Application of higher order spectral features and support vector machines for bearing faults classification

Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals.     

Ni2V2O7 dandelion microsphere for a high-performance electrocatalyst in water splitting

Water splitting is an effective way to produce hydrogen to solve the energy crisis problem, and inorganic metal compounds are widely used in electrocatalysis field due to efficient hydrogen evolution reaction (HER). Herein, we synthesize Ni₂V₂O₇ dandelion microsphere from nickel nitrate and vanadium pentoxide by “one-step hydrothermal” way, which exhibits large specific surface area of 102.74 m² g⁻¹. The as-prepared Ni₂V₂O₇ microsphere shows good electrocatalysis performances including OER overpotential of 358 mV and good stability, as well as HER overpotential of 195 mV. Furthermore, the Ni₂V₂O₇ microsphere electrode is assembled to Ni₂V₂O₇ microsphere//Ni₂V₂O₇ microsphere system, showing the water splitting voltage of 1.50 V at 10 mA cm⁻² by two-electrode method, which is much lower than those of commercial RuO₂//Pt/C system and most of spinel oxides electrocatalysts. Our work opens up a new and facile avenue for fabricating inorganic microsphere electrocatalyst in hydrogen production field.     

Impact of the anode operating conditions on the liquid water distribution in the cathode gas diffusion layer

Previous experimental results indicate that the humidification conditions at the anode have an impact on the liquid water distribution in the cathode gas diffusion layer. Numerical simulations are developed to reproduce and analyze this effect. Results consistent with the experimental results are first obtained by playing with the partition coefficients of an advanced pore network model computing the liquid water formation and transfer in the cathode gas diffusion layer (GDL) for a large range of operating conditions. Then, a model for the full anode – cathode assembly is developed by combining the pore network model of the cathode GDL and a 1D model describing the heat and water transfer in the various components of the anode-cathode assembly. This enables one to generalize the dry – wet regime diagram introduced in a previous work by incorporating the effect of the humidity condition at the anode.     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

Boosting the activity of FeOOH via integration of ZIF-12 and graphene to efficiently catalyze the oxygen evolution reaction

Transition metal oxyhydroxides have been used as promising electrocatalysts for water splitting however, their catalytic activity is restricted due to low surface area and poor conductivity. Herein, we report novel composite FeOOH@ZIF-12/graphene composite as electrocatalyst for water oxidation, whereby ZIF-12 provide extra surface for the FeOOH dispersion whilst graphene act as excellent electron mediator. The composite shows a low overpotential value of 291 mV to attain a current density of 10 mA cm^?2 and a low Tafel slope value of 78 mV dec^?1. The catalyst offers a maximum current density of 101 mA cm^?2, while it gives a turnover frequency (TOF) value of 0.031 s^?1 at an overpotential of 291 mV only. The excellent activity and remarkable stability of composite is attributed to highly conductive and porous support.     

Hydrogen from wet air and sunlight in a tandem photoelectrochemical cell

A solid-state photoelectrochemical (SSPEC) cell is an attractive approach for solar water splitting, especially when it comes to monolithic device design. In a SSPEC cell the electrodes distance is minimized, while the use of polymer-based membranes alleviates the need for liquid electrolytes, and at the same time they can separate the anode from the cathode. In this work, we have made and tested, firstly, a SSPEC cell with a Pt/C electrocatalyst as the cathode electrode, under purely gaseous conditions. The anode was supplied with air of 80% relative humidity (RH) and the cathode with argon. Secondly, we replaced the Pt/C cathode with a photocathode consisting of 2D photocatalytic g-C₃N₄, which was placed in tandem with the photoanode (tandem-SSPEC). The tandem configuration showed a three-fold enhancement in the obtained photovoltage and a steady-state photocurrent density. The mechanism of operation is discussed in view of recent advances in surface proton conduction in absorbed water layers. The presented SSPEC cell is based on earth-abundant materials and provides a way towards systems of artificial photosynthesis, especially for areas where water sources are scarce and electrical grid infrastructure is limited or nonexistent. The only requirements to make hydrogen are humidity and sunlight.     

应用膨胀算法提取目标的直接定位算法

为了解决被动雷达系统中的多发射源定位问题，提出了一种基于多重信号分类(MUSIC)算法和图像膨胀(IE)算法的直接定位方法。该方法结合了谱分析中的MUSIC思想，通过对接收量测协方差矩阵进行特征分析求解目标的位置。首先，在目标个数未知的前提下，利用Akaike信息准则(AIC)来确定模型阶数；然后，推导了基于MUSIC的定位代价函数；之后，利用图像膨胀算法处理得到的代价函数平面；最后，膨胀处理后的输出为目标个数及目标位置的估计值。提出的算法有效地解决了目标检测及提取的问题，能够确定多个目标的位置坐标，为后续的定位性能分析提供可能性，也保证了算法的完整性。进一步地分析了多个临近目标情况下影响目标提取性能的主要因素。     

Hydrology,topography and demography matter: Why care needs to be exercised when assessing water prices and regulation and the extent to which they conform with best practice

Water tariffs frequently seek to achieve multiple objectives, some of which may conflict. However, the nature and rationale for those conflicts is not always understood or appreciated. This paper consider how localised natural and human phenomena can shape the extent to which so-called ‘best practice’ economic regulation and pricing can be expected to take hold in Victoria and South Australia. Overall, we find that there is room for improvement in the institutional arrangements that circumscribe water pricing in some cases, but direct comparisons are not always helpful, especially when the underlying hydrology, topography and demography of states differs markedly.     

水提法提取—电感耦合等离子体质谱法测定婴幼儿配方奶粉中的碘

用水提取婴幼儿奶粉中的碘,亚铁氰化钾和乙酸锌盐析法沉淀蛋白,过滤后可以得到澄清处理液。用电感耦合等离子体质谱对提取样液进行测定,130Te作为内标物进行定量分析。该方法简便快捷,检出限为0.10 mg/kg加标回收率为90.8%~109%,相关系数0.999,精密度试验RSD2%。