This paper proposed a wired network fault diagnosis method based on One-dimensional Convolutional Neural Network(1D-CNN) and distributed reflectometer. The paper improved the distributed reflectometer technique by pro...
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The Gini index of economic inequality appears to be by far the most important such index. Although a variety of alternative inequality measures have been proposed, only Gini's index (G) incorporates both the incom...
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Background With the increasing prominence of hand and finger motion tracking in virtual reality(VR)applications and rehabilitation studies,data gloves have emerged as a prevalent *** this study,we developed an innovat...
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Background With the increasing prominence of hand and finger motion tracking in virtual reality(VR)applications and rehabilitation studies,data gloves have emerged as a prevalent *** this study,we developed an innovative,lightweight,and detachable data glove tailored for finger motion tracking in VR *** The glove design incorporates a potentiometer coupled with a flexible rack and pinion gear system,facilitating precise and natural hand gestures for interaction with VR ***,we calibrated the potentiometer to align with the actual finger bending angle,and verified the accuracy of angle measurements recorded by the data *** verify the precision and reliability of our data glove,we conducted repeatability testing for flexion(grip test)and extension(flat test),with 250 measurements each,across five *** employed the Gage Repeatability and Reproducibility to analyze and interpret the repeatable ***,we integrated the gloves into a SteamVR home environment using the OpenGlove auto-calibration *** The repeatability analysis revealed an aggregate error of 1.45 degrees in both the gripped and flat hand *** outcome was notably favorable when compared with the findings from assessments of nine alternative data gloves that employed similar *** these experiments,users navigated and engaged with virtual objects,underlining the glove's exact tracking of finger ***,the proposed data glove exhibited a low response time of 17-34 ms and back-drive force of only 0.19 ***,according to a comfort evaluation using the Comfort Rating Scales,the proposed glove system is wearable,placing it at the WL1 level.
In the context of global carbon neutrality, the application of lightweight magnesium alloys is becoming increasingly attractive. In this study, selective laser melting(SLM) was employed to achieve nearly full dense an...
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In the context of global carbon neutrality, the application of lightweight magnesium alloys is becoming increasingly attractive. In this study, selective laser melting(SLM) was employed to achieve nearly full dense and crack-free AZ91D components with fine equiaxed grain structure. The formation mechanism of typical pore defects(gas pore, lack-of-fusion pore and keyhole pore) and melting modes(keyhole mode and conduction mode) were systematically studied by varying the laser power and scanning speed. The morphology and volume fraction of the pores under different processing conditions were characterized. A criterion based on the depth-to-width ratio of the melt pool was established to identify different melting modes. The strength and ductility(tensile strength up to 340 MPa and uniform elongation of 8.9%)of the as deposited AZ91D are far superior to those of the casting components and are comparable to those of its wrought *** superior balance of strength and ductility of SLMed AZ91D, as well as the negligible anisotropic properties are mainly ascribed to the extremely fine equiaxed grain structure(with average grain size of ~1.2 μm), as well as the discontinuous distribution of β-Al_(12)Mg_(17) phases. It thus provides an alternative way to fabricate high-strength magnesium alloys with complex geometry.
Facial Expression Recognition (FER) aims to cate-gorize emotional expressions depicted on a human face, and isa challenging task under unconstrained conditions, such as faceocclusions and pose variations. Recent metho...
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Three-Dimensional(3D)swirling flow structures,generated by a counter-rotating dualstage swirler in a confined chamber with a confinement ratio of 1.53,were experimentally investigated at Re=2.3×10^(5)using Tomogr...
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Three-Dimensional(3D)swirling flow structures,generated by a counter-rotating dualstage swirler in a confined chamber with a confinement ratio of 1.53,were experimentally investigated at Re=2.3×10^(5)using Tomographic Particle Image Velocimetry(Tomo-PIV)and planar Particle Image Velocimetry(PIV).Based on the analysis of the 3D time-averaged swirling flow structures and 3D Proper Orthogonal Decomposition(POD)of the Tomo-PIV data,typical coherent flow structures,including the Corner Recirculation Zone(CRZ),Central Recirculation Zone(CTRZ),and Lip Recirculation Zone(LRZ),were *** counter-rotating dual-stage swirler with a Venturi flare generates the independence process of vortex breakdown from the main stage and pilot stage,leading to the formation of an LRZ and a smaller CTRZ near the nozzle *** confinement squeezes the CRZ to the corner and causes a reverse rotation flow to limit the shape of the CTRZ.A large-scale flow structure caused by the main stage features an explosive breakup,flapping,and Precessing Vortex Core(PVC).The explosive breakup mode dominates the swirling flow structures owing to the expansion and construction of the main jet,whereas the flapping mode is related to the wake *** limits the expansion of PVC and causes it to contract after the impacting area.
CrCN, CrAlN, and CrAlCN series coatings were deposited on WC substrates using a high-power impulse magnetron sputtering (HiPIMS) system with various nitrogen, aluminum, and carbon flow rates. The effects of the alumin...
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This study delves into the combustion behavior of various lignite types within a circulating fluidized bed boiler(CFBB),with a primary focus on the impact of different bed material sphericity ratios(0.5,0.7,and 0.9).U...
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This study delves into the combustion behavior of various lignite types within a circulating fluidized bed boiler(CFBB),with a primary focus on the impact of different bed material sphericity ratios(0.5,0.7,and 0.9).Utilizing bed material with a sphericity ratio of 0.9 sourced from theÇan power plant and verified through experimentation,the research reveals several key ***,furnace temperatures tended to rise with higher sphericity ratios,albeit with variations between lignite types,particularly highlighting the complexity of this relationship in the case of GLI-Tunçbilek *** levels in the combustion chamber remained consistent across different sphericity ratios,indicating minimal influence on pressure *** combustion efficiency,especially at the bottom of the boiler,was observed at lower sphericity levels(0.5 and 0.7)forÇan lignite,as reflected in CO_(2) mole *** NO_(x) emissions generally decreased with lower sphericity,the sensitivity to sphericity varied by lignite type,with Ilgın lignite showcasing low NO_(x) but high SO_(2) emissions,underscoring the intricate interplay between lignite properties,sphericity,and ***,this study advances our understanding of CFBB combustion dynamics,offering insights valuable for optimizing performance and emissions control,particularly in lignite-based power.
Variational mode decomposition(VMD)is a suitable tool for processing cavitation-induced vibration signals and is greatly affected by two parameters:the decomposed number K and penalty factorαunder strong noise *** so...
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Variational mode decomposition(VMD)is a suitable tool for processing cavitation-induced vibration signals and is greatly affected by two parameters:the decomposed number K and penalty factorαunder strong noise *** solve this issue,this study proposed self-tuning VMD(SVMD)for cavitation diagnostics in fluid machinery,with a special focus on low signal-to-noise ratio conditions.A two-stage progressive refinement of the coarsely located target penalty factor for SVMD was conducted to narrow down the search space for accelerated decomposition.A hybrid optimized sparrow search algorithm(HOSSA)was developed for optimalαfine-tuning in a refined space based on fault-type-guided objective *** on the submodes obtained using exclusive penalty factors in each iteration,the cavitation-related characteristic frequencies(CCFs)were extracted for *** power spectrum correlation coefficient between the SVMD reconstruction and original signals was employed as a stop criterion to determine whether to stop further *** proposed SVMD overcomes the blindness of setting the mode number K in advance and the drawback of sharing penalty factors for all submodes in fixed-parameter and parameter-optimized *** with other existing methods in simulation signal decomposition and in-lab experimental data demonstrated the advantages of the proposed method in accurately extracting CCFs with lower computational *** especially enhances the denoising capability of the VMD-based method.
During the initial phases of operation following the construction or renovation of existing buildings,the availability of historical power usage data is limited,which leads to lower accuracy in load forecasting and hi...
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During the initial phases of operation following the construction or renovation of existing buildings,the availability of historical power usage data is limited,which leads to lower accuracy in load forecasting and hinders normal ***,by transferring load data from similar buildings,it is possible to enhance forecasting ***,indiscriminately expanding all source domain data to the target domain is highly likely to result in negative transfer *** study explores the feasibility of utilizing similar buildings(source domains)in transfer learning by implementing and comparing two distinct forms of multi-source transfer ***,this study focuses on the Higashita area in Kitakyushu City,Japan,as the research *** buildings that exhibit the highest similarity to the target buildings within this area were selected for ***,the two-stage TrAdaBoost.R^(2) algorithm is used for multi-source transfer learning,and its transfer effect is ***,the application effects of instance-based(IBMTL)and feature-based(FBMTL)multi-source transfer learning are compared,which explained the effect of the source domain data on the forecasting accuracy in different transfer *** results show that combining the two-stage TrAdaBoost.R^(2) algorithm with multi-source data can reduce the CV-RMSE by 7.23%compared to a single-source domain,and the accuracy improvement is *** the same time,multi-source transfer learning,which is based on instance,can better supplement the integrity of the target domain data and has a higher forecasting ***,IBMTL tends to retain effective data associations and FBMTL shows higher forecasting *** findings of this study,which include the verification of real-life algorithm application and source domain availability,can serve as a theoretical reference for implementing transfer learning in load forecasting.
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