Journal of Engineering and Thermal Sciences
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Assessment of the influence of external dynamic factors on force loading of anchor bandage of traction electric motors
Full text linkA methodology has been proposed for calculating the force loading of anchor bandages of locomotive traction electric motors from the action of external dynamic factors, which makes it possible to determine dynamic stresses in each section of the anchor bandage along its entire length, depending on the operating modes of the traction electric motor, taking into account its design features and real operating conditions. It has been established that the most significant influence on the fluctuations of the armature shaft of traction electric motors of diesel locomotives is exerted by dynamic influences from the collision of wheels with joints and unevenness of the rail track, as well as from errors in the manufacture of the serrated broadcast (gears). The supposed economic effect from the creation of new glass bandage designs for the anchors of traction electric motors of diesel locomotives of the 2TE10M series is estimated at approximately 10.92 million soums for one such diesel locomotive. It is recommended to continue these studies in order to develop and justify rational geometric parameters of a new design of the anchor glass bandages of a traction electric motor with increased fatigue strength
Self-supervised CNN for user behavior analysis on smart meter data
Full text linkSmart meters generate extensive data on individual consumer electricity usage, providing valuable insights that can aid in identifying demographic information and advancing the development of smart grids. Current research has primarily focused on traditional machine learning approaches for this task, with relatively few studies exploring deep learning methods, despite their potential for more accurate and efficient analysis. To address this gap, this paper proposes a self-supervised deep learning approach based on Convolutional Neural Network (CNN) to identify demographic information from smart meter data. The model leverages the Fast Fourier Transform (FFT) to detect frequency cycles within the dataset, which are then used to optimize the sizes of convolutional kernels. This design enhances periodic stability during shallow feature extraction, improving the model’s ability to capture meaningful patterns in the data. Furthermore, the model incorporates a self-supervised pre-training strategy to predict temporal and spatial interactions in load signals, effectively enhancing representation learning without relying on extensive labeled data. This approach ensures the model’s robustness and adaptability to different datasets. Comprehensive experiments were conducted on a publicly available Irish dataset to evaluate the model’s performance. Results demonstrate that the proposed model surpasses a series of state-of-the-art (SOTA) methods, achieving superior performance in demographic information identification. These findings highlight the effectiveness of integrating FFT-based kernel design and self-supervised learning in improving feature extraction and representation learning for smart meter data
Design and verification of a new type of hydraulic vibration isolator for high-speed train floors
Full text linkWith the development of high-speed trains, the requirements for noise, vibration, and comfort are becoming increasingly stringent. The train body floor, as one of the main pathways for vibration transmission, is crucial to be treated for vibration reduction and noise attenuation. This paper, in response to this demand, has developed a new type of floor vibration isolator specifically for high-speed trains. Through finite element simulation analysis and experimental verification, it has been proven that this vibration isolator can effectively reduce the vibration of the train body floor and significantly enhance the NVH (Noise, Vibration, and Harshness) performance of the train
Influence of the supporting surface inclination angle on the locomotion conditions of a vibration-driven system
Full text linkThis paper investigates the influence of supporting surface inclination angle on the locomotion of a capsule-type robot driven by an imbalanced rotor, considering dry anisotropic friction. Using Lagrange’s second-order differential equations, a mathematical model is developed, and numerical simulations are performed with Wolfram Mathematica software. The scientific novelty lies in the comprehensive analysis of how inclination angle, coupled with anisotropic friction, affects the capsule’s motion, including the derivation of analytical conditions for maintaining a “non-detachable” motion regime and preventing backward slippage. Key results include the establishment of relationships for the maximum permissible angular velocity of the imbalanced rotor as a function of surface inclination angle and friction coefficient. It is found that this velocity is maximal on horizontal surfaces and decreases with increasing inclination, while higher backward friction coefficients allow for greater rotor speeds. The practical value of these findings is significant for the design and control of vibration-driven robots, particularly for applications such as pipeline inspection, monitoring, and cleaning, where reliable navigation across varied inclinations is crucial
Finite element analysis of vibration transmission in building-integrated metro systems
Full text linkThis study develops a comprehensive model that integrates the vibration source, building structure, and surrounding soil layers. The methodology involves a vertical vehicle-track coupling dynamic model and a multi-scale coupled finite element model encompassing moving loads, track structure, building body, and surrounding strata. The results show that vibrations induced by trains operating on the first level remain within acceptable limits. However, when trains operate simultaneously on both the first and second levels, vibration levels in the overlying structure exceed specified standards. Further targeted design optimizations are recommended
The effect of the quantity and length of fibers on the mechanical properties of fiber-reinforced concrete based on polypropylene fibers
Full text linkIn these studies, the effect of polypropylene fibers on the mechanical properties of concrete was studied, and special attention was paid to determining their optimal amount and acceptable length. The fibers were added to the concrete composition in amounts of 0.1-0.5 % and lengths of 10, 20, 30, 40, 50 mm and tested. According to the results of the study, the highest results were recorded at a fiber content of 0.2-0.3 % and lengths of 20-30 mm, and the compressive strength of concrete increased by up to 15.9 % compared to ordinary concrete. When adding fibers in excess (≥ 0.4 %) or with a length of 50 mm, a decrease in strength was observed. The results obtained showed that it is possible to increase the quality and improve the strength of concrete by selecting the optimal parameters of polypropylene fibers
Research of the stress-strain state and durability of freight wagon trolley springs by the method of finite element modeling in ANSYS
Full text linkThis paper presents a study of the stress-strain state and the prediction of the cyclic durability of a set of trolley springs for freight wagons using the finite element modeling (FEM) method in the ANSYS software package. The aim of the study is to evaluate the influence of materials (steel 55Si2 and 60Si2CrVA) on the performance characteristics of springs under static and dynamic loads corresponding to loaded and empty conditions of the wagon. To achieve this goal, parametric 3D models of springs have been created, finite element models have been developed, and strength and fatigue calculations have been performed. The distributions of equivalent stresses and deformations are analyzed, fatigue durability is predicted, and safety margin coefficients are determined. The results obtained make it possible to evaluate the reliability and durability of springs made of various materials in real-world operating conditions, as well as identify critical stress concentration zones
Research on friction characteristics of drill string in whole well section of gas drilling based on finite element method
Full text linkDuring gas drilling, the drill string friction is directly related to the safety of drilling and tripping. When the drill string reaches the horizontal section, the friction problem is prominent, which greatly increases the risk and difficulty of trajectory control in the horizontal section. The purpose of this paper is to study the frictional characteristics between drill string and wellbore wall. Firstly, the dynamic mathematical model of drill string in gas drilling is established, a new boundary conditions between wellhead and bottom hole is proposed. Secondly, the governing equation of drill string system is established by using Lagrange equation. Thirdly, the improved Generalized-α method is used to solve the dynamic equation of drill string system. Finally, the effects of weight on bit (WOB) and rotational speed on friction torque of drill string system are analyzed, as well as the effects of different borehole curvature and friction coefficient on friction characteristics of drill string. The findings indicate that as the WOB and rotational speed increase, the lateral motion range and friction torque of the drill string gradually rise; With an increase of borehole curvature and friction coefficient, the friction resistance of the drill string increases obviously. Additionally, it is observed that the average friction resistance of the drill string is greater in horizontal sections compared to vertical and deflecting sections. The average lifting friction on the drill string is less than the lowering friction. Theoretical research plays a crucial role in guiding the optimization of drilling parameters and the implementation of friction reduction
NGO-MRE combined with DELM for bearing fault diagnosis
Full text linkTo improve the effectiveness of Multiscale Range Entropy (MRE) in extracting features from rolling bearing faults, this paper proposes a novel bearing fault diagnosis method that combines the Northern Goshawk Optimization (NGO) algorithm, MRE, and a Deep Extreme Learning Machine (DELM). First, the raw vibration signal is decomposed using Variational Mode Decomposition (VMD) to obtain its Intrinsic Mode Functions (IMFs). Second, the NGO algorithm is employed to optimize the MRE parameters, using the minimum crest factor as the objective function. Then, using these optimized parameters, MRE is applied to extract fault features. The resulting feature set undergoes dimensionality reduction to create the final sample set. Finally, an NGO-optimized DELM is used for fault classification. The experimental results demonstrate that this method effectively extracts the characteristic signals of rolling bearing faults through robust parameter optimization, thereby improving the accuracy of fault diagnosis
Stress analysis and seismic performance testing of surrounding rock in coal mine roadway
Full text linkThis study focuses on the stability control of surrounding rock in coal mine roadway. The finite difference method combined with FLAC3D software was adopted to establish numerical simulation model of the roadway roof, so as to analyze the influence of roof cutting height and roof cutting angle on the surrounding rock stress field. Through field tests, the bidirectional blasting excavation technology with energy-gathering pipes was used, combined with resistance-controllable support equipment. Differentiated monitoring point scheme was designed to monitor the changes in anchor cable tension and roof subsidence. The research results show that when the roof cutting height increases from 3 m to 6 m, the maximum stress of the roadway decreases by approximately 17 %, and the high-stress area shifts to the deep stable rock formation. When the roof cutting angle is adjusted from 0° to 10°, the maximum stress decreases by about 19.4 %, and the area of the high-stress zone is reduced to 11 % of the total cross-sectional area. When the distance behind the working face exceeds 100 m, the roof reaches a stable state under the action of support