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YANG Xi, TIAN Chong, FANG Ruyi, LIU Zeyu, ZHANG Yinhang, LEI Kejun
Available online:May 19, 2022 DOI: 10.16339/j.cnki.hdxbzkb.2022353
Abstract:The classical maximum eigenvalue detection (MED) algorithm has excellent performance in detecting correlated signals. However, with the increasing signal dimensionality, the MED algorithm faces serious problems in the calculation efficiency and implementation of test statistic and decision threshold, thus greatly limiting the further application of the algorithm in modern cognitive communication systems. To this end, a low-implementation complexity MED algorithm based on a numerical analysis theoretical framework is proposed. The new algorithm uses the Rayleigh quotient accelerated power method to iteratively compute the test statistic, which has a fast convergence rate in detecting high-dimensional signals compared with the classical power method; meanwhile, different from the classical look-up table method, a threshold calculation method based on the cubic spline interpolation method is proposed, which can quickly determine the decision threshold corresponding to any given target false-alarm probability. The proposed MED algorithm effectively improves the computational efficiency and reduces the complexity of algorithm implementation while maintaining the detection performance of the original algorithm, which is particularly attractive for spectrum sensing problems in high-dimensional conditions. Finally, the simulation results demonstrate the effectiveness of the proposed algorithm.
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Available online:May 19, 2022 DOI: 10.16339/j.cnki.hdxbzkb.2022355
Abstract:A terahertz fundamental up-conversion mixer with a high local oscillator (LO)/ radio frequency (RF) and local oscillator / intermediate frequency (IF) port isolation was presented, which was in the IHP 0.13μm SiGe BiCMOS process. The mixer adopted Gilbert’s double-balanced structure, local oscillator signal was transmitted through the Coplanar Waveguide (CPW) to suppress the transmission asymmetry caused by the strong parasitic coupling effect in the transmission process, which reduced the characteristic of LO/RF port isolation deterioration caused by the asymmetry. By adopting an asymmetric switch interconnection structure, the imbalance of the parasitic coupling of the local oscillator signal at the collectors of the switching transistors was reduced, and the cancellation efficiency of the local oscillator signal at the collectors of the switching transistors was improved. And the local oscillator signal was suppressed at the port of intermediate frequency by arranging the position of the transconductance transistors in a reasonable layout. The post-simulation results show that under the power supply voltage of 2.2V, the local oscillator signal is 230GHz and the intermediate frequency signal is 2-12GHz, when the up-conversion mixer works at 218-228GHz, the LO/RF port isolation is greater than 24dB, LO/IF port isolation is greater than 20dB, the conversion gain is -4dB to-3.4dB. The output 1dB compression point is -14.8dBm with an intermediate frequency signal is 10GHz. The DC power consumption is 42.4mW, the core area of the chip is 0.079mm2.
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YUAN Yongjie, YANG Liang, CHEN Shenghai, MA Rongchang
Available online:May 17, 2022 DOI: 10.16339/j.cnki.hdxbzkb.2022296
Abstract:Free space optical (FSO) communications offer high speed, low cost, and strong anti-interference ability. However, the atmospheric turbulence-induced fading causes deterioration in the performance of FSO communication systems. The conventional solution is to use RF links as parallel communication links to improve the system performance. On the other hand, reconfigurable intelligent surfaces (RIS) can be employed to further improve the received signal-to-noise ratio of the RF link due to its advantages of low loss, easy deployment, and no complex coding and decoding. In this paper, an RIS-assisted hybrid RF-FSO transmission system is proposed to improve the communication quality of service. Based on this hybrid model, exact expressions for the outage probability, average BER, and channel capacity are derived, and Monte-Carlo simulations are presented to verify the accuracy of the analytical results. Results show that the performance of the proposed system is significantly improved compared to the conventional hybrid RF-FSO system.
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Available online:May 17, 2022 DOI:
Abstract:The mechanism for asymmetric transmission is an important issue for enhanced sensing, amplification and asymmetric control of elastic waves. Parity-Time symmetric systems may provide a simple solution. The concept of Parity-Time symmetric systems comes from quantum mechanics, and one of its characteristics is unidirectional reflectionlessness. A PT symmetric beam for flexural waves is designed, which is based on piezoelectric shunting technology. Firstly, the PT symmetric condition is derived. Then, based on the effective medium method and finite element simulation, it is verified that the effective parameters of gain and loss unit meet the PT symmetric condition. The tunability of exception points is studied by changing the resonant frequency and the shunting resistance. Finally, the scattering property of the PT sym-metric beam is derived by transfer matrix method and finite element simulation, and the relationship between exceptional points and unidirectional non-reflection is illustrated. The calculated and simulated results show that the PT symmetric beam has several exceptional points including 511Hz and 520.5Hz. When the incident flexural waves of 511Hz is applied at the right side of the PT symmetric beam, the reflection coefficient is close to zero. However, when the frequency of the incident flexural waves changes to 520.5Hz, it should be applied on the left side of the PT symmetric beam in order to gain a total transmission without reflecting. The structure of the proposed PT symmetric beam is simple and the exceptional points of it are tunable, which can be used to achieve better asymmetric transmission of flexural wave.
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Available online:May 17, 2022 DOI: 10.16339/j.cnki.hdxbzkb.2022297
Abstract:With the rapid development of Internet, virtual communities are emerging. While providing innovative resources, these communities also have problems such as low willingness of users to share and lack of good incentive mechanism. Blockchain can better solve these problems and promote community knowledge sharing. This paper constructs an online community knowledge sharing scheme based on Multi Chain, puts forward the resource access and storage mode of "metadata cloud storage" and designs the metadata information table in detail, designs the overall framework of the knowledge sharing scheme and the key processes of some businesses, puts forward the consensus mechanism of "Nominated Proof of Stake (NPOS) to design the blockchain network, Some functions of online community knowledge sharing are realized. Through analysis and experiment, the scheme of this paper has good scientific rationality, safety and execution efficiency, and has good reference value for the development of other related projects.
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Available online:May 17, 2022 DOI: 10.16339/j.cnki.hdxbzkb.2022299
Abstract:Affected by suspended particles such as haze in the atmosphere,images taken outdoors often suffer from low contrast and low visibility. Existing dehazing methods fail to make full use of the local feature information of the image, and cannot fully extract the global details of the image. Therefore, there are problems such as incomplete dehazing and loss of image details. For this reason, this paper proposes a T-shaped image dehazing network based on wavelet transform and attention mechanism. Specifically, the proposed network obtains the edge detail features of the hazy image by performing multiple discrete wavelet decomposition and reconstruction on the image, and proposes a feature attention module that takes into account both the global feature and the local information extraction of the image, which strengthens the network"s learning in image visual perception and detail texture. Secondly, in the process of feature extraction, a T-shaped method is proposed to obtain multi-scale image features, which expands the network"s representation ability. Finally, perform color balance on the reconstructed clear image to obtain the final restored image. A large number of experimental results in synthetic data sets and real data sets show that the network proposed in this paper has superior performance compared with other existing network models.
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Available online:May 17, 2022 DOI: 10.16339/j.cnki.hdxbzkb.2022300
Abstract:This paper proposes a state-sensitive event-triggered H∞ control strategy to solve the problem of unmanned ground vehicle (UGV) path tracking control under communication restriction. Firstly, the corresponding path tracking control model is established according to the dynamics of the connected vehicle. Secondly, a novel state-sensitive event-triggered communication (SS-ETC) strategy according to the state perception of path tracking in real time is proposed. Then, an event-triggered H∞ controller is designed by combining with time delay system modeling method and Lyapunov stability theory. The proposed dynamic event-triggered communication strategy based on state perception can dynamically adjust the communication threshold according to the state measurements of the control system, and effectively realize the adaptive co-design of UGV communication and control. Finally, the effectiveness of the proposed dynamic event-triggered control strategy is verified by simulation experiments.
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Chen jian, Zhuang yao yu, Yang dan, Zhang jun jie
Available online:May 17, 2022 DOI: 10.16339/j.cnki.hdxbzkb.2022351
Abstract:Although MIMO technology can improve the utilization rate of spectrum, multi-dimensional signal processing brings great challenges to the detection of MIMO signals. Based on the analysis of various MIMO detection algorithms, QR decomposition is selected as the research object, which is a kind of nonlinear algorithm. In order to obtain higher performance of detection, the sorted QR decomposition is further studied and propose the sorting scheme based on L1-norm. Using Matlab for performance simulation, the L1-norm sorting strategy and the L2-nrom sorting strategy have basically the same impact on MIMO system, but the L1-norm sorting strategy reduces the computational complexity. On this basis, the hardware structure of improved sorted QR decomposition by Givens rotation on FPGA is proposed. Comparing with the solution of L2-norm, the L1-norm strategy reduces at least 29.2% combinational logic resources and 32.4% register resources when calculating a single column norm in the realization of 4×4 channel matrix decomposition. Comparing with similar designs, the frequency of operating clock has been significantly improved.
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wangzhenyu, Guo Yang, Li Shaoqing, Zeng Jianping
Available online:May 17, 2022 DOI: 10.16339/j.cnki.hdxbzkb.2022352
Abstract:With the development and application of communication networks, the Internet of Things carries the safe transmission and storage of a large amount of sensitive information. Since devices are usually small in size and resource-constrained, complex security primitives are not suitable for authentication of lightweight IoT devices. This paper proposes a lightweight anonymous key shared authentication protocol for IoT devices, which generates a shared key by the physical unclonable function(PUF) and uses security primitives such as the MASK algorithm and the Hash function. The security analysis and verification are accomplished by Ban logic and ProVerif to prove that the protocol ensures security attributes such as anonymity, non-repudiation, and forward/backward confidentiality. Compared with other protocols, this protocol has the characteristics of low computing cost, small communication overhead and storage capacity, and high security performance, which is suitable for the secure communication transmission of resource-constrained devices.
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LIU Guangyu, CAO Yu, ZENG Zhiyong, ZHAO Enming, XING Chuanxi
Available online:May 17, 2022 DOI: 10.16339/j.cnki.hdxbzkb.2022354
Abstract:Sonar image is seriously polluted by noise, which leads to the problem of low precision in underwater multi-target segmentation.Therefore, an underwater multi-object segmentation technique based on self-adjusting spectrum clustering combined with entropy weight method is proposed.The technology first by self-tuning spectral clustering of sonar image pixel clustering processing, make the image is divided into multiple independent area, and then according to the characteristics of complementarity and more sections of the redundancy of the statistical information entropy characteristics, brightness, contrast, long and narrow degree, entropy weight method is used to analyse the characteristics more empowerment and the optimal selection of a target area,Then the optimal target region is matched with all regions by multi-feature similarity. Finally, all target regions are segmented automatically by adaptive threshold iterative method according to the matching results of similarity. Experimental results show that there is not over-segmented of noise interference regions, and target regions segmented have higher accuracy, which verifies the effectiveness of the proposed method.
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JIANG Weilai1，2，Wang Wenlu1，2?，WANG Yaonan1，2
Abstract:To address the challenges of slow convergence rates， low success rates， and poor model generalization in deep reinforcement learning algorithms for UAV intelligent tracking decision-making under a complex environment， this study combines the attention mechanism with the deep deterministic policy gradient （DDPG） approach and introduces an attention-DDPG model. Meanwhile， incorporating a multi-experience pool method， a proposed algorithm， named multi pool attention deep deterministic policy gradient （MPADDPG） is built up， and the attention mechanism is integrated into DDPG’s Actor network. This allows for different weights to be assigned to various state components， so as to highlight the crucial information， while a multi-experience pool strategy is employed to distinguish unsuccessful experiences from successful ones in order to improve convergence. Additionally， enhancing the UAV’s environmental perception capabilities further boosts the algorithm’s generalization ability. The effectiveness of MPADDPG is validated within a continuous state and action space framework established in this research. Simulation results demonstrate that MPADDPG achieves an intelligent tracking success rate exceeding 90%， outperforming DDPG in both tracking success and generalization capability.
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XU Biao1，2，ZENG Conglei1，ZHANG Runbang1，HUANG Shengjie1，LIU Shuo1，QIN Xiaohui1，2?，WANG Ruoqin3
Abstract:Loop closure detection is a crucial component of SLAM systems， enabling the elimination of accumulated odometry errors. Traditional appearance-based methods face challenges in handling large viewpoint changes. This paper proposes a visual loop closure detection method based on semantic topological information. By leveraging the viewpoint invariance of object landmarks and encoding scenes through an object-oriented semantic topological map， the method significantly enhances system robustness under large viewpoint changes. Specifically， the method maintains a hierarchical semantic landmark database and adopts a “coarse-to-fine” detection strategy. First， high-level macroscopic object landmarks are utilized to extract topological graphs for coarse matching via local topological descriptors； to effectively eliminate mismatches， local and global topological graphs are unified in a polar coordinate system to evaluate spatial distribution similarity. Subsequently， guided by accurate object matches， fine registration is performed using low-level microscopic point landmarks to optimize pose estimation. Experimental results on the TUM and USTC datasets demonstrate that the proposed method exhibits superior performance in both precision and recall， achieving an average precision of over 80%. Notably， in large-disparity loop closure scenarios， positioning accuracy is improved by more than 40%.
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Crack detection enhanced by combining dynamic snake convolution and deformable attention transformer
CHEN Yong1，2?，ZHOU Jianyu1，AN Zhuoaobo1
Abstract:In response to the diverse and complex nature of cracks in ballastless track slabs， existing crack detection methods suffer from insufficient extraction of crack target features， discontinuity detection and low accuracy. A crack detection enhanced method is proposed based on dynamic snake convolution and deformable attention Transformer. Initially， the approach enhances the ResNet-50 feature extraction backbone by using a dynamic snake convolution on the basis of the Mask2Former segmentation model. The dynamic snake convolution， with its continuous prediction capability， improves the feature extraction network's ability to fit the geometric features of diverse ballastless track cracks， enhancing the extraction of crack features and overcoming discontinuity detection issues. Subsequently， a deformable attention Transformer decoder module is designed to enable the model to dynamically adapt to changes in local features of ballastless track cracks， in order to enhance the ability to capture global contextual information and improve the accuracy of crack recognition. Furthermore， an improved feed-forward network （FFN） is incorporated into the Transformer decoder to learn local information around the cracks， facilitating more accurate capture of local details and improving detection accuracy. Finally， the output of the Transformer decoder is fused with the pixel decoder output to obtain the crack detection results. Experimental results demonstrate that the proposed method accurately detects cracks of various shapes. It achieves a 6.34 percentage points increase in average accuracy， a 14.47 percentage points increase in average recall， and an F1-score of 94.30% compared to the original Mask2Former model. The proposed method exhibits superior performance in the detection of surface cracks on ballastless track slabs， enhancing detection accuracy and outperforming comparative methods in both subjective and objective evaluations.
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WANG Dengfei1，SU Hongsheng1?，GE Leijiao1，WANG Shaofei2，YIN Wenfu3
Abstract:The trouble of moving electric multiple units detection system （TEDS） needs to detect components with diverse shapes and sizes， which leads to high false positive and missed detection rates in existing detection methods. Therefore， a pseudo anomaly multi-head depth separable self-attention reverse knowledge distillation network is proposed to achieve anomaly detection on TEDS images. Firstly， the self-attention head vector is generated by replacing the matrix with depthwise separable convolution， and the sharp distribution of similarity is adjusted with a focus function. The constructed multi-head depthwise separable linear self-attention enjoys linear computational complexity. Secondly，a lightweight attention teacher-student model based reverse knowledge distillation network is constructed using a bottleneck residual module and a multi-head depth separable linear self-attention module， which improves the network’s feature extraction ability while reducing the number of trainable parameters， and accelerates the detection speed. Projection layers are set after each module of the teacher network. Meanwhile， the Simplex and random cropping pseudo-defect mechanisms are employed to simulate pseudo-defect samples during training. Through multi-loss guidance， the projection layers are pushed away from the normal feature space to exclude defect information， forcing them to focus on exploring deeper representations of normal features and restricting the flow of defect information to the student network， resulting in greater feature differences between the teacher and student networks for anomaly. Research shows that the improved network can effectively enhance the anomaly detection capability of TEDS images； the evaluation metrics of image-Auroc， pixel-Auroc， and Aupro reach 94.6%， 93.3%， 80.1%， respectively. Compared with other algorithms， these metrics show improvements of 3.3， 3.8， 4 percentage points， respectively. This method can achieve a detection speed of 0.37 seconds per sheet， meeting the real-time requirements of TEDS systems.
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Abstract:Aiming at the issue of imperfect channel state information （CSI） caused by the passive nature of eavesdroppers， this paper introduces an external friendly jammer to degrade the quality of the eavesdropper channels and proposes a robust physical layer security optimization method for a downlink communication system with dual-sided single user and multiple eavesdroppers， assisted by a Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface （STAR-RIS） and cooperative jamming. The objective is to maximize the system’s sum secrecy rate （SSR） under the worst-case scenario， by jointly designing the beamforming vectors at the base station （BS） and the jammer， as well as the transmit/reflection coefficient matrix of the STAR-RIS. Since the formulated optimization problem is a non-convex problem with multiple coupled variables， an efficient iterative algorithm is developed by leveraging alternative optimization （AO）， semidefinite relaxation （SDR）， and the S-procedure to obtain a suboptimal solution. Simulation results demonstrate that the proposed robust scheme significantly enhances the secrecy performance of the system compared to baseline schemes.
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LIN Junting1，2?，CHEN Yu1，ZOU Jiping1
Abstract:In addressing the shortcomings of extant methodologies for point cloud registration， including inadequate robustness， inaccurate feature representation and sensitivity to initial registration， particularly in the context of noisy point clouds， a novel point cloud registration network structure， RPM-AFAMNet， is proposed. This structure is constructed by integrating an adaptive feature aggregation module （AFAM） within the RPM-Net network. The AFAM is comprised of two modules： the Batch Attention Mechanism （BatchFormer） and the Dynamic Re-aggregated Feature Representation （DRFR） module. The purpose of the AFAM is twofold： firstly， to enhance the robustness of the network， and secondly， to optimise the representation of point cloud features. The BatchFormer is designed to mitigate the interference of noisy points by batch-weighted learning of point cloud features. The DRFR module， meanwhile， enhances the understanding of point cloud spatial relationships through a dynamic feature reorganisation strategy. This， in turn， improves the accuracy of point cloud alignment. Finally， the network is tested on the ModelNet40 dataset and significant improvements are achieved in six evaluation metrics， such as rotational and translational mean square error. Compared with RPM-Net， the following reductions are achieved： 32.07% for rotational mean square error， 75.85% for rotational mean absolute error， 33.83% for translational mean square error， 79.23% for translational mean absolute error， 33.02% for rotation angle error， and 33.99% for translation distance error. The experimental results demonstrate the efficacy of the proposed method in enhancing the registration performance of noise-containing point clouds.
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ZHOU Changjiang1?，TANG Shan1，LIU Yahui2，MA Yinjie1
Abstract:To meet the optimization demands of the piston cooling system in a highly enhanced engine， a CFD model of the piston cooling nozzle jet based on the Dispersed-VOF method was established. The model incorporated the gas volume fraction and was validated by the results of the high-speed camera test under multiple operating conditions. The jet characteristics of the piston cooling nozzle and their influencing mechanisms were systematically investigated. Based on the parameters of jet velocity， turbulence intensity and dissipation， and divergence angle， the influences of engine speed （600~1 800 r/min） and length-diameter ratio of cooling nozzle （1~6） on jet characteristics were analyzed. This study provides the first quantitative revelation of the linear relationship between the gas volume fraction of the jet and engine speed， as well as the linear relationship between the divergence angle and engine speed： for every increase of 300 r/min in engine speed， the gas volume fraction is decreased by an average of 4.2%， and the jet divergence angle is increased by an average of 0.14°. It also finds that the nozzle with a length - diameter ratio of 4 exhibits relatively superior jet divergence characteristics and turbulence intensity during operation， which can effectively improve the oil intake efficiency and enhance the cooling effect.
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Abstract:This study systematically investigates the optimization of selective laser melting （SLM） process parameters for K418B nickel-based superalloy to enhance its mechanical properties. The effects of key parameters， such as laser power and scanning speed， on the density， microstructure， and mechanical performance of the fabricated parts were explored. The optimal process window was determined by characterizing and quantifying micro-defects in samples prepared with various volumetric energy densities （Ev）. Furthermore， the intrinsic relationship between process parameters， microstructure evolution， and mechanical properties was revealed through EBSD analysis and in-situ tensile testing. The results demonstrate that a relative higher density exceeding 99.6% can be consistently achieved when the Ev is below 60 J/mm3， effectively suppressing defects like pores and cracks. Within the optimal process window of Ev= 40~50 J/mm3， the alloy exhibited excellent comprehensive mechanical properties， with its yield strength， ultimate tensile strength， and elongation reaching 780 MPa， 875 MPa， and 2.5%， respectively. This work confirms that optimizing SLM process parameters to minimize micro-defects is crucial for improving the performance of the K418B alloy.
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HUANG Shuai，Wu Xinlong，HUANG Bangzhu，LIU Tianyu，FENG Kai?
Abstract:To improve the utilization efficiency of hydrogen in fuel cell systems， a novel vane-type hydrogen recirculation pump was designed， with a particular focus on the static and dynamic performance of its key component—the herringbone-grooved gas-lubricated bearing. By constructing the gas-lubricated Reynolds equation and applying the finite difference method combined with Newton iteration， the gas film pressure distribution of the herringbone-grooved bearing with a rectangular groove bottom was systematically analyzed. The influence of groove depth ratio， groove length ratio， and spiral angle on load capacity was investigated. Furthermore， a small perturbation method was introduced to examine how key parameters， such as rotational speed and radial clearance， affect the stiffness and damping characteristics of the bearing. The results show that increasing the groove depth and length ratios reduces the load capacity， while an optimal spiral angle in the range of 50°-60° yields the highest load capacity. Dynamic analysis reveals that stiffness coefficients increase with speed， whereas damping coefficients decrease； both stiffness and damping coefficients decrease with increasing radial clearance. To validate the proposed model， a hydrogen recirculation pump test bench was constructed， and it was observed that when the speed exceeds 50 000 r/min， nonlinear vibrations and instability may occur. The findings provide theoretical guidance and engineering reference for the design of high-efficiency and stable hydrogen recirculation pumps.
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WU Yiwan，YANG Hao，BAI Hongbai?，TANG Yu，RAO Zhiqiang
Abstract:A new type of bellows-type composite damping vibration isolator was designed to address the complex structure and poor sealing of the bellows vibration isolator and the metallic rubber composite vibration isolator. Static mechanical tests were carried out on different parameters affecting the vibration isolator. The mechanical properties were characterised using average stiffness， energy dissipation， and structural loss factor. The results showed that the addition of metallic rubber and dimethyl silicone oil significantly enhanced the mechanical properties of the vibration isolator and the performance increased with the increase in the density of metallic rubber. At 4 mm displacement loading， the annular metallic rubber enhanced the vibration isolation performance significantly. As the loading displacement increases， the energy dissipation and structural loss factor increase continuously， while the average stiffness shows a slightly decreasing trend. Finally， based on the equivalent damping model of the trace method and considering the rules of change， such as density and deformation amplitude， a static mechanical model was constructed using the parameter decomposition identification method， with stiffness prediction error of less than 1.5%.
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YE Nanhai1，ZHANG Shengxiong2，WANG Songwen2，LIU Sanxing2，JIANG Wenping2，ZHANG Chao1?
Abstract:Aiming at the multi-axial fatigue failure problem caused by the long-term cyclic load of the linear vibrating screen plate in the cigarette production line， research on its fatigue life prediction and life distribution is carried out. Taking the rework cigarette production line equipment of a certain factory as the research object， its dynamic model is constructed according to the actual operating conditions， the force of the elastic element is solved， and the force is imported into ANSYS as the input condition for finite element analysis， so as to obtain the stress distribution during the operation of the vibrating screen. By extracting the results of stress components and combining them with the multi-axial high-cycle fatigue life prediction model based on the critical plane method， the fatigue life of the vibrating screen plate is evaluated， and the fatigue risk parts of the structure are identified. With the aid of dynamic modeling， static analysis and multi-axial fatigue theory， a comprehensive analysis method suitable for cigarette equipment under constant amplitude loads is proposed. The research results show that the damage degree of the vibrating screen surface is relatively small. The maximum force-bearing part is located at the connection between the lower screen surface and the shock-absorbing spring， which has a high consistency with the position of the lowest service life point.
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YAO Donghui，REN Yongsheng?，ZHANG Jinfeng
Abstract:To improve the convergence performance of the AMDM （adomian modified decomposition method） in solving the differential equations of vibration problem of non-uniform Timoshenko beams under elastic boundary conditions， the adaptive segmentation technology is introduced to the calculation process of the AMDM. By making the integral absolute error estimation of Taylor expansion of section shape dependent terms meet specific thresholds， the length of each segment and the number of segments are obtained automatically for non-uniform beams with shape functions of different power indices and taper ratios. The effects of taper ratio， length-to-height ratio， power index of shape functions and boundary stiffness on natural frequencies of linear， power， and exponential non-uniform beams are analyzed and the factors affecting convergence are discussed. The numerical results show that the reduction of calculation time ranges from 46% to 91% compared with conventional AMDM in different cases. In addition， compared with the finite element simulation， the error of the calculation results in this paper is less than 0.16%， which verifies the effectiveness and accuracy of the method. It is found that the natural frequency exhibits varying sensitivity to length-to-height ratio successively from large to small for power， linear， and exponential non-uniform beams. The boundary support stiffness determines the increasing or decreasing trend of the frequency-taper curve.
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Abstract:To address the issue of the high-dimensional integral of the normalization factor in the calculation of the likelihood function in traditional Bayesian methods， an approximate Bayesian finite element model updating method based on Wasserstein distance is proposed. Firstly， a radial basis function surrogate model is constructed to replace the finite element model to reduce the computational load. Secondly， the Wasserstein distance is selected as the similarity measurement index to measure the overall distribution difference between the experimental observation data and the finite element model simulation data， overcoming the sensitivity of the traditional measurement method to local errors. Finally， the approximate Bayesian-sequential Monte Carlo sampling method is adopted to solve the likelihood， which converges with only a few iterations， thereby efficiently identifying the posterior distribution of the parameters. The proposed method is verified through numerical examples of a three-degree-of-freedom spring， a simply supported beam and a steel truss， as well as a 3 kW small wind blade test.
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JIA Ran，XING Peixin，CHEN Tao?，SUN Jingchao
Abstract:To address the issue of low accuracy in anomaly detection for integrated transmission devices caused by high data complexity during operation， this paper proposes an integrated GRU-CNN anomaly detection model based on dynamically gated regulation. The model dynamically generates regulation factors for the update gate and reset gate of the GRU through a gating mechanism， enabling flexible adjustments at each time step. This achieves the combined effect of the dynamically gated regulation mechanism and the GRU. By preprocessing sensor monitoring data and partitioning datasets to clean redundant data， the dynamically gated regulation mechanism selects critical features， assigns appropriate weights， and adjusts these weights in real-time according to operational states. Validation through two anomaly detection case studies on integrated transmissions shows that， compared to traditional methods， the proposed method significantly improves detection accuracy—achieving 99.40% and 98.36%—thus verifying its effectiveness. The dynamically gated GRU-CNN approach provides a novel solution for anomaly detection in integrated transmission devices.
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TAN Yanghong1?，LI Zhongxiang1，2，ZHONG Hao1
Abstract:The operational reliability of power transformers is inextricably tied to the security of the power system. Short circuits are the most common faults for transformers. These faults generate large short-circuit currents and electromagnetic forces that can deform the windings， compromise winding stability， and cause insulation failure. However， due to the high cost of full-scale testing， there is limited validation of such phenomena through prototype tests on actual transformers under short-circuit conditions in current research. Accordingly， a synergistic methodology for assessing transformer winding stability is developed， incorporating both multi-physics field simulation and cumulative short-circuit impulse experiments. An electromagnetic-structural field coupled transformer model is used to calculate the maximum radial stress in the low-voltage winding. An iterative solution yields the cumulative impulse test waveform， which is then applied to a new， full-size power transformer under an industry–academic collaboration to perform a real-condition short-circuit cumulative impulse test. Comparative analysis of the experimental and simulation results demonstrates that the proposed method can effectively assess the radial stability of transformer windings， providing a reliable basis for predicting winding deformation and analyzing insulation reliability.
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Abstract:To reduce the quiescent current and chip area of the bandgap reference voltage source， a low-power subthreshold reference voltage source circuit is designed by optimizing the bias current generation circuit and the dual-output startup circuit. The bias current generator employs subthreshold-operated NMOS transistors instead of BJTs so as to provide nA-level biasing for the reference output circuit， significantly reducing power consumption and area. The startup circuit adopts a dual-output structure， providing an additional charging and discharging path for the bias current generation circuit during power-up， eliminating degenerate operating points and accelerating settling time. Based on the 0.5 μm CMOS process， the circuit design and tape-out testing are completed. The results show that within the power supply voltage range of 1.8~5 V， the reference output voltage is 1.145 V， and the maximum line regulation is 0.6 ×10-3； within the range of -20~100 ℃， the temperature coefficient is 45.6 ppm/℃； at low frequencies， the power supply rejection ratio is -84 dB@10 Hz， and over the entire frequency range， the power supply rejection ratio is less than -26 dB； the static current is less than 270 nA； and the layout area is 0.02 mm2. This reference voltage source features a low power consumption and a compact area， making it suitable for energy-constrained applications.
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DONG Haiyan1，LIANG Bo1，YAN Ningning1，DOU Jianming2?，WANG Sirun3，LIN Xiaojun4
Abstract:The double-break molded case circuit breaker （MCCB） has the characteristics of rapid breaking and double-arcs motion. As the key equipment of short-circuit protection， it is widely used in the low-voltage distribution system of a traction substation. In this paper， the simulation model of the double-arcs of a double-break MCCB coupled with mechanical-electromagnetic-thermal-flow multi-physics is established based on the theory of kinematics and magneto hydrodynamics （MHD）. By considering the mechanical motion of the operating system， the parametric fitting function is used to control the rotation and breaking of the conductive bridge， so as to realize the synchronous coupling of mechanical motion and arc behavior. The temperature， pressure and current density are taken as the characterization parameters to explore the full time-space evolution trajectory of the breaking double arcs from growth， migration to extinction. The results show that the conductive bridge is rotated and broken， and the double breakpoints are opened. At the same time， the air gap is broken down， and the double arcs are formed in the left and right arc-extinguishing chamber driven by the mechanism， which is finally extinguished by motion growth and arc column cutting. The mechanical motion of the conductive bridge is significantly nonlinear； the arc breaking time is 3.2 ms； and the arc extinguishing time is 3.5 ms. The temperature of double-arcs is related to the change of current， while the arc heat and power exhibit synchronous changes with a “Λ”-shaped distribution. Due to the influence of the thermal difference between the two arcs and the splitter plates obstruction， the double flow vortices and the double pressure cavities in the left and right arc extinguishing chambers have an impact on arc extinguishing. The formation of several short arcs and the attenuation of current cause a sharp increase in arc resistance and promote arc extinguishing. The variation of arc current and voltage characteristic curves obtained by simulation and experiment is basically the same， which verifies the accuracy of the model.
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Wang Zhendao1，Bao Mingkang1?，He Long2
Abstract:The performance of the on-chip power supply directly affects the operating state and energy efficiency of the entire chip， and a low-dropout linear regulator （LDO） is usually used as its step-down power supply on the chip. However， with the increase of input and output voltage difference， the conversion efficiency of LDO decreases significantly. The conversion efficiency of the DC-DC converter is significantly better than LDO， and it does not change with the pressure difference， but it has inherent limitations in ripple suppression. In this thesis， a new chip power supply solution for Buck DC-DC converter based on COT control architecture is proposed. In terms of reducing ripple， the current feedback circuit is innovatively introduced to realize the decoupling of ripple and loop control signal. At the same time， multilayer ceramic capacitors with low equivalent series resistance are selected as the output filter element， so as to reduce the ripple and maintain the stability of the system at the same time. The module is designed based on SMIC 40 nm CMOS process. The test results show that the conversion efficiency of the power module under all working conditions is more than 83.5%. The maximum output voltage ripple is less than 1.2 mV， When the load changes suddenly， the voltage fluctuation is less than 11.1 mV.
Vol, 53, No.4, 2026
Special Issue
Virtual Special Issue中国科学引文数据库来源期刊(CSCD)
第二届国家期刊奖百种重点期刊
教育部中国高校百佳科技期刊
湖南省十佳科技期刊
