)对其进行了结构表征和分析。制备成旁热式气体传感器,测试了其对乙醇(C2H5OH)的气敏特性。实验结果表明：基于ZnO纳米花制作出的传感器比纳米球状传感器对C2H5OH具有更高的灵敏度,在200oC下对50ppm的C2H5OH灵敏度为34.7,是球状ZnO基传感器的1.7倍;两种ZnO基传感器对C2H5OH均表现出较好的重复性,在最佳工作温度下对C2H5OH的响应恢复时间均在15秒以内;最后对ZnO基C2H5OH气体传感器的气敏机理进行了讨论。     

NiO电极中YSZ添加量对NOx传感器气敏性能的影响

以钇稳氧化锆(简称YSZ,Yttria-Stabilized Zirco nia)为固体电解质,添加不同摩尔比例YSZ的NiO+YSZ混合体为敏感电极材料,通过丝网印刷技术制备了相应的混合电势型NOx传感器.采用XRD和SEM手段对NiO混合物进行了物理性能分析,利用电势和阻抗测量设备对传感器样品的输出电势(EMF)和交流阻抗等电学参数随NO浓度的变化进行了研究.结果显示:NiO+YSZ的混合体中,物相独立,没有新相产生;在相同NO检测环境下,敏感电极中YSZ所占摩尔比例为20mol%时传感器的响应电势最大且在0.O1 Hz～100 kHz范围内的阻抗谱最小,SEM也显示此时具有很好的TPB.     

On-line estimation of product properties for crude distillation units

The stringent quality requirement of petroleum products in a highly competitive market makes on-line monitoring and control of product properties essential. But unfortunately few on-line hardware sensors are available and these are also difficult to maintain. It is, therefore, necessary to develop ‘software sensors’ to predict the quality using other easily measurable secondary variables. This study presents an algorithm that uses the crude true boiling point (TBP) curve and other routinely measured flow rates, temperatures and pressures in the crude distillation unit (CDU) to predict the product properties. The measured top plate, side-stripper draw plates and flash zone temperatures are corrected for hydrocarbon partial pressures to obtain equilibrium flash vaporization (EFV) temperatures. These product EFVs are converted to product TBPs and are superimposed on the crude TBP curve. An assumption, that the initial boiling point (IBP) of the next heavier product lies vertically below the final boiling point (FBP) of the product under consideration and the two points are equidistant from the crude TBP curve, allows estimation of the IBP and FBP temperatures of all the distillate products. A straight line approximation of the product TBP curve is used to obtain intermediate temperatures. These TBP temperatures are converted to product ASTM (American Society for Testing Materials) temperatures which are correlated with the desired product properties. Several properties have been predicted using the above procedure. These include densities of all the CDU products, Flash Points for all the side-stream products, Reid Vapor Pressure (RVP) for the distillate, Freeze Point for kerosene, Pour Point and the recovery for the gas oils etc. It is possible to predict these properties repeatedly every minute as long as steady state conditions prevail in the CDU. The algorithm has been applied off-line with the available on-line data from two different operating refineries. A satisfactory match between the predicted and the measured properties validated the developed soft sensors. However, extensive testing is recommended before the implementation of these soft sensors on the actual process.     

Sensor location and classification for disturbance rejection by measurement feedback

In this paper a new necessary and sufficient condition is proposed for the solvability of the Disturbance Rejection by Measurement Feedback (DRMF) problem involving linear structured systems. The associated system graph can be used to easily check whether or not the condition holds. In relation to the DRMF problem, two issues related to the available sensor set have been investigated:

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  Sensor number and location: when the DRMF problem is not solvable with the given sensor set, how many sensors are needed and where should they be located to make the DRMF problem solvable?

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  Sensor classification: when the DRMF problem is solvable with the given sensor set, what is the impact of the failure of a sensor on the solvability?

Based on the new condition, a lower bound can be determined for the number of sensors required. Moreover, measuring state variables outside a given subset is found to be of no use. To solve the DRMF problem, it is sufficient to measure state variables sufficiently close to the disturbances in the associated system graph. Sensor classification is used to distinguish between essential sensors, i.e. sensors for which failure leads to unsolvability, and useless sensors that have no impact on solvability. Partial classification results are provided for the general case and a complete characterization of essential and useless sensors is provided for the single disturbance case.     

苯乙烯-马来酸酐交替共聚物钠盐/聚苯乙烯磺酸钠复合物的湿敏特性

以苯乙烯-马来酸酐交替共聚物钠盐(NaSMA)与聚苯乙烯磺酸钠(NaPSS)复合物为湿敏材料,在叉指金电极上浸涂成膜制备了电阻型湿度传感器,考察了NaSMA和NaPSS浓度对复合湿度传感器响应特性的影响.研究表明,加入NaPSS可降低传感器在低湿下电阻,同时提高传感器的高湿灵敏度.在最佳条件下,当环境湿度从33%RH增...     

TiO_2/V_2O_5双层薄膜的TMA气敏特性研究

报道了以TiCl4 和V2 O5为源 ,采用等离子增强化学气相沉积 (PECVD)和溶胶 -凝胶 (sol-gel)技术制备了TiO2 /V2 O5双层薄膜 ,将该薄膜沉积在带有金梳状电极的陶瓷管和硅片上 ,进行了X射线衍射(XRD)分析 ,并且测量其对三甲基胺 (TMA)的气敏特性。结果发现该双层薄膜对TMA具有高灵敏度、良好的选择特性和快速的响应恢复特性。     

栅格划分下的传感器部署

提出一种在不精确探测和地形属性限制下的传感器部署方法,对给定的划分为栅格点的传感器区域,该方法不仅能求出所需的最小的传感器数目,还能给出这些传感器的位置。用一些典型情景下的仿真证明:提出的这种方法比随机部署有效地减少了使用传感器的数量,并给出了这些传感器的位置。     

Modeling and experimental studies on retro-reflective fiber optic micro-displacement sensor with variable geometrical properties

Fiber optic displacement sensors (FODS) are studied and analyzed by using different configurations (Atsushi and Kohichi, 1996; Faria, 1998; Buchade and Shaligram, 2006) [1], [2] and [6]. Mathematical models developed for these configurations use analytical methods and techniques. It is observed that these models are useful for a specific geometrical arrangement of fibers and reflector and are not useful for any variation in configuration. Hence it is necessary to develop a mathematical model which is independent of configuration of the fiber optic sensors. This paper discusses development of such generalized model which is useful for studying and analyzing any configuration and scenario of fiber optic sensor. The model is expected to be useful in analyzing manufacturing tolerances as well as effects of the geometrical parameters on performance of the sensor.     

Effect of soft-hard segment structure on vapor responsiveness of polyurethane conducting composite thin films loaded with multi-walled carbon nanotubes

A series of multi-walled carbon nanotubes/polyurethane (MWNTs/PU) composite conducting dispersoids were prepared via an in situ coupling reaction among linear hydroxyl-terminated polymer diols, 1,6-hexamethylene diisocyanate (HDI) and various chain extenders. The composite conducting thin films were formed by spin-coating and depositing the dispersoids onto comb-like electrode substrates. The resulting structure and the dispersion quality of MWNTs in the dispersoids were examined by means of FTIR, XRD, TEM, SEM and UV-vis analyses. The response of the as-prepared films toward some volatile organic solvent vapors such as benzene, anhydrous ether, acetone and chloroform was evaluated. The experimental results indicated that the composite conducting films constructed by hydroxyl-terminated poly(butadiene-co-acrylonitrile), trimethylolpropane, and MWNTs-OH bear better vapor responsiveness. The dispersion behavior of MWNTs in the dispersoids, types of MWNTs and soft-hard segmental compositions are believed to be closely related with the sensing properties of the films. In particular, the chemical linkage of MWNT-OH with HDI in the PU matrix is expected to improve the dispersivity and further to enhance the sensing properties of the composite sensors. The vapor sensing properties well reveal that these materials have a possibility as a candidate of volatile organic solvent vapor sensors.     

接触式传感器测量软体驱动器角度的数据融合

现有用于软体驱动器角度测量的接触式传感器主要包括惯性传感器与曲率传感器,但惯性传感器的测量精度易受软体驱动器内嵌气道膨胀的影响,曲率传感器测量则存在迟滞和漂移等问题。为进一步提高接触式传感器测量软体驱动器角度的准确性,结合模糊推理与卡尔曼滤波结合的算法实现惯性传感器和曲率传感器数据融合。基于BP神经网络和长短时记忆网络分别融合曲率传感器和惯性传感器,减少接触式传感器测量软体驱动器角度时迟滞和气道膨胀的影响。实验结果显示,采用长短时记忆网络、BP神经网络和模糊推理与卡尔曼滤波相结合的数据融合结果均方根误差精度分别为0.51°、0.63°和1.59°,表明长短时记忆网络能够更好地提高接触式传感器对软体驱动器角度的测量精度。