The Application of Advanced Signal Processing Techniques to Induction Motor Bearing Condition Diagnosis

Four approaches based on bispectral and wavelet analysis of vibration signals are investigated as signal processing techniques for application in the diagnosis of a number of induction motor rolling element bearing faults. The bearing conditions considered are a normal bearing and bearings with cage and inner and outer race faults. The vibration analysis methods investigated are based on the bispectrum, the bispectrum diagonal slice, the summed bispectrum and wavelets. Singular value decomposition (SVD) is used to extract the most significant features from the vibration signatures and the features are used as inputs to an artificial neural network trained to identify the bearing faults. The results obtained show that the diagnostic system using a supervised multi-layer perceptron type neural network is capable of classifying bearing condition with high success rate, particularly when applied to summed bispectrum signatures.     

Numerical simulation of turbulent free-surface flow in curved channel

This paper presents first results of numerical simulation of turbulent free-surface flow. Simple implementation of surface capturing method is based on the variable density approach. The flow is treated as if there is only one fluid, but with variable material properties (density, viscosity). The switch in these values is done by a function resulting from the mass conservation principle. This approach simplifies the implementation of turbulence model. In this case the SST k−ω model was chosen in modification given by Hellsten.Numerical solution was carried out by finite-volume method with explicit Runge-Kutta time-integration. The artificial compressibility method was used for time-marching search for steady state solution. The whole model was tested on horizontally placed square-sectioned 90^∘ bend, which was partially filled by the water. The main goal of this study was to demonstrate the applicability of this model and solution method for capturing the water-air interface as well as for predicting the turbulent effects in both fluids.     

Effect of promoters on dynamics of gas-solid fluidized bed Statistical and ANN approaches

In this study, a bubbling fluidized bed column, 99 mm in inside diameter and 960 mm in height, was used to investigate the effect of rod and disc promoters on fluctuation and expansion ratios. Factorial design （statistical approach） and artificial neural network （ANN） models were developed to predict the fluctuation and expansion ratios in this gas-solid fluidized bed with varying gas flow rates, bed heights, particle sizes and densities. The fluctuation and expansion predicted using these statistical and ANN models, for beds with and without promoters, were found to agree well with corresponding experiments. The statistical model was found to be superior to the ANN model due to its ability to take into account both individual and interactive effects. The rod promoters were found to be more effective in reducing bed fluctuation, and in increasing bed expansion at high gas mass velocities.     

FT-IR,EPR and SEM–EDAX investigation of some accelerated aged painting binders

The results of FT-IR, SEM–EDAX and EPR investigations of some binders used in classical paintings and artificial aged binders, i.e. linseed oil, hen yolk and linseed oil/hen yolk are presented and discussed. Carbon dioxide, sulfur dioxide as well as nitrogen oxides were used as aging agents. Accordingly, the FT-IR spectra of all binders showed a set of characteristic modifications. This makes it possible to select the most representative bands which, acting as sui generis fingerprints, provided evidence of certain specific combinations for each binder and the polluting agents. The EPR spectroscopy was helpful in choosing the most appropriate chemical reactions whose products were identified in the corresponding FT-IR spectra. Moreover, the SEM–EDAX data allowed us to establish that, in the case of CO₂ aging, the patina consists of finely dispersed carbon aggregates. Within this context, the most plausible chemical reactions explaining the observed changes were proposed and discussed.     

Correlation of solubility data of ammonia in ionic liquids for gas separation processes using artificial neural networks

Artificial neural networks have been used for the correlation and prediction of solubility data of ammonia in ionic liquids. This solubility of ammonia is highly variable for different types of ionic liquids at the same temperature and pressure, its correlation and prediction is of special importance in the removal of ammonia from flue gases for which effective and efficient solvents are required. Nine binary ammonia + ionic liquids mixtures were considered in the study. Solubility data (P–T–x) of these systems were taken from the literature (208 data points for training and 50 data points for testing). The training variables are the temperature and the pressure of the binary systems (T, P), being the target variable the solubility of ammonia in the ionic liquid (x). The study shows that the neural network model is a good alternative method for the estimation of solubility for this type of mixtures. Absolute average deviations were below 5.6%, for each isothermal data set and overall absolute average deviations were below 3.0%. Only in the range of low solubility (below 0.2 in mole fraction) did predicted solubility give deviations higher than 10%.     

Chitosan Based Diamond Paste Stochastic Microsensors Modified with Gold Nanoparticles Detect Hepatitis C Virus Core Antigen

Three types of chitosan (chitosan I (n=371–744), chitosan II (n=682–930), and chitosan III (n=868–1365)) as well as gold nanoparticles (10 nm diameter) were used to modify diamond paste for the design of new stochastic microsensors. Hepatitis C virus core antigen was used as model analyte to prove the stochastic behavior of the proposed microsensors. The microsensors cover a linear range of concentration between 40 fg/mL and 4 ng/mL. The highest sensitivity (1.38×10⁵ s^?1/mg/mL) and the lower limit of determination (40 fg/mL) were obtained for chitosan III based microsensor. The hepatitis C virus core antigen was assayed from whole blood samples with recoveries higher than 98.00 %.     

Genetic studies of rheumatoid arthritis

Rheumatoid arthritis (RA) is a common autoimmune disease that results in significant morbidity. As with other complex disorders, genome-wide association studies (GWASs) have greatly contributed to the current understanding of RA etiology. In this review, we describe the genetic configuration of RA as revealed primarily through GWASs and their meta-analyses. In addition, we discuss the pathologic mechanisms of RA as suggested by the findings of genetic and functional studies of individual RA-associated genes, including HLA-DRB1, PADI4, PTPN22, CCR6 and FCRL3, and the potential use of genetic information for RA treatment in clinical practice.     

直膨式空调人工神经网络在线自适应控制器应用研究

直接膨胀式空调系统人工神经网络控制器已经有了一些研究成果,为了解决控制器控制范围和精度的问题,引入在线自适应控制系统。该控制器的控制能力测试采用直接膨胀式空调系统实验装置进行。试验结果表明,基于人工神经网络动态模型的在线自适应控制器进行训练的前提下,该控制器能够将室内空气的干球和湿球温度控制在一定范围内,具有较高的控制精度。     

人工神经网络分光光度法同时测定钼和铬

在钼,铬－二溴羟基苯基荧光酮－ＣＴＭＡＢ显色体系中,应用三层ＡＮＮ－ＢＰ网络解析钼和铬的吸收光谱,不经分离分光光度法同时测定钼和铬。钼和铬的表观摩尔吸光系数分别为ε５３０＝１．４×１０＾５Ｌ·ｍｏｌ＾－１·ｃｍ＾－１,ε５１２＝３．７×１０＾４Ｌ·ｍｏｌ＾－１·ｃｍ＾－１。以合金钢中钼和铬进行了同时测定,结果满意。使用改进的ＢＰ算法,避免了神经网络学习过程中可能产生的麻痹现象,提出了目标向量的简单     

Vertical quantum dots at high magnetic fields beyond the few-electron limit

We describe phenomena that can be studied in vertical quantum dot single electron transistors. Moving from the few-electron to the several- and many-electron regimes, features in the conductance peaks initially related to spin polarization evolve with magnetic field. This allows us to first probe the spin-flip region beyond the last single-particle crossing at low field, and then the formation and stability of the spin-polarized maximum density droplet at high field. According to a simple capacitance model, charge redistribution in the dot at higher magnetic fields is accompanied by abrupt changes in the area of the droplet.