Search Results (139)

The model explicitly incorporates boundary conditions that account for the complex interplay between sections experiencing varying degrees of reduction. This interaction significantly influences the overall deformation behavior and force loading. The control effect is associated with boundary conditions determined by the unevenness of the compression, which have certain quantitative and qualitative characteristics. These include additional loading, which is less than the main load, which implements the process of plastic deformation, and the ratio of control loads from the entrance and exit of the deformation site. According to this criterion, it follows from experimental data that the controlling effect on the plastic deformation site occurs with a ratio of additional and main loading in the range of 0.2–0.8. The next criterion is the coefficient of support, which determines the area of asymmetry of the force load and is in the range of 2.00–4.155. Furthermore, the criterion of the regulating force ratio at the boundaries of the deformation center forming a longitudinal plastic shear is within the limits of 2.2–2.5 forces and 1.3–1.4 moments of these forces. In this state, stresses and deformations of the plastic medium are able to realize the effects of plastic shaping. The force effect reduces with an increase in the unevenness of the deformation. This is due to a change in height of the longitudinal interaction of the disparate sections of the strip. There is an appearance of a new quality of loading—longitudinal plastic shear along the deformation site. The unbalanced additional force action at the entrance of the deformation source is balanced by the force source of deformation, determined by the appearance of a functional shift in the model of the stress state of the metal. The developed theory, using the generalized method of an argument of functions of a complex variable, allows us to characterize the functional shift in the deformation site using invariant Cauchy–Riemann relations and Laplace differential equations. Furthermore, the model allows for the investigation of material properties such as the yield strength and strain hardening, influencing the size and characteristics of the identified limit state zone. Future research will focus on extending the model to incorporate more complex material behaviors, including viscoelastic effects, and to account for dynamic loading conditions, more accurately reflecting real-world milling processes. The detailed understanding gained from this model offers significant potential for optimizing mill roll designs and processes for enhanced efficiency and reduced energy consumption. Full article

The threshing drum, a core component in combine harvesters, experiences significant unbalanced vibrations during high-speed rotation, leading to severe mechanical wear, increased energy consumption, elevated noise levels, potential safety hazards, and higher maintenance costs. A primary challenge is that excessive interference signals often obscure the fundamental frequency characteristics of the vibration, hampering balancing effectiveness. This study introduces a signal conditioning model to suppress such interference and accurately extract the unbalanced quantities from the raw signal. Leveraging this extracted vibration force signal, an automatic optimization method for the balancing counterweights was developed, solving calculation issues inherent in traditional approaches. This formed the basis for an automatic balancing control strategy and an integrated system designed for online monitoring and real-time control. The system continuously adjusts the rotation angles, θ₁ and θ₂, of the balancing weight disks based on live signal characteristics, effectively reducing the drum’s imbalance under both internal and external excitation states. This enables a closed loop of online vibration testing, signal processing, and real-time balance control. Experimental trials demonstrated a significant 63.9% reduction in vibration amplitude, from 55.41 m/s² to 20.00 m/s². This research provides a vital theoretical reference for addressing structural instability in agricultural equipment. Full article

Against the backdrop of ecological civilization construction and regional coordinated development strategies, functional zone (MFOZ) planning guides national spatial development through differentiated policies. However, a prominent conflict exists between the ecological protection responsibilities and regional development rights in restricted and prohibited development zones, leading to a vicious cycle of “ecological protection → restricted development → poverty exacerbation”. This paper focuses on the synergistic mechanisms between ecological compensation and targeted poverty alleviation. Based on the capability approach and sustainable development goals (SDGs), it analyzes the dialectical relationship between the two in terms of goal coupling, institutional design, and practical pathways. The study finds that ecological compensation can break the “ecological poverty trap” through the internalization of externalities and the enhancement of livelihood capabilities. Nevertheless, challenges remain, including low compensation standards, unbalanced benefit distribution, and insufficient legalization. Through case studies of the compensation reform in the water source area of Southern Shaanxi, China, and the Common Agricultural Policy (CAP) of the European Union, this paper proposes the construction of a long-term mechanism integrating differentiated compensation standards, market-based fund integration, legal guarantees, and capability enhancement. The research emphasizes the need for institutional innovation to balance ecological protection and livelihood improvement, promoting a transition from “blood transfusion” compensation to “hematopoietic” development, thereby offering a Chinese solution for global sustainable development. Full article

An enhanced snow geese algorithm (ESGA) is proposed to address the problems of the weakened population diversity and unbalanced search tendencies encountered by the snow geese algorithm (SGA) in the search process. First, an adaptive switching strategy is used to dynamically select the search strategy to balance the exploitation and exploration capabilities. Second, a dominant group guidance strategy is introduced to improve the population quality. Finally, a dominant stochastic difference search strategy is designed to enrich the population diversity and help it escape from the local optimum by co-directing effects in multiple directions. Ablation experiments were performed on the CEC2017 test set to illustrate the improvement mechanism and the degree of compatibility of their improved strategies. The proposed ESGA with a highly cited algorithm and the powerful improved algorithm are compared on the CEC2022 test suite, and the experimental results confirm that the ESGA outperforms the compared algorithms. Finally, the ability of the ESGA to solve complex problems is further highlighted by solving the robot path planning problem. Full article

This paper presents Enhanced Voltage Sensorless Control for PWM converter with DSOGI-FLL under grid disturbances. Even without grid voltage sensors, the proposed method accurately estimates the grid angle and voltage, which are necessary for power transfer between the DC link of the PWM converter and the grid. The estimated grid voltage obtained through observer design is separated into positive and negative sequence components, and the grid frequency is estimated using the Dual Second-Order Generalized Integrator Quadrature Signal Generator (DSOGI-QSG) and Dual Second-Order Generalized Integrator Frequency-Locked Loop (DSOGI-FLL). The estimated positive and negative sequence voltages were effectively controlled using a dual current controller. The method operates effectively under normal, balanced AC source conditions and in various grid fault scenarios, including unbalanced voltage, harmonic distortion, voltage sag, and frequency step changes. The validity of the proposed method was evaluated through experimental results by using a grid simulator to implement the fault condition. Full article

This study introduces a custom-designed CNN architecture that extracts robust, multi-level facial features and incorporates preprocessing techniques to correct or reduce asymmetry before classification. The innovative characteristics of this research lie in its integrated approach to overcoming facial asymmetry challenges and enhancing CNN-based emotion recognition. This is completed by well-known data augmentation strategies—using methods such as vertical flipping and shuffling—that generate symmetric variations in facial images, effectively balancing the dataset and improving recognition accuracy. Additionally, a Loss Weight parameter is used to fine-tune training, thereby optimizing performance across diverse and unbalanced emotion classes. Collectively, all these contribute to an efficient, real-time facial emotion recognition system that outperforms traditional CNN models and offers practical benefits for various applications while also addressing the inherent challenges of facial asymmetry in emotion detection. Our experimental results demonstrate superior performance compared to other CNN methods, marking a step forward in applications ranging from human–computer interaction to immersive technologies while also acknowledging privacy and ethical considerations. Full article

Using the method of moments, we analyze three array antennas for low cross-polarized radiation. Each antenna comprises two dual-loop elements connected to a feedline horizontal to the ground plane. First, a feedline end is excited with an unbalanced source as a reference antenna. Next, the feedline center is excited with a balanced source, after the transformation of a decoupling array configuration. It is found that the antenna exhibits a cross-polarized radiation lower by 12 dB than the reference antenna. Last, the decoupling antenna is modified to have an unbalanced source without a complicated balun circuit design. It is pointed out that the modified antenna is an array of four loop elements, sequentially rotated by 90º. Full article

Change detection (CD) is an important research direction in the field of remote sensing, which aims to analyze the changes in the same area over different periods and is widely used in urban planning and environmental protection. While supervised learning methods in change detection have demonstrated substantial efficacy, they are often hindered by the rising costs associated with data annotation. Semi-supervised methods have attracted increasing interest, offering promising results with limited data labeling. These approaches typically employ strategies such as consistency regularization, pseudo-labeling, and generative adversarial networks. However, they usually face the problems of insufficient data augmentation and unbalanced quality and quantity of pseudo-labeling. To address the above problems, we propose a semi-supervised change detection method with data augmentation and adaptive threshold updating (DA-AT) for high-resolution remote sensing images. Firstly, a channel-level data augmentation (CLDA) technique is designed to enhance the strong augmentation effect and improve consistency regularization so as to address the problem of insufficient feature representation. Secondly, an adaptive threshold (AT) is proposed to dynamically adjust the threshold during the training process to balance the quality and quantity of pseudo-labeling so as to optimize the self-training process. Finally, an adaptive class weight (ACW) mechanism is proposed to alleviate the impact of the imbalance between the changed classes and the unchanged classes, which effectively enhances the learning ability of the model for the changed classes. We verify the effectiveness and robustness of the proposed method on two high-resolution remote sensing image datasets, WHU-CD and LEVIR-CD. We compare our method to five state-of-the-art change detection methods and show that it achieves better or comparable results. Full article

The Dung Beetle Optimization Algorithm (DBO) is characterized by its great convergence accuracy and quick convergence speed. However, like other swarm intelligent optimization algorithms, it also has the disadvantages of having an unbalanced ability to explore the world and to use local resources, as well as being prone to settling into local optimal search in the latter stages of optimization. In order to address these issues, this research suggests a multi-strategy fusion dung beetle optimization method (MSFDBO). To enhance the quality of the first solution, the refractive reverse learning technique expands the algorithm search space in the first stage. The algorithm’s accuracy is increased by adding an adaptive curve to control the dung beetle population size and prevent it from reaching a local optimum. In order to improve and balance local exploitation and global exploration, respectively, a triangle wandering strategy and a fusion subtractive averaging optimizer were later added to Rolling Dung Beetle and Breeding Dung Beetle. Individual beetles will congregate at the current optimal position, which is near the optimal value, during the last optimization stage of the MSFDBO; however, the current optimal value could not be the global optimal value. Thus, to variationally perturb the global optimal solution (so that it leaps out of the local optimal solution in the final optimization stage of the MSFDBO) and to enhance algorithmic performance (generally and specifically, in the effect of optimizing the search), an adaptive Gaussian–Cauchy hybrid variational perturbation factor is introduced. Using the CEC2017 benchmark function, the MSFDBO’s performance is verified by comparing it to seven different intelligence optimization algorithms. The MSFDBO ranks first in terms of average performance. The MSFDBO can lower the labor and production expenses associated with welding beam and reducer design after testing two engineering application challenges. When it comes to lowering manufacturing costs and overall weight, the MSFDBO outperforms other swarm intelligence optimization methods. Full article

An in-depth analysis was conducted on the dynamic strength design optimization of carbon fiber composite cap cones in aircraft engines subjected to bird body impacts. Initially, the top, 1/4, 1/2, 3/4, and root positions of the cap cone’s generatrix were designated as the impact sites. The analysis of bird impacts revealed that the 1/2 position along the generatrix is the most hazardous impact location. Subsequently, considering the thickness of the composite material cap cone as a variable and accounting for its high-speed rotational state, a bird impact analysis was performed at the most critical impact location. Additionally, a comparative study on the bird impact performance of the composite material cap cone under rotating and non-rotating conditions was conducted. The study indicates that, under identical conditions, the cap cone in rotation experiences more severe damage than in a non-rotating state, necessitating a cone thickness of 7 mm or greater; Subsequently, a bolt strength analysis model was established to thoroughly examine the impact of varying cone side thicknesses on the load applied to connecting bolts, and to assess bolt strength. The findings suggest that excessive bolt loads can also constrain the optimization of the cap cone; hence, finding the optimal balance between bolt quantity and strength is essential in design. Lastly, the study discussed the weakening of local stiffness in the composite material cap cone post-impact, noting a 12% decrease in its elastic mode frequency and the emergence of asymmetric vibration modes. This phenomenon could potentially lead to dynamic unbalanced loads, thus necessitating further evaluation in the optimization process of the cap cone. Full article

One of the most challenging aspects of designing a humanoid robot is ensuring stable walking. To achieve this, the kinematic architecture must support 3D motion and maintain equilibrium, particularly during single-foot support. Without proper configuration, the robot may experience unbalanced weight distribution, significantly increasing the risk of falling while walking. While adding redundant degrees of freedom (DOFs) can enhance adaptability, it also raises the system’s complexity and cost and the need for more sophisticated control strategies and higher energy consumption. This paper explores a reduced-DOF bipedal robot, which, despite its limited number of DOFs, is capable of performing 3D motion. It features an inverted pendulum and elastic ankles made of thermoplastic polyurethane (TPU), enabling effective balance control and attenuation of disturbances. The robot’s electromechanical design is introduced alongside the kinematic model. Momentum equilibrium in a pseudo-static mode is considered in both the frontal and sagittal planes, taking into account the pendulum and the swinging leg during the single support phase. The TPU ankle’s performance is assessed based on its ability to resist external bending forces, highlighting challenges related to the robot’s weight equilibrium stability and ankle inversion. Experimental results from both Finite Element Analysis (FEA) and real-world tests are compared. Lastly, the joint movements of the inverted pendulum-based biped robot are evaluated in both a virtual environment and a physical prototype while performing lateral tilting and various gait sequences. Full article

Aiming at the problems of insufficient power supply capacity, unbalanced load, and poor safety and reliability of the urban power grid, a flexible DC optimization control strategy is proposed to support the interconnection of power grid zones. Firstly, the steady-state and transient optimal control objectives are established to meet the safety and economic operation requirements of the grid; secondly, comprehensive evaluation indexes are constructed, covering load balancing, network loss, and voltage deviation, and a step-by-step approximation method is used to quickly solve the optimal power of the flexible DC, so as to realize the optimal control of the urban grid in the steady state. Meanwhile, a multi-terminal flexible DC adaptive sag control strategy based on the power margin of the converter station is designed to reasonably allocate the emergency power support in each partition after a fault and reduce the frequency deviation of the heavily loaded nodes. Taking the urban grid as an example, a simulation model of the grid structure with a 750 KV outer ring and a 220 KV inner ring is constructed, and the simulation results verify the effectiveness of the proposed method and its engineering practicability. Full article

To effectively address the issue of premature failure caused by the unbalanced distribution of pressure drops between the stages of a traditional two-stage finger seal, this study proposes a method to improve the pressure drop balance by increasing the protection height of the second stage back plate. We established a new numerical calculation model for a two-stage finger seal, based on the porous media model. After verifying the precision of the model, we conducted a numerical analysis to examine the impact of the protection height of the second stage back plate on the flow and heat transfer characteristics of the two-stage finger seal. We then conducted a differentiated structural design for each stage of the two-stage finger seal. The research results are as follows: the pressure drop at the second stage of the traditional two-stage finger seal exceeds that of the first stage; when the protection height of the second stage back plate of the traditional two-stage finger seal is increased from 1.5 mm to 1.57 mm, forming a two-stage pressure equalizing finger seal structure, the pressure drop between the two stages is balanced, but the leakage is greater than that of the traditional two-stage finger seal; a grate seal structure was arranged between the first and second stages of the two-stage pressure equalizing finger seal to form a two-stage pressure equalizing finger seal with grate teeth, which exhibits significantly lower leakage compared to the two-stage pressure equalizing finger seal. However, the proportion of pressure drop at the first and second stages of the two-stage pressure equalizing finger seal is 36.8% and 42.1%, respectively, while the grate tooth stage accounts for 21.1%, resulting in an imbalanced pressure drop once again. Increasing the protection height of the second stage back plate in the two-stage pressure equalizing finger seal with grate teeth to 1.6 mm results in a 37.5% pressure drop at the first and second stages, and a 25% pressure drop at the grate tooth stage. The two-stage finger seal balances the pressure drop and matches the leakage of the traditional two-stage finger seal. The maximum temperatures of the first and second stages of the finger seal are 0.7% lower and 2.6% higher compared to the traditional two-stage finger seal. This suggests that a differential multi-stage finger seal is the optimal structure. Full article

In the heavy-duty vehicle industry, unbalance in the armature is one of the most common problems affecting starters’ performance and durability. This research presents a comprehensive study to improve the balancing process for starting rotors in heavy-duty vehicles. The complete manufacturing process of armatures was analyzed to understand the contribution of assembly processes to unbalancing. The analysis revealed that the primary factor leading to high unbalance in these parts is the misalignment of conductors within the armature winding. During assembly, these conductors experience axial movements, resulting in non-uniform mass distribution and causing unbalanced values ranging from 150 to 350 g·mm. These values surpass the permissible limit, making rectification during the balancing process at the end of the assembly impossible. Consequently, a novel alignment tool was designed to address this issue, significantly reducing the effect and achieving the maximum allowable unbalance of 100 g·mm. This allowed the balancing machine used in the process to correct the initial unbalance of the reinforcements in a single work cycle, improving operation efficiency by about 15%. Full article

For ultra-high-speed digital transmission, required by 5G/6G communications, ultra-wideband common-mode rejection (CMR) structures with autonomous phase-balancing capability are proposed. Common-mode noise, caused by phase and amplitude unbalances, is one of the most undesired disturbances affecting modern digital circuits. According to the circuit design guides with a typically used differential line (DL) for high-speed digital transmission, common-mode rejection is achieved using CMR filters, and the unbalanced phase, caused by a length difference between the two signal lines of a DL, is compensated by inserting an additional delay line. However, due to nonlinear phase interactions between the two DLs and unbalanced electromagnetic (EM) interferences, the conventional compensation method is frequency-limited at around 10 GHz. To significantly enhance the common-mode rejection level and extend the phase recovery bandwidth, the proposed CMR structure utilizes a planar balanced line (BL), such as a coplanar stripline (CPS) or a parallel stripline (PSL), along with additional conductor strips arranged laterally near the BL. To demonstrate the performance of the proposed BL-based CMR structures, various types of CMR structures are fabricated, and the measurement results are compared with the 3D EM simulation results. As a result, it is proven that the proposed BL-based CMR structures have the capability to reject the common-mode noise with suppression levels of more than 10 dB and to simultaneously recover the phase balance from near DC to over 40 GHz. Full article