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Intelligent Parameter Decision-Making and Multi-objective Prediction for Multi-layer and Multi-pass LDED Process
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作者 Li Yaguan Nie Zhenguo +2 位作者 Li Huilin Wang Tao Huang Qingxue 《稀有金属材料与工程》 北大核心 2026年第1期47-58,共12页
The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical m... The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts. 展开更多
关键词 multi-layer and multi-pass laser cladding Taguchi method grey relational analysis GB-BP network
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SVM-PSO在微铣削表面粗糙度预测中的应用
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作者 王二化 赵宇航 刘颉 《机械设计与制造》 北大核心 2026年第2期119-123,共5页
这里提出了一种基于振动信号的微铣削表面粗糙度预测方法,首先提取微铣削振动信号小波包系数的均方根、峭度、偏度以及小波包能量比作为表面粗糙度的特征,并构建特征库。然后利用基于粒子群优化算法(Particle Swarm Optimization,PSO)... 这里提出了一种基于振动信号的微铣削表面粗糙度预测方法,首先提取微铣削振动信号小波包系数的均方根、峭度、偏度以及小波包能量比作为表面粗糙度的特征,并构建特征库。然后利用基于粒子群优化算法(Particle Swarm Optimization,PSO)的支持向量机(Support Vector Machine,SVM)模型实现微铣削表面粗糙度的预测,其中,PSO用来优化SVM模型的关键参数,避免这些关键参数选择的不合适所带来的过拟合和局部最优问题。这里提出的微铣削表面粗糙度预测方法精度较高,平均预测误差为2.37%。 展开更多
关键词 微铣削 表面粗糙度 小波包分解 支持向量机 粒子群优化
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Multi-layer multi-pass friction rolling additive manufacturing of Al alloy:Toward complex large-scale high-performance components 被引量:2
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作者 Haibin Liu Run Hou +2 位作者 Chenghao Wu Ruishan Xie Shujun Chen 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS 2025年第2期425-438,共14页
At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-laye... At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components. 展开更多
关键词 aluminum alloy additive manufacturing SOLID-STATE friction stir welding multi-layer multi-pass
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基于PSO和网格优化结合的SVM算法癌症分类研究
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作者 汪颖 王琳 《兰州文理学院学报(自然科学版)》 2026年第1期56-61,共6页
针对乳腺癌良性与恶性的鉴别,提出一种融合粒子群优化与网格搜索的支持向量机模型(GPSO-SVM).该方法先通过网格搜索初步确定粒子群优化的超参数范围,并在粒子群优化迭代过程中阶段性引入网格搜索.联合完成对支持向量机超参数的优化,有... 针对乳腺癌良性与恶性的鉴别,提出一种融合粒子群优化与网格搜索的支持向量机模型(GPSO-SVM).该方法先通过网格搜索初步确定粒子群优化的超参数范围,并在粒子群优化迭代过程中阶段性引入网格搜索.联合完成对支持向量机超参数的优化,有效结合了网格搜索的全局搜索能力与粒子群算法的局部精细寻优优势,提高了参数寻优的效率与准确性.实验结果显示,GPSO-SVM模型在4种不同乳腺癌数据集上的五折交叉验证准确率分别达到98.60%、97.00%、90.52%和88.89%,优于其他寻优方法. 展开更多
关键词 癌症分类 网格搜索 GPSO-svm
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基于DWT和BO-ECOC-SVMs的异步电机调速过程匝间短故障检测与定位
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作者 马杰 曾祥浩 +1 位作者 费继友 孙钢 《电气工程学报》 北大核心 2025年第6期214-222,共9页
轨道交通车辆等运输设备较多采用三相异步电机作为驱动电机,三相异步电机经常工作于变频调速状态。为了能够在异步电机的调速过程中对其匝间短路故障进行检测和定位,首先需要测量异步电机的零序电压和三相电流,利用离散小波(Discrete wa... 轨道交通车辆等运输设备较多采用三相异步电机作为驱动电机,三相异步电机经常工作于变频调速状态。为了能够在异步电机的调速过程中对其匝间短路故障进行检测和定位,首先需要测量异步电机的零序电压和三相电流,利用离散小波(Discrete wavelet transform,DWT)分解和重构将零序电压信号和三相电流重构于不同的频带,并计算各个频带信号的均方根(Root mean square,RMS)。其次,以各频带信号RMS为故障特征,采用纠错输出码(Error-correcting output code,ECOC)结合支持向量机(Support vector machine,SVM)建立多分类模型,利用贝叶斯优化方法(Bayesian optimization,BO)对该多分类模型的超参数进行优化,采用该最优模型进行异步电机匝间短路故障检测与定位。设计试验平台对所提出的方法进行试验验证,将试验所得的样本标记为无故障、a相匝间短路、b相匝间短路和c相匝间短路4类。通过试验数据所建立的模型在训练集和测试集上的分类正确率分别为99.83%和95.31%,该结果证明了基于DWT和BO-ECOC-SVMs的异步电机调速过程匝间短故障检测与定位方法的有效性。 展开更多
关键词 匝间短路 故障检测 ECOC-svms 贝叶斯优化
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基于改进VMD和CS-SVM的汽车发动机故障诊断方法
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作者 张忠其 梁裕益 叶龙 《机械制造与自动化》 2026年第1期293-298,共6页
为提高汽车发动机故障诊断准确性,提出一种变分模态分解结合支持向量机的K20C3涡轮增压发动机故障诊断方法。采用鲸鱼算法(WOA)优化变分模态分解(VMD)层数k和惩罚因子参数α,并利用优化后的VMD获取汽车发动机振动信号,用奇异谱熵表征信... 为提高汽车发动机故障诊断准确性,提出一种变分模态分解结合支持向量机的K20C3涡轮增压发动机故障诊断方法。采用鲸鱼算法(WOA)优化变分模态分解(VMD)层数k和惩罚因子参数α,并利用优化后的VMD获取汽车发动机振动信号,用奇异谱熵表征信号特征,利用布谷鸟搜索算法(CS)优化支持向量机(SVM)核函数的参数γ及惩罚因子C,并将发动机振动信号特征输入SVM的故障诊断模型进行分类识别。结果表明:优化后的VMD可有效分解K20C3涡轮增压发动机信号,CS-SVM的诊断模型可有效识别K20C3涡轮增压汽车发动机故障类型,且相较于标准SVM和粒子群优化(PSO)-SVM的故障诊断模型,具有更高的准确性,对缸内压力信号的诊断准确率达98.45%,对缸盖振动信号诊断的准确率达到99.21%。由此得出,该方案在发动机故障诊断方面具有一定的可行性。 展开更多
关键词 发动机故障 VMD算法 奇异谱熵 svm算法 故障诊断
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基于转矩角的永磁同步电机SVM-DTC研究
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作者 董艮滔 余垚博 +5 位作者 张鑫杰 张平 严伟 郭明 雷新卓 彭恺 《工业控制计算机》 2026年第1期132-133,135,共3页
通过对永磁同步电机转矩角控制进行分析,将空间矢量脉宽调制(SVPWM)与直接转矩控制(DTC)相结合。在此基础上对速度控制器进行改进,构建了基于转矩角的SVM-DTC转速闭环控制系统。仿真结果表明这套控制架构具有良好的稳定性和动态性能,实... 通过对永磁同步电机转矩角控制进行分析,将空间矢量脉宽调制(SVPWM)与直接转矩控制(DTC)相结合。在此基础上对速度控制器进行改进,构建了基于转矩角的SVM-DTC转速闭环控制系统。仿真结果表明这套控制架构具有良好的稳定性和动态性能,实现了对电机转速更为精准的控制。 展开更多
关键词 转矩角 永磁同步电机 svm-DTC PI
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基于HEC-HMS-SVM的鄱阳湖流域平江山洪模拟研究
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作者 刘惠英 朱怀涛 吴祥宇 《水土保持研究》 北大核心 2026年第2期115-122,共8页
[目的]探究机器学习这一新方法在山洪模拟方面的应用,提高平江流域山洪模拟及早期预警精度。[方法]选取了山洪发生区1997—2018年共25场典型洪水事件及对应的5 min高分辨率降雨数据,分别构建基于HEC-HMS水文模型、支持向量机(SVM)模型及... [目的]探究机器学习这一新方法在山洪模拟方面的应用,提高平江流域山洪模拟及早期预警精度。[方法]选取了山洪发生区1997—2018年共25场典型洪水事件及对应的5 min高分辨率降雨数据,分别构建基于HEC-HMS水文模型、支持向量机(SVM)模型及HEC-HMS-SVM耦合模型,对比评估了3类模型在洪水过程模拟中的精度及稳定性。[结果](1)HEC-HMS模型对“单峰型”洪水模拟效果优异,外延性良好,整体合格率达92%(甲级精度);(2)SVM模型总体合格率为84%(乙级精度),但对峰现时间敏感性较高,率定期与验证期差异显著,稳定性较弱;(3)耦合模型综合性能最优,验证期合格率提升至100%(较SVM提高25%),整体合格率较HEC-HMS和SVM分别提高8%和16%,且洪水过程拟合度显著改善。[结论]HEC-HMS-SVM耦合模型可有效提升山洪模拟精度,为山洪灾害防治提供更可靠的技术支持。 展开更多
关键词 山洪模拟 山洪灾害 HEC-HMS svm 机器学习
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A Multi-Layer Progressive Analysis Method for Collision Energy Flow in Rail Trains
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作者 Jingke Zhang Tao Zhu +4 位作者 Xiaorui Wang Bing Yang Shoune Xiao Guangwu Yang Yuru Li 《Chinese Journal of Mechanical Engineering》 2025年第5期425-439,共15页
The huge impact kinetic energy cannot be quickly dissipated by the energy-absorbing structure and transferred to the other vehicle through the car body structure,which will cause structural damage and threaten the liv... The huge impact kinetic energy cannot be quickly dissipated by the energy-absorbing structure and transferred to the other vehicle through the car body structure,which will cause structural damage and threaten the lives of the occupants.Therefore,it is necessary to understand the laws of energy conversion,dissipation and transfer during train collisions.This study proposes a multi-layer progressive analysis method of energy flow during train collisions,considering the characteristics of the train.In this method,the train collision system is divided into conversion,dissipation,and transfer layers from the perspective of the train,collision interface,and car body structure to analyze the energy conversion,dissipation and transfer characteristics.Taking the collision process of a rail train as an example,a train collision energy transfer path analysis model was established based on power flow theory.The results show that when the maximum mean acceleration of the vehicle meets the standard requirements,the jerk may exceed the allowable limit of the human body,and there is a risk of injury to the occupants of a secondary collision.The decay rate of the collision energy along the direction of train operation reaches 79%.As the collision progresses,the collision energy gradually converges in the structure with holes,and the structure deforms when the gathered energy is greater than the maximum energy the structure can withstand.The proposed method helps to understand the train collision energy flow law and provides theoretical support for the train crashworthiness design in the future. 展开更多
关键词 Train Cllision multi-layer Progression Energy Flow Energy Conversion Energy Dissipation Energy Transfer
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Intrusion Detection Model on Network Data with Deep Adaptive Multi-Layer Attention Network(DAMLAN)
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作者 Fatma S.Alrayes Syed Umar Amin +2 位作者 Nada Ali Hakami Mohammed K.Alzaylaee Tariq Kashmeery 《Computer Modeling in Engineering & Sciences》 2025年第7期581-614,共34页
The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging at... The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging attacks,there is a demand for better techniques to improve detection reliability.This study introduces a new method,the Deep Adaptive Multi-Layer Attention Network(DAMLAN),to boost the result of intrusion detection on network data.Due to its multi-scale attention mechanisms and graph features,DAMLAN aims to address both known and unknown intrusions.The real-world NSL-KDD dataset,a popular choice among IDS researchers,is used to assess the proposed model.There are 67,343 normal samples and 58,630 intrusion attacks in the training set,12,833 normal samples,and 9711 intrusion attacks in the test set.Thus,the proposed DAMLAN method is more effective than the standard models due to the consideration of patterns by the attention layers.The experimental performance of the proposed model demonstrates that it achieves 99.26%training accuracy and 90.68%testing accuracy,with precision reaching 98.54%on the training set and 96.64%on the testing set.The recall and F1 scores again support the model with training set values of 99.90%and 99.21%and testing set values of 86.65%and 91.37%.These results provide a strong basis for the claims made regarding the model’s potential to identify intrusion attacks and affirm its relatively strong overall performance,irrespective of type.Future work would employ more attempts to extend the scalability and applicability of DAMLAN for real-time use in intrusion detection systems. 展开更多
关键词 Intrusion detection deep adaptive networks multi-layer attention DAMLAN network security anomaly detection
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General analytical solutions for one-dimensional diffusion of degradable organic contaminant in the multi-layered media containing geomembranes
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作者 JIANG Wen-hao GE Shang-qi LI Jiang-shan 《Journal of Central South University》 2025年第10期3895-3910,共16页
In practical engineering construction,multi-layered barriers containing geomembranes are extensively applied to retard the migration of pollutants.However,the associated analytical theory on pollutants diffusion still... In practical engineering construction,multi-layered barriers containing geomembranes are extensively applied to retard the migration of pollutants.However,the associated analytical theory on pollutants diffusion still needs to be further improved.In this work,general analytical solutions are derived for one-dimensional diffusion of degradable organic contaminant(DOC)in the multi-layered media containing geomembranes under a time-varying concentration boundary condition,where the variable substitution and separated variable approaches are employed.These analytical solutions with clear expressions can be used not only to study the diffusion behaviors of DOC in bottom and vertical composite barrier systems,but also to verify other complex numerical models.The proposed general analytical solutions are then fully validated via three comparative analyses,including comparisons with the experimental measurements,an existing analytical solution,and a finite-difference solution.Ultimately,the influences of different factors on the composite cutoff wall’s(CCW,which consists of two soil-bentonite layers and a geomembrane)service performance are investigated through a composite vertical barrier system as the application example.The findings obtained from this investigation can provide scientific guidance for the barrier performance evaluation and the engineering design of CCWs.This application example also exhibits the necessity and effectiveness of the developed analytical solutions. 展开更多
关键词 general analytical solutions degradable organic contaminant diffusion behavior multi-layered media containing geomembranes composite barrier system
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Numerical Exploration on Load Transfer Characteristics and Optimization of Multi-Layer Composite Pavement Structures Based on Improved Transfer Matrix Method
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作者 Guo-Zhi Li Hua-Ping Wang +2 位作者 Si-Kai Wang Jing-Cheng Zhou Ping Xiang 《Computer Modeling in Engineering & Sciences》 2025年第12期3165-3195,共31页
Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanism... Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures. 展开更多
关键词 multi-layer composite pavement improved theoretical analysis transfer matrix method structural optimization damage prevention
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An improved model for predicting thermal contact resistance at multi-layered rock interface
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作者 WEN Min-jie XIE Jia-hao +4 位作者 LI Li-chen TIAN Yi EL NAGGAR M.Hesham MEI Guo-xiong WU Wen-bing 《Journal of Central South University》 2025年第1期229-243,共15页
This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi... This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient. 展开更多
关键词 multi-layered structures general thermal contact model thermal contact resistance GL thermoelastic theory Laplace transform
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Routing cost-integrated intelligent handover strategy for multi-layer LEO mega-constellation networks
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作者 Zhenglong YIN Quan CHEN +2 位作者 Lei YANG Yong ZHAO Xiaoqian CHEN 《Chinese Journal of Aeronautics》 2025年第6期487-500,共14页
Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed ... Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed satellites,ground users now can be covered by multiple visible satellites,but also face complex handover issues with such massive high-mobility satellites in multi-layer.The end-to-end routing is also affected by the handover behavior.In this paper,we propose an intelligent handover strategy dedicated to multi-layer LEO mega-constellation networks.Firstly,an analytic model is utilized to rapidly estimate the end-to-end propagation latency as a key handover factor to construct a multi-objective optimization model.Subsequently,an intelligent handover strategy is proposed by employing the Dueling Double Deep Q Network(D3QN)-based deep reinforcement learning algorithm for single-layer constellations.Moreover,an optimal crosslayer handover scheme is proposed by predicting the latency-jitter and minimizing the cross-layer overhead.Simulation results demonstrate the superior performance of the proposed method in the multi-layer LEO mega-constellation,showcasing reductions of up to 8.2%and 59.5%in end-to-end latency and jitter respectively,when compared to the existing handover strategies. 展开更多
关键词 multi-layer LEO mega-constellation networks HANDOVER Routing cost Dueling Double Deep Q Network(D3QN)
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Experimental investigation on dynamic stab resistance of highperformance multi-layer textile materials
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作者 Mulat Alubel Abtew François Boussu +1 位作者 Irina Cristian Bekinew Kitaw Dejene 《Defence Technology(防务技术)》 2025年第5期1-14,共14页
Stab-resistant textiles play a critical role in personal protection,necessitating a deeper understanding of how structural and layering factors influence their performance.The current study experimentally examines the... Stab-resistant textiles play a critical role in personal protection,necessitating a deeper understanding of how structural and layering factors influence their performance.The current study experimentally examines the effects of textile structure,layering,and ply orientation on the stab resistance of multi-layer textiles.Three 3D warp interlock(3DWI)structures({f1},{f2},{f3})and a 2D woven fabric({f4}),all made of high-performance p-aramid yarns,were engineered and manufactured.Multi-layer specimens were prepared and subjected to drop-weight stabbing tests following HOSBD standards.Stabbing performance metrics,including Depth of Trauma(DoT),Depth of Penetration(DoP),and trauma deformation(Ymax,Xmax),were investigated and analyzed.Statistical analyses(Two-and One-Way ANOVA)indicated that fabric type and layer number significantly impacted DoP(P<0.05),while ply orientation significantly affected DoP(P<0.05)but not DoT(P>0.05).Further detailed analysis revealed that 2D woven fabrics exhibited greater trauma deformation than 3D WIF structures.Increasing the number of layers reduced both DoP and DoT across all fabric structures,with f3 demonstrating the best performance in multi-layer configurations.Aligned ply orientations also enhanced stab resistance,underscoring the importance of alignment in dissipating impact energy. 展开更多
关键词 2D/3D woven fabrics High-performance fibers Protective textiles multi-layer panels Impact ply orientation Dynamic stab resistance
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CMFDE和MSIDBO-SVM在滚动轴承故障诊断中的应用
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作者 李佰霖 张政 +2 位作者 唐淞 付文龙 孟凯悦 《重庆理工大学学报(自然科学)》 北大核心 2026年第2期105-111,共7页
针对滚动轴承故障特征信息提取困难导致故障诊断准确率较低的问题,提出基于复合多尺度模糊散布熵(CMFDE)和改进蜣螂优化算法(MSIDBO)优化支持向量机(SVM)的轴承故障诊断方法。针对蜣螂优化算法(DBO)种群多样性差易陷入局部最优,引入多... 针对滚动轴承故障特征信息提取困难导致故障诊断准确率较低的问题,提出基于复合多尺度模糊散布熵(CMFDE)和改进蜣螂优化算法(MSIDBO)优化支持向量机(SVM)的轴承故障诊断方法。针对蜣螂优化算法(DBO)种群多样性差易陷入局部最优,引入多种策略改进DBO算法。采用DBO对变分模态分解(VMD)进行参数优化,利用优化后的VMD将信号分解成多个本征模态分量(IMF),再根据综合指标筛选IMF。计算筛选后IMF的CMFDE值,并将其作为MSIDBO-SVM模型的输入向量。采用美国凯斯西储大学轴承数据集和SpectraQuest实验台轴承数据集进行验证,结果表明,MSIDBO-SVM模型准确率分别为98.89%和97.78%,验证了所提方法的有效性和泛化能力。 展开更多
关键词 熵权法-TOPSIS 复合多尺度模糊散布熵 改进蜣螂优化算法 支持向量机 故障诊断
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基于OneClass SVM的应用层CC攻击检测模型研究
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作者 胡鑫 张欣 张巧 《现代传输》 2026年第1期51-56,共6页
为了应对应用层CC攻击隐蔽性强、检测难度大的问题,本文提出了一种基于集成One-Class SVM模型的CC攻击检测方法。首先,从实际Web访问日志中提取多维特征,构建训练数据集,并采用特征子空间扰动、样本空间扰动及参数扰动等策略,提升子模... 为了应对应用层CC攻击隐蔽性强、检测难度大的问题,本文提出了一种基于集成One-Class SVM模型的CC攻击检测方法。首先,从实际Web访问日志中提取多维特征,构建训练数据集,并采用特征子空间扰动、样本空间扰动及参数扰动等策略,提升子模型的多样性和整体鲁棒性。随后,通过集成多个One-Class SVM子模型,形成综合判别机制,以提高检测准确率与降低误报率。实验结果表明,集成One-Class SVM模型在准确率、精确率、召回率、假正率及AUC等指标上均优于单一模型及传统方法,其中AUC值达到0.935。进一步通过消融实验验证了各模块对整体性能的贡献,充分证明了所提方法在应用层CC攻击检测中的有效性和实用性。 展开更多
关键词 OneClass svm 应用层 CC攻击检测
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基于改进SVM算法和滤波器的电能表电流采样电阻故障检测方法
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作者 张永旺 李健 +2 位作者 赵炳辉 张科 李嘉杰 《微电机》 2026年第2期51-55,76,共6页
为有效处理具有非线性、高维度特性数据,保证电能表电流采样电阻故障检测的可靠性,提出基于改进SVM算法和滤波器的电能表电流采样电阻故障检测方法。将关键的电流数据输入支持向量机故障预测模型中,利用该模型对非线性数据的强大处理能... 为有效处理具有非线性、高维度特性数据,保证电能表电流采样电阻故障检测的可靠性,提出基于改进SVM算法和滤波器的电能表电流采样电阻故障检测方法。将关键的电流数据输入支持向量机故障预测模型中,利用该模型对非线性数据的强大处理能力,检测电能表电流采样电阻故障;并引入变异算子迭代搜寻最优支持向量机故障预测函数的核函数,输出电能表电流采样电阻故障类型。实验结果表明,该方法能够有效保留电流采样数据关键信息,抑制噪声,更迅速搜寻到全局范围内核函数最优解,区分不同类型电阻故障。 展开更多
关键词 改进svm算法 滤波器 电能表 故障检测 变异算子
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基于TSO-LS-SVM模型的电煤库存风险评价研究
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作者 陈云峰 于雪 +2 位作者 刘吉成 马旭颖 朱玺瑞 《中国管理科学》 北大核心 2026年第2期164-175,共12页
为提高电煤企业库存风险评估的准确度和效率,本文提出一种金枪鱼群优化算法与最小二乘支持向量机(TSO-LS-SVM)的风险组合评价模型。首先,该方法利用金枪鱼群优化算法(tuna swarm optimization algorithm,TSO)实现了最小二乘法(least squ... 为提高电煤企业库存风险评估的准确度和效率,本文提出一种金枪鱼群优化算法与最小二乘支持向量机(TSO-LS-SVM)的风险组合评价模型。首先,该方法利用金枪鱼群优化算法(tuna swarm optimization algorithm,TSO)实现了最小二乘法(least squares,LS)和支持向量机模型(support vector machine,SVM)的参数设置优化。其次,通过算例分析验证了所提TSO-LS-SVM模型在电煤库存风险评价中的适用性。再次,通过对比金枪鱼群优化算法、鲸鱼优化算法(whale optimization algorithm,WOA)和粒子群优化算法(particle swarm optimization,PSO)验证了本文所提方法的优越性。结果显示,TSO-LS-SVM模型收敛速度快,准确率更高,均方误差更小,在电煤库存风险评价中表现最优。最后,通过灵敏性分析从煤炭损耗、政策机遇、设施建设、员工素养和信息传导5个角度提出了风险管控策略,为电煤企业提高库存风险管控水平提供了参考。 展开更多
关键词 电煤库存风险 风险评价 支持向量机 金枪鱼群优化算法
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基于改进VMD和SVM方法的滚动轴承故障诊断
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作者 何晓良 苏春 张玉茹 《东南大学学报(自然科学版)》 北大核心 2026年第2期322-332,共11页
为解决旋转部件早期振动故障信号存在的特征微弱、非平稳等问题,提出一种基于改进变分模态分解(VMD)及支持向量机(SVM)的故障诊断方法。采用改进的野马算法(IWHO)优化VMD中的惩罚因子α和模态数K以实现参数自动寻优,采用适应度函数选择... 为解决旋转部件早期振动故障信号存在的特征微弱、非平稳等问题,提出一种基于改进变分模态分解(VMD)及支持向量机(SVM)的故障诊断方法。采用改进的野马算法(IWHO)优化VMD中的惩罚因子α和模态数K以实现参数自动寻优,采用适应度函数选择最小包络熵。利用优化后的VMD完成振动信号分解,得到振动信号的固有模态函数(IMF)。在此基础上,采用峭度准则选取前5阶IMF分量以计算时频域特征,构建特征向量;将特征向量输入SVM中完成训练,实现旋转部件的故障分类。以滚动轴承试验数据集为例,验证方法有效性。结果表明:所提出的方法能有效处理非平稳振动信号,针对数据集中轴承4种运行状态诊断的准确率达99.17%;在模拟噪声干扰环境下,模型仍能保持95.8%以上的诊断精度。 展开更多
关键词 变分模态分解 支持向量机 改进野马算法 故障诊断
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