Time-Frequency Fault Feature Extraction for Rolling Bearing Based on the Tensor Manifold Method

Rolling-bearing faults can be effectively reflected using time-frequency characteristics. However, there are inevitable interference and redundancy components in the conventional time-frequency characteristics. Therefore, it is critical to extract the sensitive parameters that reflect the rolling-bearing state from the time-frequency characteristics to accurately classify rolling-bearing faults. Thus, a new tensor manifold method is proposed. First, we apply the Hilbert-Huang transform (HHT) to rolling-bearing vibration signals to obtain the HHT time-frequency spectrum, which can be transformed into the HHT time-frequency energy histogram. Then, the tensor manifold time-frequency energy histogram is extracted from the traditional HHT time-frequency spectrum using the tensor manifold method. Five time-frequency characteristic parameters are defined to quantitatively depict the failure characteristics. Finally, the tensor manifold time-frequency characteristic parameters and probabilistic neural network (PNN) are combined to effectively classify the rolling-bearing failure samples. Engineering data are used to validate the proposed method. Compared with traditional HHT time-frequency characteristic parameters, the information redundancy of the time-frequency characteristics is greatly reduced using the tensor manifold time-frequency characteristic parameters and different rolling-bearing fault states are more effectively distinguished when combined with the PNN

Fabrication of a Needle Microsensor and Its Applications in the Detection of Dissolved Oxygen

A novel needle microsensor measurement system was fabricated and applied to determine the concentration of dissolved oxygen. Platinum nanoparticles were employed to modify the surface of copper-core electrode in order to improve electrochemical response signal. The homemade electrode displayed efficient electrocatalytic reduction activity towards dissolved oxygen. The sensor responded linearly to dissolved oxygen in the range of 10 μM to 0.195 mM and had a remarkable sensitivity of 9.02 μA/mM. In addition, it showed an excellent reproducibility, stability, and selectivity. These results indicated that the needle microsensor when used, could yield good performance. Moreover, it is believed to be a potential tool for studying specific substances at a cellular level or in vivo in future

A study on the treatment effects of Crataegus pinnatifida polysaccharide on non-alcoholic fatty liver in mice by modulating gut microbiota

The objective of this study was to investigate the protective effect of Crataegus pinnatifida polysaccharide (CPP) on non-alcoholic fatty liver disease (NAFLD) induced by a high-fat diet (HFD) in mice. The findings demonstrated that CPP improved free fatty acid (FFA)-induced lipid accumulation in HepG2 cells and effectively reduced liver steatosis and epididymal fat weight in NAFLD mice, as well as decreased serum levels of TG, TC, AST, ALT, and LDL-C. Furthermore, CPP exhibited inhibitory effects on the expression of fatty acid synthesis genes FASN and ACC while activating the expression of fatty acid oxidation genes CPT1A and PPARα. Additionally, CPP reversed disturbances in intestinal microbiota composition caused by HFD consumption. CPP decreased the firmicutes/Bacteroidetes ratio, increased Akkermansia abundance, and elevated levels of total short-chain fatty acid (SCFA) content specifically butyric acid and acetic acid. Our results concluded that CPP may intervene in the development of NAFLD by regulating of intes-tinal microbiota imbalance and SCFAs production. Our study highlights that CPP has a potential to modulate lipid-related pathways via alterations to gut microbiome composition thereby ex-erting inhibitory effects on obesity and NAFLD development

Thin film composite (TFC) membranes with improved thermal stability from sulfonated poly(phthalazinone ether sulfone ketone) (SPPESK)

Sulfonated poly(phthalazinone ether sulfone ketone)s (SPPESK) were used to prepare thin film composite (TFC) membranes having increased thermal stability, hydrophilicity and potentially improved fouling-resistance. TFCs were prepared from SPPESK having a degree of sulfonation (DS) 1.5 as the top selective layer coated onto polysulfone (PSF) or poly(phthalazinone ether sulfone ketone)s (PPESK) asymmetric support membranes. At room temperature and 0.25 MPa pressure SPPESK/PSF composite membrane rejections for 1000 ppm Na2SO4 and NaCl were 91 and 41%, respectively and solution fluxes were 30 and 35 kg m\u87222 h\u87221. A SPPESK/PPESK, TFC membrane had rejections for Na2SO4 and NaCl of 67 and 30%, respectively with similar solution fluxes. Another SPPESK/PPESK membrane had a rejection 63% for 100 ppm Clayton Yellow dye (CY, MW=695) while the solution flux was 62 kg m\u87222 h\u87221. When the feed solution temperature increased from 20 to 120 \ub0C, solution flux was increased four-fold and the rejection decreased by 14%. The properties of the membrane were almost unchanged from the original values after the membrane was heated at 130 \ub0C for 1 h and then decreased to 20 \ub0C. Author Keywords: Composite membrane; Nanofiltration; Ultrafiltration; ThermostabilityNRC publication: Ye

A Data-Driven Method for Calculating Neutron Flux Distribution Based on Deep Learning and the Discrete Ordinates Method

The efficient and accurate calculation of neutron flux distribution is essential for evaluating the safety of nuclear facilities and the surrounding environment. While traditional numerical simulation methods such as the discrete ordinates (SN) method and Monte Carlo method have demonstrated excellent performance in terms of accuracy, their complex solving process incurs significant computational costs. This paper explores a data-driven and efficient method for obtaining neutron flux distribution based on deep learning, specifically targeting shielding problems with constant geometry and varying material cross-sections in practical engineering. The proposed method bypasses the intricate numerical transport calculation process of the discrete ordinates method by constructing a surrogate model that captures the correlation between transport characteristics and neutron flux from data characteristics. Simulations were carried out using Kobayashi-1 and Kobayashi-2 geometric models for shielding problems with constant geometry and varying material cross-sections. A series of validations have proved that the data-driven surrogate model demonstrates high generalization ability and reliability, while reducing the time required to obtain neutron flux distribution to 0.1 s without compromising on calculation accuracy compared to the discrete ordinates method

Experimental Study on the Mechanical Property of Loess Mixed with Bentonite-HDTMA

Malan loess in the middle and lower reaches of the Yellow River after mixed with different bentonite and HDTMA ratios was selected to carry out shear and consolidation tests for discussing the influence of bentonite-HDTMA on the mechanical property of loess lining material in landfills. Studies have shown that, after mixing 6% to 14% bentonite, the cohesive force of modified loess is significantly increased, the friction angle is reduced and remains stable, and the shear strength is improved. The compressibility of materials slightly decreases with the increase of bentonite ratio. The addition of 2%–4% HDTMA weakens the increment for the cohesive force caused by bentonite, but the friction angle is effectively recovered. The compressibility of materials increases with the increase of HDTMA ratio. As the dry density increases, the shear strength of the modified loess increases, and the compressibility coefficient decreases. The mechanical property of loess lining material can be optimized by adding 6%–14% bentonite. The incorporation of 2%–4% HDTMA does not have a significant negative impact on the optimization effect of bentonite. From the perspective of the mechanical property, it is recommended that the dry density of modified loess is 1.70 g/cm3, the bentonite ratio is 10%–14%, and the HDTMA ratio is 2%–4%

Effects of sulfone/ketone in poly(phthalazinone ether sulfone ketone) on the gas permeation of their derived carbon membranes

A series of copolymer, poly(phthalazinone ether sulfone ketone)s (PPESKs) with the sulfone over ketone unit (S/K) ratio varying from 20/80, 50/50 to 80/20, were used as precursors to prepare carbon membranes. The effects of chemical structure as S/K ratio of PPESKs on the microstructure and gas separation performance of their derived carbon membranes were mainly investigated. The properties of PPESKs were detected in terms of density, fractional free volume, char yield, interlayer distance and glass transition temperature. During the formation process of carbon membranes (i.e., stabilization and pyrolysis), the changes in functional groups, microstructural parameters and gas permeation were monitored by FTIR, X-ray diffraction, TEM and single gas permeation techniques. The results have shown that the microstructure and gas permeation of obtained carbon membranes are significantly affected by the S/K ratio in precursor PPESKs. Carbon membranes exhibit higher selectivity and lower permeability when prepared at low pyrolytic temperature (i.e., 650 degrees C and 800 degrees C) and from PPESKs with S/K ratio equaling 50/50, followed with 20/80 and 80/20. As for carbon membranes prepared at high pyrolytic temperature (i.e., 950 degrees C), the selectivity order of them is well in accordance with S/K mole ratio in precursor PPESKs: 20/80>50/50>80/20, and vice versa for permeability. (C) 2009 Elsevier B.V. All rights reserved

Exploring the Relationship between the Eco-Environmental Quality and Urbanization by Utilizing Sentinel and Landsat Data: A Case Study of the Yellow River Basin

Yellow River Basin urban agglomeration (YRBU) is the main carrier of regional socio-economic development in the Yellow River Basin, and its eco-environmental quality, urbanization, and coupling coordination degree are facing higher demands. It is of great significance for the development of YRBU to understand the interactive coupling relationship between the eco-environment and urbanization development from the multi-scale perspective. This research intended to understand the spatio-temporal characteristics of eco-environmental quality, urbanization, and coupling coordination degree in the study area from 2013 to 2021. We proposed an Adjusted Remote Sensing Ecological Index (A-RSEI), integrated Sentinel-2A, Landsat 8, and other remote sensing data to evaluate the eco-environmental quality of the study area, from 2013 to 2021. Coupled coordination degree (CCD) model was used to obtain the CCD between eco-environmental quality and urbanization. In addition, spatio-temporal and multi-scale analysis was carried out from the perspectives of urban agglomeration, municipal, county, and pixel scales. Combined with spatial autocorrelation analysis and Tapio decoupling model, the CCD was further explored. The results show that the proposed A-RSEI model is more suitable for monitoring the eco-environmental quality of the Yellow River Basin. The coupling coordination degree of eco-environment and urbanization in most regions of the study area are rising in a relatively green development trend. The multi-scale analysis among eco-environmental quality, urbanization, and CCD can not only indicate the impact of the central city on its surrounding areas but also help to describe the details of CCD combined with the terrain. The comprehensive discrimination of urban agglomeration and county scale is helpful to express the relationship between urbanization and eco-environmental quality centered on a certain city. The results can provide scientific support for eco-environment protection and high-quality development of the Yellow River Basin