Journal of Engineering and Thermal Sciences
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Muti-objective optimization of tuned liquid column damper design parameters for vibration control under wind load
Full text linkTuned Liquid Column Dampers (TLCDs) are widely used as passive devices for vibration control in structures dominated by wind loads, utilizing the oscillation of liquid in a U-shaped container to dissipate energy. The effectiveness of TLCDs is significantly influenced by key design parameters, like mass ratio, tuning frequency ratio, and head loss coefficient. This study developed governing equations of TLCDs and investigated the influence of external load excitation spectrum on the vibration mitigation performance. A multi-objective optimization approach based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was proposed to identify optimal design parameters of TLCDs under various loading conditions. The results revealed that the external excitation spectrum played a crucial role in determining the optimal parameters, and the damper performance was distinctly different when the excitation frequencies changed. This optimization method was validated through a 200-meter high tower, where the optimized TLCD significantly enhanced vibration control performance at a wide range of wind directions. These findings offered valuable insights for the application of TLCDs in complex environments with varying external load characteristics
Study of the aerodynamics of a full-scale tractor-trailer
Full text linkThe wind tunnel campaign evaluated 10 configurations of a tractor-trailer combination using a Volvo VNL860 tractor and the 30 ft NRC trailer. The test results include balance measurements of drag force, side force, and yawing moment. The baseline tractor-trailer combination had a blockage-corrected drag coefficient of 0.457 at 0° yaw and a wind-averaged drag coefficient of 0.527. The combined removal of the side extenders, their extensions, and the roof air deflector (in Configurations 6 and 7) resulted in the largest increase in drag (6 % relative to baseline) of all of the aerodynamic packages that were evaluated. The smallest change in drag coefficient resulted from the removal of the tractor skirt extensions (aerodynamic package 4), but it should be noted that the tractor skirt extensions were only evaluated at 0 yaw and would have more of an effect at higher yaw angles. The purpose of this paper is to study the drag coefficient of the entire Tractor through wind tunnel experiments. At present, there are few tests on the resistance coefficient of Tractors, and there are also few published papers on this topic. By removing Aerodynamic packages, this helps to understand the impact of different Aerodynamic packages on the overall drag coefficient of the vehicle
Small targets detection in low-resolution remote sensing images based on super-resolution joint optimization
Full text linkWhile convolutional neural networks have driven remarkable progress in remote sensing object detection, persistent challenges remain in detecting small targets within low-resolution imagery due to their limited pixel representation and feature degradation during hierarchical downsampling. To address this, this study proposed the joint super-resolution and detection network (JSRDN), which synergistically optimizes SR reconstruction through task-specific detection feedback, significantly enhancing small target recognition in LR remote sensing imagery. Firstly, generator in generative adversarial network incorporates improved residual blocks, enabling enhanced perception of complex deep-level features in the SR reconstruction process. Then, a perceptual loss function is introduced into the adversarial training process, which captures perceptual discrepancies in high-level features between reconstructed images and original HR references. After that, an edge-enhancement network is designed to dynamically detect edges in intermediate features restored by the generator, prioritizing edge influence across network layers to generate discriminative features for target recognition. Furthermore, the JSRDN implements detection-driven feedback by backpropagating object recognition loss through the generator, enforcing the super-resolution process to prioritize detection-salient feature recovery. Evaluated on 64×64 low-resolution COWC datasets, JSRDN achieves 0.1819 dB peak signal-to-noise ratio (PSNR) and 7.18 % average precision (AP) improvements over the deep residual dual-attention network (DRDAN), with ablation studies and visualizations confirming its balanced optimization of reconstruction fidelity and detection-oriented feature learning. This technology can provides valuable support for small target measurement and opens new opportunities in the field
Modernization of the electromagnetic vibration stand for testing aviation industry products
Full text linkThe article presents a methodology for modernizing a two-mass resonant electromagnetic vibration stand for testing parts of the aviation industry for vibration resistance. The main goal of the modernization is to provide a significantly lower disturbance force from electromagnetic vibration exciters to set the working body in motion. For this purpose, by introducing a third oscillating mass into the two-mass mechanical system, the interresonant mode of operation of the vibration stand is ensured. Analytical dependencies are presented that reveal the methodology for calculating inertial and stiffness parameters that ensure the transformation of a two-mass resonant vibration system into a three-mass interresonant vibration system. A specific example demonstrates the implementation of the proposed approach in the modernization of the design. The amplitude-frequency characteristics of the basic two-mass resonant and modernized three-mass interresonant vibration systems are constructed. It has been confirmed that to ensure the specified amplitude of oscillations of the working body in the modernized design, 4 times less disturbing force from electromagnetic vibration exciters (400 N) is required
Multi-scale information distillation attention network for super-resolution reconstruction of remote sensing images
Full text linkSuper-resolution (SR) is an effective and reasonable way to improve the spatial resolution of remote sensing images, which serve as an important information carriers for Earth observations. Compared to natural images, the more complex spatial distributions and more detailed ground information contained within remote sensing data place higher demands on the feature-representation ability of the model. Moreover, considering the deployment of these systems on mobile hardware, the complexity of the model is also an urgent issue. To overcome these problems, this study proposes the multi-size information distillation attention network (MSIDAN) for super-resolution reconstruction of remote sensing images. In the designed residual block, a multi-size information-distillation module is designed to distill and fuse multi-level semantic features step-by-step while reducing the number of model parameters. After this, an enhanced contrast-aware channel attention mechanism is employed to perceive high-frequency information by automatically encoding the weight values of candidate features. A large number of comparative experiments on four typical remote sensing image datasets demonstrate that MSIDAN outperforms other state-of-the-art approaches in both quantitative metrics and visual qualities. Compared to the information multi-distillation network (IMDN), MSIDAN improves the Peak Signal-to-Noise Ratio (PSNR) by 0.03312 dB, 0.06031 dB, 0.05319 dB, and 0.03812 dB on the RSSCN7, WHU-RS19, NWPU VHR-10, and COWC datasets, respectively. Moreover, in comparison to other comparable CNNs-based approaches, MSIDAN achieves a more favorable balance by jointly considering SR performance and model size. This technology provides valuable support for small target measurement and opens new opportunities in the field
Structural instability motion and optimization of the demolition and blasting scheme for complex continuous multi-span frame-shear structure
Full text linkDue to challenges faced during demolition and blasting processes such as conducting prototype monitoring tests on large continuous multi-span structures or carrying out full-area dynamic monitoring of overall structural stress; This paper takes the demolition of the Ruzhou Unicom building as the background, optimizes the design of the demolition and blasting program through theoretical analysis and simulation monitoring, and also studies the form of structural instability movement and the deformation of the key parts of the damage and internal force characteristics, and obtains the following conclusions: the axial force reaches the maximum value when the building is not deflected; when the first-order derivative of the shear force is 0, the maximum shear stress occurs at the position of 2/3 of the height of the building; When the first-order derivative of bending moment is 0, the maximum bending moment occurs at 1/3 of the building height. In Mushroom Pavilion incision formation, the support part of the main structure produces a downward force, exacerbating the disintegration of the main part of the damage; the main structure of the collapse process, the back row of columns are mainly presented as bending shear damage, the upper side beams are mainly presented as tensile damage, the central and lower side beams are mainly presented as compression shear damage. Notably, the bidirectional notch configuration results in a forward displacement of 9.5 meters and a subsequent recoil of 4.6 meters, providing effective shielding for the military fiber-optic cables positioned at the forefront and the adjacent deep excavation pits. Additionally, this configuration facilitates the rapid establishment of a stable collapse pattern between the Mushroom Pavilion structure and its main body, ultimately accelerating the disintegration of the overall building structure during the collapse event
Research on bearing equipment fault diagnoses via SAWOA-LSTM
Full text linkTo address the current low fault diagnosis accuracy problem for bearing equipment, and improve the detection methods, in this paper a sine-adapted whale optimization algorithm (SAWOA)-based optimization of a long short-term memory (LSTM) network is proposed as the equipment fault diagnosis method (SAWOA-LSTM). First, an optimization strategy based on sinusoidal population initialization and adaptive optimization is proposed for the whale optimization algorithm, which has the two drawbacks of slow convergence and easily falling into a local optimum. Second, to improve the accuracy and efficiency of fault diagnoses, the SAWOA is used to optimize the number of hidden units and the learning rate parameter of the LSTM. Compared with ACO-, PSO-, and WOA-based LSTM models, the proposed method improves diagnostic accuracy by 14.17 %, 15.03 %, and 4.32 %, respectively. In tests on 50 bearing samples, SAWOA-LSTM further improves accuracy for RBD, IRA, and ORD by 1.08 %, 1.62 %, and 1.10 %, respectively. Our algorithm provides an innovative solution for the health management of complex industrial bearing equipment
Fault diagnosis of time-varying speed gearbox based on gated recurrent dropout attention unit
Full text linkIn response to the difficulty of fault diagnosis of gearbox under time-varying speed conditions, this paper presents a novel approach for diagnosing gearbox faults in time-varying speed, utilizing an improved gate recurrent unit (GRU), which adds attention gate mechanism and cyclic dropout learning strategies on the basis of the GRU, and constructs a new model named as gated recurrent dropout attention unit (GRDAU). By introducing attention gate mechanism to realize allocating weights dynamically, focusing on key features, and enhancing GRU’s ability to capture important information. In addition, the designed cyclic dropout learning strategy reduces excessive dependence on specific hidden states by randomly discarding some hidden state information. Finally, the robustness and excellent interference suppression ability of the proposed method were verified through case analysis of a gearbox under time-varying speed, and the diagnostic accuracy of the method is as high as 99.78 %. Comparative experiments were conducted to validate its superior performance and stronger generalization ability compared to existing advanced diagnostic methods
Dual-stator ultrasonic motor achieving 2-DOF linear and rotary motion with single-phase excitation
Full text linkThis study proposes a novel dual-stator linear-rotary ultrasonic motor. The piezoelectric ceramic excites both out-of-plane and in-plane vibration modes within the stator. These distinct vibration modes independently drive the slider (rotor), generating reciprocating linear and rotational motions, respectively. Finite element analysis and laser vibrometer-based vibration testing validated the motor's operational principle. The close agreement between simulated and measured resonant frequencies for both vibration modes, with mere discrepancies of 3 % and 4 %, respectively, underscores the accuracy of the stator’s vibrational characteristics. Subsequently, two stators are fabricated and assembled to the ultrasonic motor prototype. Experimental results demonstrate the motor’s impressive performance, achieving a maximum linear velocity of 265 mm/s and a peak rotational speed of 1600 rpm. Furthermore, the motor delivers a maximum thrust force of 0.18 N and a stalling torque of 1.8 mN·m
Investigation of transient processes in auxiliary asynchronous electric motors of locomotives using differential equations
Full text linkThe aim of this research is to scientifically substantiate the operating conditions of small and medium-power auxiliary asynchronous electric motors currently in use on mainline electric locomotives of the VL60, VL80, and Ermak 3ES5K types. The goal is to draw conclusions based on scientific research, such as evaluating the operational efficiency of auxiliary asynchronous electric motors and creating the possibility to predict their service life based on the assessment results. This, in turn, will enable timely maintenance of auxiliary engines in locomotives