Henan Normal University

About: Henan Normal University is a education organization based out in Xinxiang, China. It is known for research contribution in the topics: Catalysis & Ionic liquid. The organization has 10863 authors who have published 11077 publications receiving 166773 citations.

A New Online Detection Approach for Rolling Bearing Incipient Fault via Self-Adaptive Deep Feature Matching

Abstract: This paper presents a new online detection approach for rolling bearing’s incipient fault based on self-adaptive deep feature matching (SDFM). This approach includes offline and online stages. At the offline stage, a new health state assessment algorithm is first proposed based on singular value decomposition (SVD) and Kurtosis criterion. Based on the assessment results, a kind of deep learning algorithm, i.e., stacked denoising autoencoder (SDAE), is introduced to extract the common deep features of normal state and early fault state. Support vector data description (SVDD) is applied to establish the offline detection model using the obtained features. At the online stage, a self-adaptive matching strategy with 1-Dimensional anchor is proposed. By utilizing the SDAE model established at offline stage, this strategy can extract more representative deep features of the target bearing via generating various proposal fragments and then determining the fault occurrence time in a self-adaptive way by feeding the online features into the SVDD model. Experiments run on the bearing data set of IEEE prognostic and health management (PHM) Challenge 2012. The results show the proposed approach has good detection performance in real time and much lower false alarm rate, with no need to acquire fault characteristic frequency in advance.

Crystal structures and proton conductivities of a MOF and two POM-MOF composites based on Cu(II) ions and 2,2'-bipyridyl-3,3'-dicarboxylic acid.

Abstract: We have succeeded in constructing a metal-organic framework (MOF), [Cu(bpdc)(H(2)O)(2)](n) (H(2) bpdc=2,2'-bipyridyl-3,3'-dicarboxylic acid, 1), and two poly-POM-MOFs (POM=polyoxometalate), {H[Cu(Hbpdc)(H(2)O)(2)](2) [PM(12)O(40)]·nH(2)O}(n) (M=Mo for 2, W for 3), by the controllable self-assembly of H(2) bpdc, Keggin-anions, and Cu(2+) ions based on electrostatic and coordination interactions. Notably, these three compounds all crystallized in the monoclinic space group P2(1)/n, and the Hbpdc(-) and bpdc(2-) ions have the same coordination mode. Interestingly, in compounds 2 and 3, Hbpdc(-) and the Keggin-anion are covalently linked to the transition metal copper at the same time as polydentate organic ligand and as polydentate inorganic ligand, respectively. Complexes 2 and 3 represent new and rare examples of introducing the metal N-heterocyclic multi-carboxylic acid frameworks into POMs, thereby, opening a pathway for the design and the synthesis of multifunctional hybrid materials based on two building units. The Keggin-anions being immobilized as part of the metal N-heterocyclic multi-carboxylic acid frameworks not only enhance the thermal stability of compounds 2 and 3, but also introduce functionality inside their structures, thereby, realizing four approaches in the 1D hydrophilic channel used to engender proton conductivity in MOFs for the first time. Complexes 2 and 3 exhibit good proton conductivity (10(-4) to ca. 10(-3) S cm(-1)) at 100 °C in the relative humidity range 35 to about 98%.

Climate and litter C/N ratio constrain soil organic carbon accumulation

Abstract: Soil organic carbon (SOC) plays critical roles in stabilizing atmospheric CO2 concentration, but the mechanistic controls on the amount and distribution of SOC on global scales are not well understood In turn, this has hampered the ability to model global C budgets and to find measures to mitigate climate change Here, based on the data from a large field survey campaign with 2600 plots across Chinas forest ecosystems and a global collection of published data from forested land, we find that a low litter carbon-to-nitrogen ratio (C/N) and high wetness index (P/PET, precipitation-to-potential-evapotranspiration ratio) are the two factors that promote SOC accumulation, with only minor contributions of litter quantity and soil texture The field survey data demonstrated that high plant diversity decreased litter C/N and thus indirectly promoted SOC accumulation by increasing the litter quality We conclude that any changes in plant-community composition, plant-species richness and environmental factors that can reduce the litter C/N ratio, or climatic changes that increase wetness index, may promote SOC accumulation The study provides a guideline for modeling the carbon cycle of various ecosystem scales and formulates the principle for land-based actions for mitigating the rising atmospheric CO2 concentration