光纤流量非浸入式测试系统

提出了一种基于湍流振动原理的非浸入式流量测量方法。该方法通过在油管外壁缠绕特定长度的传感光纤,并在传感光纤两端焊接光纤光栅组成光纤流量传感单元。由于流体流过管壁时湍流产生动态压力,动态压力会导致缠绕在管壁上的传感光纤相位发生变化;通过光纤干涉仪技术、时分复用技术及相位载波调制解调技术解调出相位信息,即可实现流量的在线监测。实验数据分析显示,得到的相位变化与流速呈二次曲线关系,设计的实验系统可实现5~50m3/h流量的实时在线测量。由于采用光纤作为传感器感知流量信号,该方法结构简单可靠,灵敏度高,避免了传感光纤流量计需要浸入流场的缺陷,是井下流量测试的理想方法。     

便携式光纤Bragg光栅波长解调仪的研制

近年来光纤光栅在传感领域中的应用研究日益得到关注，其中光纤光栅波长解调是光纤光栅传感器得到应用推广的关键之一。针对大型建筑结构监测应用领域，研制了一种便携式光纤Bragg光栅波长解调仪。解调仪基于无源比例解调原理，以熔融拉锥器件作为线性滤波器，采用锁相放大技术提取微弱信号，并利用单片机控制光纤Bragg光栅波长信息的采集、显示以及存储。解调仪结构简单、成本低，可实现大量程波长测量。实验表明，该光纤光栅解调仪解调范围达15nm，波长测量精度为12．4pm。     

利用光纤偏振分束器和保偏光纤的传感解调系统

提出了一种利用光纤偏振分束器(PBS)和保偏光纤(PMF)中偏振模间干涉原理实现光纤布拉格光栅波长解调的方案,以提高光纤光栅传感解调系统的解调精度和稳定性。运用矩阵光学原理建立了数学分析模型,由此给出了系统输出信号与光纤光栅布拉格波长之间的关系。通过仿真分析,研究了保偏光纤长度、输入光相对于保偏光纤主轴的偏振角度和光纤偏振分束器主轴方位对系统输出信号的影响,明确提出了提高系统灵敏度的方法。根据设计方案搭建了实验系统,并进行了实验验证。结果表明:该设计方案可行,系统的波长分辨率1pm,测量精度1pm,温度可测量范围为90℃。该系统测量精度高,其稳定性优于利用M-Z型干涉仪的解调装置。     

柔性MEMS流速传感器的测控电路设计与实验

针对MEMS流速传感器量程小及无法应用于曲面的不足,设计制造了一种柔性MEMS流速传感器,其结构主要包含加热电阻和3对测温热电阻,同时结合热损失和热温差工作原理来实现宽量程的流速测量。设计了带温度补偿的双惠斯登电桥测控电路,利用STM32微处理器ADC模块对多路流速测量结果进行采样。测试实验实现了0～32 m/s的输入风速测量,其中在1 m/s以下的低风速段内传感器具有100 m V/(m·s~(-1))的较高灵敏度,在风速(1～7 m/s)和(7～32 m/s)下的灵敏度分别为83.1 m V/(m·s~(-1))和28.3 m V/(m·s~(-1))。该柔性MEMS流速传感器可贴于曲面应用,测量范围大、精度高。     

光纤光栅压力传感器中双边缘解调技术的理论与实验研究

以1545/1555 nm的拉曼泵浦合成器（PCOM）为边缘解调器件,对光纤光栅压力传感器中双边缘解调技术的有关内容进行研究,文中对所定义的波长调制函数、波长灵敏度等物理量进行了相应的理论分析和实验测试,给出了单边缘解调与双边缘解调灵敏度曲线,得到当系统的波长解调范围为2 nm左右,压力范围为0-6 MPa时,双边缘解调的波长灵敏度是单边缘解调波长灵敏度的2-3倍的结论。     

低流速热阻式流速仪

介绍了用于低流速测量的热阻式流速仪的硬件和软件的设计.通过实验验证了仪器具有较高灵敏度和精度的特点.当流体流速在15～30 cm/s时,分辨率可达0.1 cm/s.适合于河工模型试验中对流速的测量.     

光纤环镜在光栅传感解调系统中的应用

为实现高稳定性、高精度的波长干涉解调,研究了保偏光纤环镜在波长解调结构中的应用,设计并搭建了一种基于光纤环镜的新型光纤布拉格光栅传感器解调系统.依据传统的矩阵光学原理建立理论模型,分析采用保偏光纤环镜实现干涉解调的基本原理,研究了其结构参数对解调精度的影响并进行数值仿真验证.在理论指导的基础上,搭建光路模块,并基于LabVIEW软件设计了用于消除系统结构参数误差的测定软件与解调系统监控软件,研制电路模块,构成了完整的传感解调系统.经传感检测验证,该系统在20～90 ℃对温度的分辨率为0.03 ℃,准确度可达±0.1 ℃,实验结果与理论分析相吻合,展示了该系统具有良好的稳定性,较高的检测灵敏度和较强的适用性.     

基于布拉格光栅测温解调系统研究

光纤布拉格光栅传感器是利用布拉格光栅波长对温度、应力的敏感特性而制成的一种新型光纤传感器,具有抗电磁干扰、测量范围大、动态范围广、稳定性好等优点。光纤光栅传感器的解调技术是目前光纤光栅传感技术研究领域的重点和难点之一,开发高精度、低价格的解调系统成为光纤光栅传感器大量应用于实际的关键。简要介绍了光纤光栅的发展动态和应用现状;系统地介绍了光纤光栅的解调原理,并给出了采用边缘滤波器法实现光纤布拉格光栅温度解调的模型;利用所设计的光纤布拉格光栅传感解调系统进行了光纤布拉格光栅的温度解调实验,并对实验结果进行了分析和处理,验证了基于光纤布拉格光栅温度解调方案的可行性。     

啁啾效应对Bragg波长匹配解调精度的影响与消除

介绍了光纤光栅Bragg波长的匹配解调原理,分析了传感光纤光栅和匹配光纤光栅的反射谱相关函数, 说明相关函数与光电探测器输出信号具有线性关系。指出基于最大相关原理(光电探测器输出信号极值判断法)的匹配解调只适用于两个光纤光栅具有相同的反射谱型。采用光电探测器输出信号峰值判读时,传感光纤光栅的啁啾效应会引起Bragg波长的解调误差。理论分析和实验研究表明,对光 电探测器输出信号进行去卷积运算处理可以消除传感光纤光栅啁啾效应对Bragg波长解调精度的影响。     

基于氧化石墨修饰长周期光纤光栅的传感特性

提出一种基于氧化石墨烯(GO)修饰的长周期光纤光栅(LPFG)传感器。利用氢氧化钠溶液对LPFG表面进行羟基化处理,采用氢键结合的方式使GO固定在光栅表面,形成基于GO修饰的LPFG传感器。实验研究了GO-LPFG对外部折射率及温度的响应特性,结果表明:该GO-LPFG的平均折射率灵敏度较未涂覆GO的LPFG提高1.09倍,温度灵敏度略有降低。随着光栅直径的减小,GO-LPFG的平均折射率灵敏度进一步提高。当光栅直径为108μm时,在折射率1.333～1.448内的平均波长和耦合强度折射率灵敏度分别约为38.99nm/RIU和57.33dB/RIU,与未采用GO修饰直径为108μm的LPFG及直径为125μm的GO-LPFG相比,其平均波长和耦合强度折射率灵敏度分别提高1.45,2.17,3.80和3.42倍。该GO-LPFG传感器在各种大分子量的病毒抗原蛋白、生物病菌等生物检测领域具有潜在的应用价值。     

Model analysis for differential pressure two-phase flow rate meter in intermittent flow

Multiphase flow rate metering is a challenging problem, specially for flow patterns other than wet-gas. This paper brings forward a new comparative analysis of three differential pressure calibration models suited for liquid dominated two-phase flows, in a total of seven model configurations. First, the models are compared theoretically and classified in terms of the type of input data required. Then, experimental data of over 300 horizontal air–water experiments, for $1$” and $2$” pipe diameters, supports quantitative analyses of the prediction accuracies and sensitivity of the superficial velocities of gas and liquid to measurement errors in the model input variables. Finally, a method for assessing the decoupled measurement errors for the void fraction and gas velocity is shown, as these variables are typically subject to higher uncertainties. It results that, though the void fraction is shown to be systematically under evaluated in more than 10%, the total mass flow rate is estimated through the Paz et al. (2010) model with an overall root mean squared deviation (RMSD) of 5.75% for the $2$” data. Also, the use of gas velocity measurements, even if subject to considerable errors, decreased the RMSD for the gas superficial velocity by more than half for the $1$” data.     

Development of a flow meter for instantaneous flow rate measurements of anaesthetic liquids

An instrument has been developed for instantaneous flow rate measurements of anaesthetic liquids. For periodically time-varying flows, the instantaneous flow rate is reconstructed from the axial velocity time series measured on the centre-line of a pipe. The theoretical background for the method is given and it is demonstrated that fast variations of flow rate can be measured. The instrument is based on a laser Doppler anemometer (LDA) to record the instantaneous velocity on the axis of a capillary; an ultraviolet laser permits velocity measurements with good signal-to-noise ratio from tracer particles in the submicrometer range present in anaesthetic liquids.     

Mass flow rate measurement of gas-liquid two-phase flow using acoustic-optical-Venturi mutisensors

The measurement of multiphase flow parameters is essential for the online monitoring of industrial production and energy metering. In this paper, a multi-sensor experimental measurement device is designed based on NIR, acoustic emission sensors, and throated Venturi. The measurement information is decomposed using modal decomposition, and the characteristic variables of the gas volume fraction are extracted by flow noise decoupling and light attenuation analysis. A new gas volume fraction model is proposed based on Gradient Boosting Decision Tree (GBDT) through feature-level fusion, and the Mean Absolute Percentage Error (MAPE) of the gas volume fraction prediction models is within 4% for the three flow patterns. A new flow rate model is established based on the Homogeneous and Collins models. Laboratory results indicate that the MAPE of the flow rate model is 1.56%, and 98.61% relative deviations are within ±20% error band. The study provides a new method for online measurement of multiphase fluid motion and a theoretical basis for sensing mechanism and measurement of multiphase flow.     

Flow rate measurement by an orifice in a slowly reciprocating gas flow

It is shown that small density changes can give rise to misinterpretation of flow rate signals in unsteady (reciprocating) flows. Basically a flow rate measured at some point A cannot simply be assigned to a remote point B. Depending on the way of plotting a hysteresis appears which, in fact, does not exist. Unsteady conservation of mass is applied to a volume and orifice flow system to obtain an equation which explains and predicts the apparent hysteresis. The equation in dimensionless form contains a key parameter β which holds the flow determining quantities. Experiments are conducted with respect to a wide spread of β. It is shown that the equation predicts reality quite well.     

毛细管基微流体放大系统流体流量分配的研究

微流体在平行通道中的均匀分配是实现微流体控制放量制备粒径单分散性功能微球的重要技术。本研究设计了毛细管基微流体控制放大装置,详细研究了毛细管尺寸、毛细管长度、流体流量以及流体粘度对微流体流量均分的影响。研究结果表明,随着毛细管内径的减小、毛细管长度的增加、流体流量的增大、流体粘度的增加,流体流量分配均匀性更好,即流体流量变异系数(CV)变小。研究获得了描述CV与其影响参数之间关系的经验公式。     

空腔流激振荡在流量测量中的应用探讨

基于空腔流激振荡原理,提出一种结构简单、又无运动部件的流量测量装置。该装置在测量过程中,具有压损小、动态响应快等特点。同时,提出可利用空腔流激振荡进行能量收集,为测量过程中的信号测量、数据处理、数据传输等供电。     

工程实施中的流量补偿计算

根据工程实施经验,介绍了在DCS控制方案设计与组态时的天然气流量补偿计算,饱和蒸汽流量补偿计算和空气流量补偿计算方法和公式,对广大自动化工程师和用户维护人员提供了十分有益的参考和指导作用。     

科里奥利颗粒料质量流量计流量公式理论分析

本文通过对科里奥利固体颗粒料质量流量计的结构分析，认为该流量计无法获取实时的质量流量，并对公开的瞬时流量计算公式进行了理论分析，说明其理论上的缺陷，给出了详细的推证过程和更为精确的理论计算方法和措施。     

Predicting oil flow rate through orifice plate with robust machine learning algorithms

Measuring fluid flow rate passing through pipelines is a basic strategy for developing the infrastructure of fluid-dependent industries. It is a challenging issue for trade, transportation, and reservoir management purposes. Predicting the flow rate of fluid is also regarded as one of the crucial steps for the development of oil fields. In this study, a novel deep machine learning model, convolutional neural network (CNN), was developed to predict oil flow rate through orifice plate (Qo) from seven input variables, including fluid temperature (T_f), upstream pressure (Pu), root differential pressure (√ΔP), percentage of base sediment and water (BS&W%), oil specific gravity (SG), kinematic viscosity (ν), and beta ratio (β, the ratio of pipe diameter to orifice diameter). Due to the absence of accurate and credible methods for determining Qo, deep learning can be a useful alternative to traditional machine learning methods. Justifying the promising performance of the developed CNN model over conventional machine learning models, three different machine learning algorithms, including radial basis function (RBF), least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM), were also developed and their prediction performance was compared with that of the CNN model. A sensitivity analysis was also performed on the influence degree of each input variable on the output variable (Qo). The study outcomes indicate that the CNN model provided the highest Qo prediction accuracy among all the four models developed by presenting a root mean squared error (RMSE) of 0.0341 m3/s and a coefficient of determination (R²) of 0.9999, when applied to the dataset of 3303 data records compiled from oil fields around Iran. The Spearman correlation coefficient analysis results display that √ΔP, Pu, and Tf were the most influential variables on the oil flow rate in respect of the large dataset evaluated.