多孔硅气体传感器

介绍了多孔硅气体传感器的原理和优点,综述了多孔硅气体传感器测量氮氧化物和几种有机气体的机理、方法及最新的研究进展,并分析了传感器的选择性和稳定性,展望了多孔硅气体传感器应用前景。     

MEMS结构氧传感器的研究

采用微加工技术研制了一种以硅为基底材料,具有MEMS结构的氧传感器.阐述了该传感器的工作原理、结构设计、工艺流程以及特性分析.给出了溅射制备TiO2薄膜的方法及锐钛矿型晶体结构能谱,讨论了二氧化钛的氧敏机理.研究表明与传统的气体传感器相比,此种传感器具有体积小、低功耗、可集成的特点.     

基于动态注意力深度迁移网络的高炉铁水硅含量在线预测方法

铁水硅含量是反映高炉冶炼过程中热状态变化的灵敏指示剂, 但无法实时在线检测, 造成铁水质量调控盲目. 为此, 提出一种基于动态注意力深度迁移网络(Attention deep transfer network, ADTNet)的高炉铁水硅含量在线预测方法. 首先, 针对传统深度网络静态建模思路无法准确描述过程变量与铁水硅含量之间的关系, 提出一种基于注意力机制模块的输入过程变量与输出硅含量之间的动态关系描述方法; 其次, 为降低硅含量预测模型训练时对标签数据的依赖, 考虑到铁水温度与硅含量数据之间的正相关性, 利用小时级硅含量标签数据微调基于分钟级铁水温度数据预训练好的深度模型的结构, 进而提高基于动态注意力深度迁移网络的硅含量预测精度; 同时, 为增强预测网络的可解释性, 实时给出了基于动态注意力机制模块计算的每个样本各过程变量对铁水硅含量的贡献度; 最后, 基于某钢铁厂2号高炉的工业实验, 验证了该方法的准确性、有效性和先进性.     

复杂高炉炼铁过程的数据驱动建模及预测算法

高炉炼铁过程的控制意味着控制高炉铁水温度及成份在指定的范围. 本文以高炉炉内热状态的重要指示剂---高炉铁水硅含量为研究对象, 针对机理建模难以准确预测、控制高炉铁水硅含量的发展变化, 利用数据驱动建模的思想, 建立了基于多元时间序列的高炉铁水硅含量数据驱动预测模型. 实例分析表明, 建立的数据驱动预测模型能够很好地预测高炉铁水硅含量, 连续预测167炉高炉铁水硅含量, 命中率高达83.23%, 预测均方根误差为0.07260. 这些指标均优于基于单一硅时间序列所建立的数据驱动模型, 对实际生产具有很好的指导作用.     

氧传感器的研究与应用

氧传感器具有低成本、结构简单、高灵敏度等优点,在工业、农业、医学和环境等领域具有广泛的应用.用于测量气体中氧分压和水中溶解氧浓度的氧传感器的基本原理相同,只是结构和所用材料有所区别.电化学氧传感器在其实际应用中存在着气候影响、残余电流以及寿命与可靠性等问题,针对这些具体问题,人们也在实际运用中采取了不同的方法加以解决.     

辅助电极型硅传感器的热力学分析与实验

首次用热力学分析了硅传感器的辅助电极与熔液中硅、氧和碳的反应方向与限度。讨论了局域)与熔液中硅活度(a[Si])的相关性;揭示了前人用辅助电极型硅传感器对高碳熔液测量平衡氧逸度(fO2时可能发生附反应,指出了有效测量范围;发现了Mg2SiO4(s)+MgO(s.s.)硅传感器存在测量盲区。研制了一种新Mg2SiO4(s)+MgO(s)硅传感器,用Mg2SiO4(s)+MgO(s)硅传感器测得了盲区内高碳低硅熔液中硅的活度,实验表明该测量无附反应发生,证明了热力学分析是可信的。     

新型硅基气体传感器

一种基于多孔硅和独特金属化工艺的新型传感器问世,与现有技术相比,可提高敏感性,降低电力需求和成本,还可用于环境探测、食品和生物医学应用中的重要气体化合物.     

微结构气体传感器的加热器设计与模拟

利用有限元分析工具ANSYS,对所设计的硅基微结构气体传感器的温度场进行了模拟.运用实体建模的方法建立了传感器衬底的多层结构模型,采用8节点等参数热单元solid70进行了分析.根据器件工作时需要的加热功率,设计了这种硅基气体传感器衬底微加热器的尺寸,确立了对流和环境温度等边界条件,从而达到气体传感器衬底的温度场分布均匀的要求.     

基于多参数灵敏度分析与遗传优化的铁水质量无模型自适应控制

铁水硅含量(化学热)和铁水温度(物理热)是高炉炼铁过程最重要的铁水质量指标, 其建模与控制对于整个高炉炼铁过程的运行优化意义重大. 针对高炉炼铁过程极复杂动态特性以及铁水质量难以进行常规机理建模与控制的难题, 基于直接数据驱动控制思想, 提出一种基于多参数灵敏度分析与大规模变异遗传参数优化的高炉铁水质量无模型自适应控制方法. 首先, 基于紧格式动态线性化(Compact form dynamic linearization, CFDL)无模型自适应控制(Model free adaptive control, MFAC)技术确定铁水质量的多变量数据驱动控制器结构; 然后, 针对CFDL-MFAC众多可调参数对控制器性能影响大, 同时对众多参数整体优化非常耗时且效果不理想的问题, 基于多参数灵敏度分析(Multi-parameter sensitivity analysis, MPSA)技术, 提出基于大规模变异与精英局部搜索遗传优化的CFDL-MFAC控制器参数整定方法; 最后, 将参数整定后的CFDL-MFAC控制器应用到高炉炼铁过程多元铁水质量控制, 并与基于递推子空间辨识的数据驱动预测控制进行比较研究, 验证所提控制方法的有效性和先进性.     

汽车用氧传感器的工作原理及其应用

主要介绍了浓盖型ZrO2氧传感器、极限型ZrO2氧传感器入半导体型TiO2氧传感器的工作原理及其在汽车中的应用。     

Neural networks for the identification and control of blast furnace hot metal quality

The operation and control of blast furnaces poses a great challenge because of the difficult measurement and control problems associated with the unit. The measurement of hot metal composition with respect to silica and sulfur are critical to the economic operation of blast furnaces. The measurement of the compositions require spectrographic techniques which can be performed only off line. An alternate technique for measuring these variables is a Soft Sensor based on neural networks. In the present work a neural network based model has been developed and trained relating the output variables with a set of thirty three process variables. The output variables include the quantity of the hot metal and slag as well as their composition with respect to all the important constituents. These process variables can be measured on-line and hence the soft sensor can be used on-line to predict the output parameters. The soft sensor has been able to predict the variables with an error less than 3%. A supervisory control system based on the neural network estimator and an expert system has been found to substantially improve the hot metal quality with respect to silicon and sulfur.     

Simulation and fabrication of piezoresistive membrane type MEMS strain sensors

Two piezoresistive (n-polysilicon) strain sensors on a thin Si₃N₄/SiO₂ membrane with improved sensitivity were successfully fabricated by using MEMS technology. The primary difference between the two designs was the number of strips of the polysilicon patterns. For each design, a doped n-polysilicon sensing element was patterned over a thin 3 μm Si₃N₄/SiO₂ membrane. A 1000×1000 μm² window in the silicon wafer was etched to free the thin membrane from the silicon wafer. The intent of this design was to fabricate a flexible MEMS strain sensor similar in function to a commercial metal foil strain gage. A finite element model of this geometry indicates that strains in the membrane will be higher than strains in the surrounding silicon. The values of nominal resistance of the single strip sensor and the multi-strip sensor were 4.6 and 8.6 kΩ, respectively. To evaluate thermal stability and sensing characteristics, the temperature coefficient of resistance [TCR=(ΔR/R₀)/ΔT] and the gage factor [GF=(ΔR/R₀)/] for each design were evaluated. The sensors were heated on a hot plate to measure the TCR. The sensors were embedded in a vinyl ester epoxy plate to determine the sensor sensitivity. The TCR was 7.5×10⁻⁴ and 9.5×10⁻⁴/°C for the single strip and the multi-strip pattern sensors. The gage factor was as high as 15 (bending) and 13 (tension) for the single strip sensor, and 4 (bending) and 21 (tension) for the multi-strip sensor. The sensitivity of these MEMS sensors is much higher than the sensitivity of commercial metal foil strain gages and strain gage alloys.     

Diagnostic techniques for the dynamics of a thin liquid film under forced flow and evaporating conditions

Motivated by quantification of micro-hydrodynamics of a thin liquid film which is present in industrial processes, such as spray cooling, heating (e.g., boiling with the macrolayer and the microlayer), coating, cleaning, and lubrication, we use micro-conductive probes and confocal optical sensors to measure the thickness and dynamic characteristics of a liquid film on a silicon wafer surface with or without heating. The simultaneous measurement on the same liquid film shows that the two techniques are in a good agreement with respect to accuracy, but the optical sensors have a much higher acquisition rate up to 30 kHz which is more suitable for rapid process. The optical sensors are therefore used to measure the instantaneous film thickness in an isothermal flow over a silicon wafer, obtaining the film thickness profile and the interfacial wave. The dynamic thickness of an evaporating film on a horizontal silicon wafer surface is also recorded by the optical sensor for the first time. The results indicate that the critical thickness initiating film instability on the silicon wafer is around 84 μm at heat flux of ~56 kW/m². In general, the tests performed show that the confocal optical sensor is capable of measuring liquid film dynamics at various conditions, while the micro-conductive probe can be used to calibrate the optical sensor by simultaneous measurement of a film under quasi-steady state. The micro-experimental methods provide the solid platform for further investigation of the liquid film dynamics affected by physicochemical properties of the liquid and surfaces as well as thermal-hydraulic conditions.     

热线式传感器的研究

介绍了热线式传感器的工作原理。以横风传感器为例说明了热线式传感器的结构设计、实验模型、数据分析和一种消除环境温度影响的方法。重点阐述了恒压和恒温工作方式下热线式传感器的数学模型和设计方法。实际研制了热线式横风传感器,并通过实验测试了该传感器工作于恒压或恒温方式时所达到的性能指标。     

NASICON-based solid-electrolyte cell as transducer for enzyme sensors

Enzyme sensors for glucose and uric acid have been developed based on a solid-electrolyte cell using NASICON (Na₃Zr₂Si₂PO₁₂). These potentiometric devices respond reversibly to glucose and uric acid over a concentration range of two orders of magnitude with sensitivities of −54 and −52 mV/decade, respectively. The sensors can be used for a batch-type as well as a flow-through-type measuring system. Primarily the sensors respond to the H₂O₂ that is produced by the enzymatic reactions. The role of the three-phase region, electrolyte solution, sensing electrode metal and NASICON has been investigated. The liquid electrolyte/sensing electrode metal interface is found to work as a potential-determining as well as a rate-determining interface for the enzyme sensor.     

计算机模拟优化的葡萄糖传感器阵列

介绍一种可植入的葡萄糖传感器阵列的设计和计算机模拟优化。葡萄糖传感器采用固定葡萄糖氧化酶层的氧电极和氧参比电极。考虑到葡萄糖传感器的使用寿命，本设计采用氧电极阵列。用计算机对氧电极阵列的氧电极排列的间距和相互影响进行了计算机模拟优化。考虑到葡萄糖传感器在体植入环境的氧浓度较低，而葡萄糖浓度较高，所以采用特殊的膜的结构，以提高葡萄糖传感器的测量范围，并用计算机模拟优化了膜的结构尺寸。     

A methodology to extract dynamic compact thermal models under time-varying boundary conditions: application to a thermopile based IR sensor

This paper presents the extraction of a boundary independent dynamic compact thermal model (DCTM). The paper specifically focuses on time-varying Dirichlet boundary conditions influence and the methodology proposed to obtain the DCTM is applied to a thermopile based infrared (IR) sensor. These type of sensors are quite sensitive to environment changes because a variation in the sensor bulk silicon temperature usually generates a different temperature influence in the hot and cold areas that can produce incorrect transient measurements of the incident IR radiation. A DCTM can be used to estimate the influence of the environmental temperature evolution in the sensor output and with the help of a temperature sensor correct the measurement of the IR incident radiation in the real device. The methodology to construct the DCTM is based in the construction of an equivalent thermal RC network, the topology of which, as well as its component values, are obtained from the analysis of the dynamic power-temperature relationship on the points of interest.     

Optochemical hydrogen peroxide sensor based on oxygen detection

A novel hydrogen peroxide sensor based on an optochemical oxygen sensor is presented. An oxygen sensitive membrane is covered with an additional layer containing inorganic catalysts which decompose hydrogen peroxide to water and oxygen. The oxygen is detected in the underlying oxygen sensitive membrane via luminescence quenching. The investigated concentration range for the reported sensor was between 0.1 and 2 wt.% hydrogen peroxide in water. Several catalysts were tested for this application with manganese dioxide being the preferred material. In addition to this, it was shown that by coating the sensor with a proper polymer layer, the hydrogen peroxide sensitivity could be improved up to five times compared to an uncoated sensor. The response times of the sensors depends on the type of covering layer, with the shortest response times being similar to that of uncoated sensors (t₉₅ was approximately 1 min for a change from 0 to 0.2 wt.% hydrogen peroxide in water).     

Method for flow measurement in microfluidic channels based on electrical impedance spectroscopy

We have developed and characterized two novel micro flow sensors based on measuring the electrical impedance of the interface between the flowing liquid and metallic electrodes embedded on the channel walls. These flow sensors are very simple to fabricate and use, are extremely compact and can easily be integrated into most microfluidic systems. One of these devices is a micropore with two tantalum/platinum electrodes on its edges; the other is a micro channel with two tantalum/platinum electrodes placed perpendicular to the channel on its walls. In both sensors the flow rate is measured via the electrical impedance between the two metallic electrodes, which is the impedance of two metal–liquid junctions in series. The dependency of the metal–liquid junction impedance on the flow rate of the liquid has been studied. The effects of different parameters on the sensor’s outputs and its noise behavior are investigated. Design guidelines are extracted and applied to achieve highly sensitive micro flow sensors with low noise.     

基于LSCM/3YSZ致密扩散障型极限电流氧传感器的研究

采用固相法制备了LSCM(La0.75Sr0.25Cr0.5Mn0.5O3)粉体。按不同质量比将其与3%-mol氧化钇稳定氧化锆粉体(3YSZ)混合,制备得到系列混合导体。根据热膨张系数、微观形貌等物理特性,选取合适比例的混合导体。采用Pt浆粘合法将其与8YSZ固体电解质叠层制作成致密扩散障型极限电流氧传感器。经测试,使用LSCM质量比分别为60%和70%的混合导体作为致密扩散障时,对应的氧传感器在973 K氧浓度分别为6 000×10-6～2.28%和1.22%～8.01%范围内具有良好的测氧特性,并且极限电流与氧浓度之间存在良好的线性关系;其在不同氧浓度下的响应时间曲线显示传感器重复性好,响应时间约数十秒。