Process monitoring method based on correlation variable classification and vine copula

Chemical processes are becoming increasingly complicated, leading to an increase in process variables and more complex relationships among them. The vine copula has a significant advantage in portraying the dependence of high-dimensional variables. However, as the dimensions increase, the vine copula model incurs a high computational load; such pressure greatly reduces model efficiency. Relationships among variables in the industrial process are complex. Different variables may be strongly or weakly associated or even independent. This paper proposes a process monitoring method based on correlation variable classification and vine copula. The weighted correlation measure is first used to divide variables into a correlated subspace and weakly correlated subspace. Then, two vine structures, C-vine and D-vine, are applied to the correlated and weakly correlated subspaces, respectively. This method takes advantage of C-vine for correlated variables and the flexibility of D-vine for weakly correlated variables. Finally, comprehensive statistics are established based on different subspaces. Monitoring results of the numerical system and the Tennessee Eastman process demonstrate the effectiveness and validity of the proposed method.     

Inferring kinetic dissolution of NaCl in aqueous glycol solution using a low-cost apparatus and population balance model

An experimental methodology for inferring brine dissolution rate in monoethylene glycol (MEG) solutions at different temperatures using a webcam combined with a mathematical model is presented. The measurement system is designed to track the RGB (red, green, and blue) colour variations during the dissolution process. A dynamic model augmented with the population balance equation is applied to describe the dissolution process. Moreover, the dissolution rate is consistently related to the temperature and MEG concentration through the driving force based on the Gibbs energy and chemical affinity. The applied low-cost measurement apparatus proved to be a useful resource for tracking the dissolution dynamics in a wide range of undersaturation.     

大采高工作面过断层破碎带围岩控制技术研究

为了研究大采高工作面断层破碎带围岩控制技术,采用UDEC分别模拟工作面揭露断层前后围岩应力变化规律、揭露断层时覆岩运移规律。根据模拟结果可知,断层导致工作面应力呈"几"字型分布及顶底板变形量增大。在断层影响区域采用锚网索、单体液压支柱挑棚联合支护取得了良好的效果。     

Structural properties and sensing performance of CeTiO3 ceramic films as a solid-state pH sensor

In this paper, we have studied the impact of postannealing treatment on the structural properties and sensing characteristics of CeTiO₃ ceramic membranes deposited on Si substrate by sputtering for solid-state electrolyte-insulator-semiconductor (EIS) pH sensors. X-ray photoelectron spectroscopy, Auger electron spectroscopy, X-ray diffraction, and atomic force microscopy were used to study the chemical compositions, elemental depth profiles, film structures, and surface morphologies of CeTiO₃ ceramic membranes treated at three rapid thermal annealing (RTA) temperatures of 700, 800 and 900?°C. The sensing performance of the CeTiO₃ ceramic membranes annealed at three different RTA temperatures is strongly correlated to their structural properties. The CeTiO₃ EIS device after RTA at 800?°C exhibited the best sensing characteristics (pH sensitivity, hysteresis voltage and drift rate) among these RTA temperatures. We attribute this behavior to the optimal RTA temperature enhancing the Ce³⁺/Ce⁴⁺ ratio of CeTiO₃ ceramic membrane, reducing an interfacial layer at the CeTiO₃-Si interface, and increasing its surface roughness.     

Ultrasonic vibration mill-grinding of single-crystal silicon carbide for pressure sensor diaphragms

Single-crystal silicon carbide (SiC) has gained tremendous attention for harsh-environment sensor applications due to its high-temperature tolerance and chemical resistance. However, there are many technological challenges in the fabrication of single-crystal SiC sensing microstructures such as thin SiC diaphragms for pressure sensors. This paper presents an ultrasonic vibration mill-grinding (UVMG) technique for the fabrication of 6H-SiC sensor diaphragms. The fundamental machining characteristics of UVMG are investigated experimentally compared with conventional mill-grinding (CMG). The experimental results show that the axial grinding force in UVMG is reduced by 60–70% compared to that in CMG. In addition, the wheel loading is severe in CMG, while the issue of wheel loading is significantly alleviated in UVMG due to the discontinuous cutting characteristic achieved in this method. As a result, sharp increase of the axial grinding force, which is accompanied by the crack of SiC workpiece, happens frequently in CMG after a total grinding depth of 200 µm. By contrast, the axial grinding force is stable in UVMG during the total grinding depth of at least 900 µm. The ultrasonic vibration in UVMG results in rough surface finish due to the material-removal mechanism of brittle fracture. However, by taking the advantages of better machining stability in UVMG and better surface roughness in CMG, extremely thin SiC sensor diaphragms with satisfactory surface quality can be achieved. Finally, we demonstrate the successful fabrication of a thin SiC diaphragm with a thickness of 20.3 µm.     

Prevailing Research Trends in Carbon Nanohorn and Polymer-based Hybrids

This review outlines research progress on carbon nanohorn (CNH) and polymer/CNH hybrids including structure, properties, application, and future stance. Carbon nanohorn is a type of nanocarbon existing as dahlia-like, bud-like, and seed-like structures. Most widely known form is single-walled carbon nanaohorn with diameter of ～5?nm and tube length ～50?nm. Polymers such as polystyrene, polyaniline, polythiophene, poly(vinylalcohol), poly(methylmethacrylate), poly(ethyleneglycol), polycaprolactone, polyimide, poly(2-aminopyridine), and nylon have been interacted with CNH using various techniques. Structural and physical properties of fine-tuned carbon nanohorn and polymer/CNH hybrids have been used for versatile applications such as dye-sensitized solar cell, supercapacitor, drug delivery, fuel cell, and sensors.     

综合改进奇异谱分解和奇异值分解的齿轮故障特征提取方法

针对齿轮故障特征微弱，在强背景噪声下难以有效提取的问题，提出了一种改进奇异谱分解（ISSD）结合奇异值分解（SVD）的齿轮故障特征提取方法。针对奇异谱分解（SSD）算法中模态参数需凭经验选取的缺陷，基于散布熵优化算法对SSD算法进行了改进，在得到既定的一组奇异谱分量的基础上，根据峭度值最大准则筛选出了最佳奇异谱分量并进行了SVD处理，采用奇异值能量标准谱自适应地确定了信号重构阶数以还原信号和提高降噪效果。最后对信号进行包络解调以提取齿轮故障特征，将所提方法运用到仿真信号和齿轮实测信号中，并同传统包络谱、SSD包络谱以及经验模态分解结合SVD(EMD-SVD)方法进行了对比分析，结果表明，所提方法的降噪和特征提取效果更佳，能够更加有效地实现齿轮故障的判别。