Jaw Functional Orthopedics and Cranoficial Growth
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Feature data analysis of dance movements by motion capture
Get PDFMotion capture technology has been applied in more and more fields, but the research in the field of dance is relatively rare. In order to combine motion capture technology with dance research, better understand the characteristics of dance movements, and provide support for their digital analysis, this paper mainly studied the application of a motion capture technology called Kinect in the analysis of dance movement feature data. The skeleton data of different dance movements was first collected based on Kinect v2, and then the collected data was analyzed using a spatio-temporal graph convolutional network (ST-GCN). On the basis of the original ST-GCN, the multi-branch structure was adopted to realize co-occurrence feature learning, and the bone length feature and direction feature were introduced to further enrich the feature data. Experiments were carried out on the NTU RGB+D and dance datasets. It was found that the improved ST-GCN had better performance than other current motion classification approaches on the NTU RGB+D. The top-1 accuracy for cross-subject (CS) and cross-view (CV) was 92.4 % and 96.7 %, respectively, and the average accuracy of different dance movements for the dance dataset was 96.035. The findings confirm the effectiveness of the proposed approach in the analysis of dance movement feature data, and it can be applied in the actual research of dance movements
Analysis and synthesis of a controllable crank-slider mechanism with parallel springs for frame saws
Get PDFFrame saws suffer from large unbalanced inertia forces, limiting operating speed and requiring heavy construction. This study aims to overcome these limitations by synthesizing a dynamically balanced main drive mechanism using a novel approach based on prescribed motion laws. The methodology involves proposing a crank-slider mechanism featuring a cam-actuated variable-length crank. The mechanism configuration with parallel spring is analyzed allowing for balancing inertia forces, achieved using a prescribed cosine slider motion law. For the considered configuration, the required variable crank length function (cam profile) and associated mechanism parameters (connecting rod length, spring stiffness) are analytically synthesized. The results of the carried-out numerical modeling demonstrate successful synthesis of a near-circular cam profile and very low pressure angles for the case studied. These findings show that synthesizing the saw drive kinematics based on force balancing requirements can theoretically eliminate inertial loads, offering the potential for higher speeds of saw frames and reduced loads. The synthesized near-circular cam profile suggests a pathway towards simpler manufacturing. The implications of successfully implementing such dynamically balanced frame saw mechanisms are potentially transformative for the sawmilling industry. Eliminating the primary inertial forces removes the major obstacle to increasing operating speeds. This could allow frame saws to operate closer to the optimal cutting speeds for wood (e.g., 40-50 m/s), leading to significant gains in productivity
Study on monitoring the loose bolts of transmission tower by vibration signal
No full textThe loose failure of transmission tower bolts may lead to structural instability and safety risks, so effective monitoring methods are crucial to the stable operation of transmission lines. The purpose of this study is to explore the effectiveness of vibration signal technology in monitoring the loose bolts of transmission tower. Based on vibration theory, the principle of bolt loosening of transmission tower is analyzed, vibration signal data is collected by means of vibration exciter and optical fiber vibration sensor, and then the monitoring test of transmission tower loosening fault is carried out. The obtained test results show that the time domain waveform is significantly different before and after excitation, and the wavelength after excitation has a significant mutation, increasing from 1550 nm to 1553 nm, and slowly decreasing to the original wavelength, which also means that the transmission tower bolt loosening fault monitoring system has a good monitoring ability and can be used for vibration measurement. According to these monitoring results, the conclusions can be obtained as follows: first, the frequency domain data amplitude changes before and after loosening can be used to judge whether the bolt is loose, so as to achieve the monitoring purpose; Second, the strength of the vibration signal is large, the vibration signal change caused by the loosening of the bolt is submerged, and the installation of excitation at the sensor should be avoided to ensure that the monitoring is not disturbed by external factors. The research provides a new technical way for real-time monitoring of loose bolt fault of transmission tower, which has practical value and popularization prospect
Research progress on 3D printed geopolymer materials
No full textThe integration of 3D printing technology with geopolymer materials offers a sustainable alternative to conventional construction methods, significantly reducing CO2 emissions. However, challenges such as rapid setting, limited workability, and weak interlayer bonding limit their broader application. This review summarizes recent progress in 3D printed geopolymer composites, focusing on materials selection, rheological optimization, buildability, and mechanical performance enhancement. Strategies including the use of rheology modifiers, fiber reinforcements, nano-additives, and process optimization have shown promise in improving printability and structural performance. Remaining challenges, such as balancing setting time and printability and enhancing interlayer adhesion, are also discussed. Future research directions are proposed to further advance the development of high-performance, low-carbon geopolymer 3D printing materials for sustainable construction
Denoising for ECG signals based on VMD and RLS
No full textElectrocardiogram (ECG) signals often encounter various types of noise interference, which annihilates their waveform characteristics and exhibits strong instability. To facilitate clinical diagnosis and analysis, it is necessary to perform denoising processing in advance. A denoising method for ECG signals based on variational mode decomposition (VMD) and recursive least square (RLS) has been proposed. VMD was used for the modal decomposition of noisy ECG signals, and the recursive least square (RLS) algorithm was used for adaptive filtering of various intrinsic mode functions (IMFs) components. The problem construction, solution, and decomposition characteristics of VMD were analyzed. The IMFs filtered by RLS were reconstructed. This achieved the elimination of interference noise in the ECG signal. The Sym8 wavelet basis, LMS, NLMS, RLS, and VMD-RLS denoising method were compared by using ECG signals including Gaussian white noise, baseband drift, electrode motion, electromyographic interference, and electrical interference noise. The experimental results showed that the VMD-RLS denoising method has significantly better denoising performance than the other four methods, achieving better values in the quantitative evaluation indicators. This algorithm improved convergence speed and signal estimation accuracy, and it has good effectiveness, superiority, and practicality. Therefore, the VMD-RLS denoising method can enable doctors and researchers to analyze and diagnose ECG signals of heart diseases more accurately
Towards explainable artificial intelligence with potential games
No full textExplainable Artificial Intelligence (XAI) emerged when researchers attempted to identify methods that would interpret the models that are used to perform classification and predictions, in order to avoid having a black box just informing about the result. Methods of XAI are crucial to determine details of the model feature contribution towards the result. One of these methods is attributed to cooperative game theory and especially Shapley values. With this method the features are considered as players and the marginal contribution of the features are employed. In this paper, we take onboard the Potential Game paradigm to show the interconnection between them and the Shapley values. We show that the Shapley values are interlinked with the potential function. Moreover, we setup a game with the marginal contribution of the players as their utility functions and we prove that the game is a potential game. Finally, we show that the price of stability of this game is 1. We utilise the Simulated Annealing (SA) method to find the optimal solution
A cost model analysis in the process of refining petroleum using supplementary variable technique
No full textThis paper presents a cost model analysis for refining petroleum using an MX/G(a , b)/1.MX/G(a , b)/1 queuing system with two stages of heterogeneous services under steady-state conditions. The study derives the total average cost per unit time for two distinct service phases: Phase I and Phase II. In the first case, the analysis focuses on the total average cost of the system when the server operates in Phase I with a probability of π1 at any given time, and in Phase II with a probability of π2. Additionally, the model incorporates holding costs, operating costs, renovation costs for both phases, and closure time costs. Finally, numerical tables and graphical representations are provided to illustrate the observations regarding the total average cost, renovation rate, and arrival rate
Scientific and practical substantiation of transient processes in asynchronous electric motors of mainline electric locomotives
No full textThe research work focuses on scientifically substantiating the operating conditions of small and medium-power auxiliary asynchronous electric motors used in mainline electric locomotives under JSC “Uzbekistan Railways”. The aim is to provide a scientific basis for the operational efficiency of auxiliary asynchronous electric motors and, based on the research findings, to conduct a practical investigation of their service life. This, in turn, will enable timely maintenance of auxiliary asynchronous electric motors in locomotives. Additionally, it will contribute to improving the performance indicators of auxiliary asynchronous electric motors
Improved CEEMD-based correction method for low-frequency shock response spectrum in large dual-wave shock tester devices
Get PDFThe shock response spectrum (SRS), calculated from a shock acceleration signal, is a critical indicator of shock environments. However, under intense loads, acceleration sensors are prone to trend term errors that can cause significant drift in the low-frequency spectral lines of large dual-wave shock tester devices. To address this issue, the complementary ensemble empirical mode decomposition (CEEMD) method was employed to decompose acceleration signals and restore the actual shock environment. Intrinsic mode functions (IMFs) were cross-correlated and compared to a predefined threshold to identify the effective IMF components required to reconstruct the signal. K-means clustering was employed to further validate the effectiveness of the IMFs for enhanced selection accuracy. Finally, the reconstructed acceleration signal was used to calculate a corrected SRS. The proposed approach demonstrated significant improvements over the traditional CEEMD algorithm. The corrected SRS exhibits a 5.6316 dB/oct slope in the low-frequency band, reflecting an equal displacement trend. The maximum error at the corresponding frequency was less than 6 % in comparison to the relative displacement response measured by low-frequency spring oscillators. This improved CEEMD correction method can effectively restore the actual shock environment of a dual-wave shock tester device, offering a valuable reference for evaluating shock resistance in onboard equipment
Vibration and noise performance analysis and optimal design of V-rotor in permanent magnet synchronous motor: a new strategy for high efficiency and low noise
Get PDFInterior Permanent magnet synchronous motors (IPMSMs) have become the preferred powertrain solution for electric vehicles due to their exceptional performance characteristics. However, the high-frequency electromagnetic noise generated during motor operation poses a significant challenge to occupant comfort within the vehicle. This study provides a comprehensive analysis of the electromagnetic forces, modal characteristics, and vibration noise for a 12-pole, 36-slot IPMSM, incorporating theoretical and simulation-based approaches as well as modal tests. By innovatively combining orthogonal experimental design with nonparametric regression techniques, a response surface model is developed to accurately characterize and optimize the radial electromagnetic force harmonics of the motor. The optimization results reveal a significant 37.7 % reduction in the motor’s surface vibration velocity and an 8.5 % decrease in peak noise levels, successfully meeting the engineering objectives for vibration and noise attenuation. This study not only contributes to the advancement of noise control technologies in electric vehicle power systems but also provides novel insights and methodologies for motor design, offering significant practical value and engineering relevance