基于电信号特征分析的电机故障诊断技术

介绍了电机故障诊断技术平台的组成,分析了电机常见故障下电信号的特征。利用宜昌和景洪工厂两台电机进行了实际对比测试,宜昌工厂电机定子电流特征频率在49.2Hz时表现出峰值-36.08dB,在50.8Hz时表现峰值则为-37.23dB,表明电机存在转子断条故障;景洪工厂电机在转子特征频率为113.51Hz时,出现峰值-58.47dB,表明电机存在静态偏心故障。经电机现场抽芯检查,验证了电机故障快速诊断平台给出的电机健康状态评估结果,证实了基于电信号特征分析的电机故障诊断技术的准确性。     

Differential gene expression of the healthy conjunctiva during the day

PurposeTo determine if there is diurnal variation in gene expression in normal healthy conjunctival cells.MethodsBulbar conjunctival swab samples were collected from four healthy subjects in the morning and evening of the same day. The two swab samples were taken from one eye of each participant, with a minimum of five hours gap between the two samples. RNA was extracted and analysed using RNA sequencing (RNA-Seq).ResultsA total of 121 genes were differentially expressed between the morning and the evening conjunctival samples, of which 94 genes were upregulated in the morning, and 27 genes were upregulated in the evening. Many of the genes that were upregulated in the morning were involved in defence, cell turnover and regulation of gene expression, while the genes upregulated in the evening were involved in signalling and mucin production.ConclusionsThis study has identified several genes whose expression changes over the course of the day. Knowledge of diurnal variations of conjunctival gene expression provides an insight into the regulatory status of the healthy eye and provides a baseline for examining changes during ocular surface disease.     

Study on vapour dispersion and explosion from compressed hydrogen spill: Risk assessment on a hydrogen plant

Hydrogen produced from renewable resources is one of the cleanest fuels and could be used to store intermittent solar, wind and other energies. The main concern about using hydrogen is its hazards, such as high storage pressure, wide-range flammability, low mass density, and high diffusion. This study investigated the hazards of compressed hydrogen storage by developing a CFD model to understand the gas dispersion behaviour. The model was validated using the past experimental data and showed a good agreement, which could demonstrate the diffusion characteristics and gas stratification of a buoyant gas. A case study of an accidental release of compressed hydrogen from a storage tank was investigated to evaluate the risk of a hydrogen plant. A mathematical model of the jet spill was used to account for the choking effect from a high-pressure release to ensure the input velocity in CFD simulation is suitable for modelling gas dispersion using verified spatial and temporal scales, then the simulation results were used as inputs of vapour cloud explosions (VCEs) to investigate the potential overpressure effect. It was found the CFD model could predict a more reasonable flammable gas amount in cloud than using the bulk hydrogen release rate. The safety distance based on the overpressure prediction was reduced by 35%. The method proposed in this study can provide more validity for the consequence analysis as part of risk assessment.     

Impedance matching optimization of SiCf/Si3N4–SiOC composites for excellent microwave absorption properties

SiC fiber reinforced ceramic matrix composites (SiC_f-CMCs) are considered to be one of the most promising materials in the electromagnetic (EM) stealth of aero-engines, which is expected to achieve strong absorption and broad-band performance. Multiscale structural design was applied to SiC_f/Si₃N₄–SiOC composites by construction of micro/nanoscale heterogeneous interfaces and macro double-layer impedance matching structure. SiC_f/Si₃N₄–SiOC composites were fabricated by using SiC fibers with different conductivities and SiOC–Si₃N₄ matrices with gradient impedance structures to improve impedance matching effectively. Owing to its unique structure, SiC_f/Si₃N₄–SiOC composites (A3-composites) achieved excellent EM wave absorption performance with a minimum reflection coefficient (RC_min) of ?25.1 dB at 2.45 mm and an effective absorption bandwidth (EAB) of 4.0 GHz at 2.85 mm in X-band. Moreover, double-layer SiC_f/Si₃N₄–SiOC with an improved impedance matching structure obtained an RC_min of ?56.9 dB and an EAB of 4.2 GHz at 3.00 mm, which means it can absorb more than 90% of the EM waves in the whole X-band. The RC is less than ?8 dB at 2.6–2.8 mm from RT to 600 °C in the whole X-band, displaying excellent high-temperature absorption performance. The results provide a new design opinion for broad-band EM absorbing SiC_f-CMCs at high temperatures.     

Spin-state regulating of cobalt assisted by iron doping and coordination for enhanced oxygen evolution reaction

Customizing catalysts from the electronic structure, such as spin state, is an effective but challenging strategy for oxygen evolution reaction (OER). Herein, an ultrafine Co–Fe material highly dispersed on nitrogen carbide matrix is fabricated by coordination polymer and self-templating method to scrutinize the impact of spin state of Co on OER through Fe doping. The optimized catalyst shows boosted OER performance, which only requires overpotential of 333 mV at 10 mA cm^?2, outperforming other control samples and commercial RuO₂. The elevated local spin states of Co by Fe doping lead to charge transfer acceleration and fast generation of oxygenated intermediates, which is proved to account for the OER elevation. In addition, the long-term stability of Co–Fe material is guaranteed by the strong coordination of Co/Fe to the melamine-formaldehyde resin, which is used to adsorb metal ions, contributing to the high dispersion of active sites during the OER process.     

Synthesis and characterizations of highly responsive H2S sensor using p-type Co3O4 nanoparticles/nanorods mixed nanostructures

High-quality p-type semiconducting Co₃O₄ with mixed morphology of nanoparticles/nanorods are synthesized using a hydrothermal route for high response and selective hydrogen sulphide (H₂S) sensor application. XRD and Raman studies revealed the crystal structure and molecular bonding for obtained Co₃O_4, respectively. The nanoparticles/nanorods-like structures were confirmed for Co₃O₄ using FESEM and TEM analysis. The EDS and XPS spectra analysis were carried out for elemental composition and chemical atomic states of Co₃O₄. The Co₃O₄ sensor is investigated for gas sensing properties in dynamic conditions. The sensor exhibited the highest selectivity towards H₂S among various hydrogen-contained gases at 225 °C. The sensor revealed a high response of 357% and 44% for 100 and 10 ppm H₂S gas concentrations, respectively. The Co₃O₄ sensor exhibited a systematic dynamic resistance response for 100–10 ppm range H₂S gas. The excellent dynamic resistance repeatability of the sensor was shown towards 25 ppm H₂S gas. The response of Co₃O₄ sensor was investigated at different operating temperatures and H₂S concentrations. The sensor stability and H₂S sensing mechanism for the Co₃O₄ sensor have been reported. Highly uniform and mixed nanostructures of Co₃O₄ can be the potential sensor material for real-time high-performance H₂S sensor application.     

A high temperature and pressure framework for supercritical water electrolysis

Water electrolysis technologies aim to provide a significant increase in green hydrogen production efficiency. In this work, a framework was developed to explore the use of supercritical water for alkaline electrolysis. This framework was used to perform Arrhenius analysis as a function of potential, and to explore activation energies for sub- and supercritical water electrolysis. An analysis of the conductivity of solution unveiled a discontinuity in the trends between sub- and supercritical potassium hydroxide solution conductivity. Unlike prior work on supercritical water electrolysis, this work investigates trends in electrochemical parameters, the sources of these trends, and how they change between the sub- and supercritical regimes.     

Fluid sloshing thermo-mechanical characteristic in a cryogenic fuel storage tank under different gravity acceleration levels

Fluid sloshing usually causes serious safety issues on the dynamic stability and propellant thermal management during the powered-flight phase of launch vehicle. With the wide using of cryogenic propellants, the coupled thermo-mechanical performance during fluid sloshing becomes more prominent. In the present study, one numerical model is established to simulate fluid sloshing by using the VOF method coupled with the mesh motion treatment. The phase change occurring within the tank is considered. Both the experimental validation and mesh sensitivity analysis are made. It shows that present numerical model is acceptable. Based on the developed numerical model, the effect of different super gravity accelerations on fluid sloshing hydrodynamic characteristic is numerically researched. The fluid pressure variation, the sloshing force and sloshing moment, the interface dynamic response and the interface shape variation are investigated, respectively. It shows that the gravity acceleration has caused obvious influences on fluid sloshing characteristic. When the gravity acceleration is higher than 4g₀, fluid sloshing becomes more obvious and must be paid enough attention. With some valuable conclusions obtained, the present work is of great significance for in-depth understanding of fluid sloshing mechanism.     

Preparation of high-purity SiC ceramics with good plasma corrosion resistance by hot-pressing sintering

High-purity SiC ceramic devices are applied in semiconductor industry owing to their outstanding properties. Nevertheless, it is difficult to densify SiC ceramics without any sintering additive even by HP sintering. In this work, high-purity and dense SiC ceramics were fabricated by HP sintering with very low amounts of sintering aids. Residual B content was only 556 ppm and relative density was more than 99.5%. Furthermore, thermal conductivity of as-prepared SiC ceramics was improved from 155 W m^?1 K^?1 to 167 W m^?1 K^?1 by increasing holding time and their plasma corrosion resistance was promoted in the meantime. The as-prepared high-purity SiC ceramics have broad application prospects in the field of semiconductor industry.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).