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The Use of IoT for Determination of Time and Frequency Vibration Characteristics of Industrial Equipment for Condition-Based Maintenance 使用物联网确定基于状态维护的工业设备的时间和频率振动特性
IF 2.2 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-09-05 DOI: 10.3390/computation11090177
Ihor Turkin, Viacheslav Leznovskyi, Andrii Zelenkov, Agil Nabizade, Lina Volobuieva, Viktoriia Turkina
The subject of study in this article is a method for industrial equipment vibration diagnostics that uses discrete Fourier transform and Allan variance to increase precision and accuracy of industrial equipment vibration diagnostics processes. We propose IoT-oriented solutions based on smart sensors. The primary objectives include validating the practicality of employing platform-oriented technologies for vibro-diagnostics of industrial equipment, creating software and hardware solutions for the IoT platform, and assessing measurement accuracy and precision through the analysis of measurement results in both time and frequency domains. The IoT system architecture for industrial equipment vibration diagnostics consists of three levels. At the autonomous sensor level, vibration acceleration indicators are obtained and transmitted via a BLE digital wireless data transmission channel to the second level, the hub, which is based on a BeagleBone single-board microcomputer. The computing power of BeagleBone is sufficient to work with artificial intelligence algorithms. At the third level of the server platform, the tasks of diagnosing and predicting the state of the equipment are solved, for which the Dictionary Learning algorithm implemented in the Python programming language is used. The verification of the accuracy and precision of the vibration diagnostics system was carried out on the developed stand. A comparison of the expected and measured results in the frequency and time domains confirms the correct operation of the entire system.
本文研究的是一种利用离散傅里叶变换和Allan方差来提高工业设备振动诊断过程的精度和准确性的工业设备振动诊断方法。我们提出基于智能传感器的面向物联网的解决方案。主要目标包括验证采用面向平台的技术进行工业设备振动诊断的可行性,为物联网平台创建软件和硬件解决方案,并通过分析时域和频域的测量结果来评估测量准确度和精度。工业设备振动诊断的物联网系统架构分为三个层次。在自主传感器层面,获得振动加速度指标,并通过BLE数字无线数据传输通道传输到基于BeagleBone单板微型计算机的第二层集线器。BeagleBone的计算能力足以与人工智能算法一起工作。在服务器平台的第三层,解决了设备状态的诊断和预测任务,使用Python编程语言实现字典学习算法。在研制的机架上对振动诊断系统的精度和精度进行了验证。在频域和时域上对预期结果和实测结果进行比较,证实了整个系统的正确运行。
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引用次数: 0
Filter Pruning with Convolutional Approximation Small Model Framework 卷积逼近小模型框架下的滤波器修剪
IF 2.2 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-09-05 DOI: 10.3390/computation11090176
Monthon Intraraprasit, O. Chitsobhuk
Convolutional neural networks (CNNs) are extensively utilized in computer vision; however, they pose challenges in terms of computational time and storage requirements. To address this issue, one well-known approach is filter pruning. However, fine-tuning pruned models necessitates substantial computing power and a large retraining dataset. To restore model performance after pruning each layer, we propose the Convolutional Approximation Small Model (CASM) framework. CASM involves training a compact model with the remaining kernels and optimizing their weights to restore feature maps that resemble the original kernels. This method requires less complexity and fewer training samples compared to basic fine-tuning. We evaluate the performance of CASM on the CIFAR-10 and ImageNet datasets using VGG-16 and ResNet-50 models. The experimental results demonstrate that CASM surpasses the basic fine-tuning framework in terms of time acceleration (3.3× faster), requiring a smaller dataset for performance recovery after pruning, and achieving enhanced accuracy.
卷积神经网络(cnn)在计算机视觉中得到了广泛的应用;然而,它们在计算时间和存储需求方面提出了挑战。为了解决这个问题,一个众所周知的方法是过滤器修剪。然而,微调修剪模型需要大量的计算能力和大量的再训练数据集。为了在修剪每一层后恢复模型的性能,我们提出了卷积逼近小模型(CASM)框架。CASM包括用剩余的核训练一个紧凑的模型,并优化它们的权重,以恢复与原始核相似的特征映射。与基本的微调相比,该方法需要更少的复杂性和更少的训练样本。我们使用VGG-16和ResNet-50模型评估了CASM在CIFAR-10和ImageNet数据集上的性能。实验结果表明,CASM在时间加速方面优于基本的微调框架(快3.3倍),需要更小的数据集进行修剪后的性能恢复,并且实现了更高的精度。
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引用次数: 0
An Image Encryption Scheme Combining 2D Cascaded Logistic Map and Permutation-Substitution Operations 一种结合二维级联Logistic映射和置换置换运算的图像加密方案
IF 2.2 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-09-05 DOI: 10.3390/computation11090178
D. Setiadi, Nova Rijati
Confusion, diffusion, and encryption keys affect the quality of image encryption. This research proposes combining bit- and pixel-level permutation and substitution methods based on three advanced chaotic logistic map methods. The three chaotic methods are the 2D Logistic-adjusted-Sine map (2D-LASM), the 2D Logistic-sine-coupling map (2D-LSCM), and the 2D Logistic ICMIC cascade map (2D-LICM). The encryption method’s design consists of six stages of encryption, involving permutation operations based on chaotic order, substitution based on modulus and bitXOR, and hash functions. Hash functions are employed to enhance key space and key sensitivity quality. Several testing tools are utilized to assess encryption performance, including histogram and chi-square analysis, information entropy, correlation of adjacent pixels, differential analysis, key sensitivity and key space analysis, data loss and noise attacks, NIST randomness tests, and TestU01. Compared to using a single 2D logistic map, the amalgamation of bit-level and pixel-level encryption and the utilization of three 2D cascade logistic maps has improved encryption security performance. This method successfully passes the NIST, TestU01, and chi-square tests. Furthermore, it outperforms the previous method regarding correlation, information entropy, NPCR, and UACI tests.
混淆、扩散和加密密钥会影响图像加密的质量。本研究在三种先进的混沌逻辑图方法的基础上,提出了结合比特和像素级排列和替换方法。这三种混沌方法分别是二维逻辑调整正弦映射(2D-LASM)、二维逻辑正弦耦合映射(2D_LSCM)和二维逻辑ICMIC级联映射(2D-LICM)。加密方法的设计包括六个加密阶段,包括基于混沌顺序的置换运算、基于模数和位XOR的替换以及哈希函数。采用哈希函数来增强密钥空间和密钥敏感度质量。使用多种测试工具来评估加密性能,包括直方图和卡方分析、信息熵、相邻像素的相关性、差分分析、密钥敏感性和密钥空间分析、数据丢失和噪声攻击、NIST随机性测试和TestU01。与使用单个2D逻辑图相比,比特级和像素级加密的融合以及三个2D级联逻辑图的使用提高了加密安全性能。该方法成功通过了NIST、TestU01和卡方测试。此外,它在相关性、信息熵、NPCR和UACI测试方面优于以前的方法。
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引用次数: 2
Knowledge Graph Engineering Based on Semantic Annotation of Tables 基于表语义标注的知识图工程
IF 2.2 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-09-05 DOI: 10.3390/computation11090175
N. Dorodnykh, A. Yurin
A table is a convenient way to store, structure, and present data. Tables are an attractive knowledge source in various applications, including knowledge graph engineering. However, a lack of understanding of the semantic structure and meaning of their content may reduce the effectiveness of this process. Hence, the restoration of tabular semantics and the development of knowledge graphs based on semantically annotated tabular data are highly relevant tasks that have attracted a lot of attention in recent years. We propose a hybrid approach using heuristics and machine learning methods for the semantic annotation of relational tabular data and knowledge graph populations with specific entities extracted from the annotated tables. This paper discusses the main stages of the approach, its implementation, and performance testing. We also consider three case studies for the development of domain-specific knowledge graphs in the fields of industrial safety inspection, labor market analysis, and university activities. The evaluation results revealed that the application of our approach can be considered the initial stage for the rapid filling of domain-specific knowledge graphs based on tabular data.
表是存储、构造和显示数据的一种方便方式。在各种应用程序中,表是一个有吸引力的知识源,包括知识图工程。然而,对其内容的语义结构和含义缺乏理解可能会降低这一过程的有效性。因此,恢复表格语义和基于语义注释的表格数据开发知识图是近年来备受关注的高度相关的任务。我们提出了一种使用启发式和机器学习方法的混合方法,用于从注释表中提取特定实体的关系表数据和知识图群体的语义注释。本文讨论了该方法的主要阶段、实现和性能测试。我们还考虑了在工业安全检查、劳动力市场分析和大学活动领域开发特定领域知识图的三个案例研究。评估结果表明,我们的方法的应用可以被视为基于表格数据快速填充特定领域知识图的初始阶段。
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引用次数: 0
AFB-GPSR: Adaptive Beaconing Strategy Based on Fuzzy Logic Scheme for Geographical Routing in a Mobile Ad Hoc Network (MANET) AFB-GPSR:基于模糊逻辑的移动自组网地理路由自适应信标策略
IF 2.2 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-09-04 DOI: 10.3390/computation11090174
Raneen I. Al-Essa, G. Al-Suhail
In mobile ad hoc networks (MANETs), geographical routing provides a robust and scalable solution for the randomly distributed and unrestricted movement of nodes. Each node broadcasts beacon packets periodically to exchange its position with neighboring nodes. However, reliable beacons can negatively affect routing performance in dynamic environments, particularly when there is a sudden and rapid change in the nodes’ mobility. Therefore, this paper suggests an improved Greedy Perimeter Stateless Routing Protocol, namely AFB-GPSR, to reduce routing overhead and increase network reliability by maintaining correct route selection. To this end, an adaptive beaconing strategy based on a fuzzy logic scheme (AFB) is utilized to choose more optimal routes for data forwarding. Instead of constant periodic beaconing, the AFB strategy can dynamically adjust beacon interval time with the variation of three network parameters: node speed, one-hop neighbors’ density, and link quality of nodes. The routing evaluation of the proposed protocol is carried out using OMNeT++ simulation experiments. The results show that the AFB strategy within the GPSR protocol can effectively reduce the routing overhead and improve the packet-delivery ratio, throughput, average end-to-end delay, and normalized routing load as compared to traditional routing protocols (AODV and GPSR with fixed beaconing). An enhancement of the packet-delivery ratio of up to 14% is achieved, and the routing cost is reduced by 35%. Moreover, the AFB-GPSR protocol exhibits good performance versus the state-of-the-art protocols in MANET.
在移动自组织网络(manet)中,地理路由为节点的随机分布和不受限制的移动提供了一种鲁棒性和可扩展性的解决方案。每个节点定期广播信标包,以便与相邻节点交换自己的位置。然而,在动态环境中,可靠的信标可能会对路由性能产生负面影响,特别是当节点的移动性发生突然而快速的变化时。因此,本文提出了一种改进的贪婪周边无状态路由协议,即AFB-GPSR,通过保持正确的路由选择来减少路由开销,提高网络可靠性。为此,采用一种基于模糊逻辑方案(AFB)的自适应信标策略来选择更优的路由进行数据转发。AFB策略可以根据节点速度、一跳邻居密度和节点链路质量三个网络参数的变化动态调整信标间隔时间,而不是固定的周期性信标。利用omnet++进行了路由评估仿真实验。结果表明,与传统路由协议(AODV和固定信标的GPSR)相比,GPSR协议中的AFB策略可以有效降低路由开销,提高分组投递率、吞吐量、平均端到端延迟和归一化路由负载。数据包的发送率提高了14%,路由成本降低了35%。此外,与MANET中最先进的协议相比,AFB-GPSR协议表现出良好的性能。
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引用次数: 2
MPC Controllers in SIIR Epidemic Models SIIR流行病模型中的MPC控制器
IF 2.2 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-09-04 DOI: 10.3390/computation11090173
Nikita Kosyanov, E. Gubar, Vladislav Taynitskiy
Infectious diseases are one of the most important problems of the modern world, for example, the periodic outbreaks of coronavirus infections caused by COVID-19, influenza, and many other respiratory diseases have significantly affected the economics of many countries. Hence, it is therefore important to minimize the economic damage, which includes both loss of work and treatment costs, quarantine costs, etc. Recent studies have presented many different models describing the dynamics of virus spread, which help to analyze the epidemic outbreaks. In the current work we focus on finding solutions that are robust to noise and take into account the dynamics of future changes in the process. We extend previous results by using a nonlinear model-predictive-control (MPC) controller to find effective controls. MPC is a computational mathematical method used in dynamically controlled systems with observations to find effective controls.
传染病是现代世界最重要的问题之一,例如,由COVID-19、流感和许多其他呼吸道疾病引起的冠状病毒感染的周期性爆发严重影响了许多国家的经济。因此,必须尽量减少经济损失,其中包括工作损失和治疗费用、隔离费用等。最近的研究提出了许多描述病毒传播动力学的不同模型,这些模型有助于分析流行病的爆发。在目前的工作中,我们专注于寻找对噪声具有鲁棒性的解决方案,并考虑到过程中未来变化的动态。我们通过使用非线性模型预测控制(MPC)控制器来扩展先前的结果,以找到有效的控制。MPC是一种用于具有观测值的动态控制系统的计算数学方法,用于寻找有效的控制。
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引用次数: 0
Predicting the Occurrence of Metabolic Syndrome Using Machine Learning Models 使用机器学习模型预测代谢综合征的发生
IF 2.2 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-09-03 DOI: 10.3390/computation11090170
M. Trigka, Elias Dritsas
The term metabolic syndrome describes the clinical coexistence of pathological disorders that can lead to the development of cardiovascular disease and diabetes in the long term, which is why it is now considered an initial stage of the above clinical entities. Metabolic syndrome (MetSyn) is closely associated with increased body weight, obesity, and a sedentary lifestyle. The necessity of prevention and early diagnosis is imperative. In this research article, we experiment with various supervised machine learning (ML) models to predict the risk of developing MetSyn. In addition, the predictive ability and accuracy of the models using the synthetic minority oversampling technique (SMOTE) are illustrated. The evaluation of the ML models highlights the superiority of the stacking ensemble algorithm compared to other algorithms, achieving an accuracy of 89.35%; precision, recall, and F1 score values of 0.898; and an area under the curve (AUC) value of 0.965 using the SMOTE with 10-fold cross-validation.
代谢综合征一词描述了长期可能导致心血管疾病和糖尿病发展的病理性疾病的临床共存,这就是为什么它现在被认为是上述临床实体的初始阶段。代谢综合征(MetSyn)与体重增加、肥胖和久坐不动的生活方式密切相关。预防和早期诊断的必要性势在必行。在这篇研究文章中,我们对各种监督机器学习(ML)模型进行了实验,以预测开发MetSyn的风险。此外,还说明了使用合成少数过采样技术(SMOTE)的模型的预测能力和准确性。对ML模型的评估突出了堆叠集成算法与其他算法相比的优越性,实现了89.35%的准确率;精确度、召回率和F1得分值为0.898;使用具有10倍交叉验证的SMOTE,曲线下面积(AUC)值为0.965。
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引用次数: 0
Intelligent Monitoring System to Assess Plant Development State Based on Computer Vision in Viticulture 基于计算机视觉的葡萄栽培植物发育状态智能监测系统
IF 2.2 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-09-03 DOI: 10.3390/computation11090171
Marina Rudenko, A. Kazak, N. Oleinikov, Angela N. Mayorova, Anna Dorofeeva, Dmitry Nekhaychuk, Olga Shutova
Plant health plays an important role in influencing agricultural yields and poor plant health can lead to significant economic losses. Grapes are an important and widely cultivated plant, especially in the southern regions of Russia. Grapes are subject to a number of diseases that require timely diagnosis and treatment. Incorrect identification of diseases can lead to large crop losses. A neural network deep learning dataset of 4845 grape disease images was created. Eight categories of common grape diseases typical of the Black Sea region were studied: Mildew, Oidium, Anthracnose, Esca, Gray rot, Black rot, White rot, and bacterial cancer of grapes. In addition, a set of healthy plants was included. In this paper, a new selective search algorithm for monitoring the state of plant development based on computer vision in viticulture, based on YOLOv5, was considered. The most difficult part of object detection is object localization. As a result, the fast and accurate detection of grape health status was realized. The test results showed that the accuracy was 97.5%, with a model size of 14.85 MB. An analysis of existing publications and patents found using the search “Computer vision in viticulture” showed that this technology is original and promising. The developed software package implements the best approaches to the control system in viticulture using computer vision technologies. A mobile application was developed for practical use by the farmer. The developed software and hardware complex can be installed in any vehicle. Such a mobile system will allow for real-time monitoring of the state of the vineyards and will display it on a map. The novelty of this study lies in the integration of software and hardware. Decision support system software can be adapted to solve other similar problems. The software product commercialization plan is focused on the automation and robotization of agriculture, and will form the basis for adding the next set of similar software.
植物健康在影响农业产量方面发挥着重要作用,植物健康状况不佳可能导致重大经济损失。葡萄是一种重要的广泛种植的植物,特别是在俄罗斯南部地区。葡萄易患多种疾病,需要及时诊断和治疗。对病害的错误识别可能导致巨大的作物损失。建立了4845张葡萄病害图像的神经网络深度学习数据集。研究了黑海地区常见的葡萄病害8大类:霉病、黄斑病、炭疽病、Esca、灰腐病、黑腐病、白腐病和葡萄细菌性癌病。此外,还包括一组健康植物。本文提出了一种基于YOLOv5的基于计算机视觉的葡萄栽培植物生长状态监测的选择性搜索算法。目标检测中最困难的部分是目标定位。实现了葡萄健康状况的快速、准确检测。测试结果表明,准确率为97.5%,模型大小为14.85 MB。通过搜索“葡萄栽培中的计算机视觉”对现有出版物和专利进行分析,表明该技术具有独创性和前景。开发的软件包实现了使用计算机视觉技术的葡萄栽培控制系统的最佳途径。为农民实际使用开发了一个移动应用程序。开发的软件和硬件综合体可以安装在任何车辆上。这样一个移动系统将允许对葡萄园的状态进行实时监控,并将其显示在地图上。本研究的新颖之处在于软硬件的集成。决策支持系统软件可以用于解决其他类似问题。软件产品商业化计划的重点是农业的自动化和机器人化,并将成为增加下一套类似软件的基础。
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引用次数: 0
Solving the Problem of Elasticity for a Layer with N Cylindrical Embedded Supports 求解N个圆柱形内嵌支承层的弹性问题
IF 2.2 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-09-03 DOI: 10.3390/computation11090172
V. Miroshnikov, Oleksandr B. Savin, Vladimir Sobol, Vyacheslav Nikichanov
The main goal of deformable solid mechanics is to determine the stress–strain state of parts, structural elements, and their connections. The most accurate results of calculations of this state allow us to optimize design objects. However, not all models can be solved using exact methods. One such model is the problem of a layer with cylindrical embedded supports that are parallel to each other and the layer boundaries. In this work, the supports are represented by cylindrical cavities with zero displacements set on them. The layer is considered in Cartesian coordinates, and the cavities are in cylindrical coordinates. To solve the problem, the Lamé equation is used, where the basic solutions between different coordinate systems are linked using the generalized Fourier method. By satisfying the boundary conditions and linking different coordinate systems, a system of infinite linear algebraic equations is created. For numerical realization, the method of reduction is used to find the unknowns. The numerical analysis has shown that the boundary conditions are fulfilled with high accuracy, and the physical pattern of the stress distribution and the comparison with results of similar studies indicate the accuracy of the obtained results. The proposed method for calculating the stress–strain state can be applied to the calculation of structures whose model is a layer with cylindrical embedded supports. The numerical results of the work make it possible to predetermine the geometric parameters of the model to be designed.
可变形固体力学的主要目标是确定零件、结构元件及其连接的应力-应变状态。这种状态的最精确的计算结果使我们能够优化设计对象。然而,并不是所有的模型都能用精确的方法求解。其中一个这样的模型是具有相互平行的圆柱形嵌入式支撑和层边界的层的问题。在这项工作中,支撑由圆柱形空腔表示,其上设置了零位移。层在笛卡尔坐标系中考虑,空腔在柱坐标系中考虑。为了解决这个问题,我们使用了lam方程,其中不同坐标系之间的基本解用广义傅里叶方法联系起来。通过满足边界条件和连接不同的坐标系,建立了一个无限线性代数方程组。在数值实现中,采用约简法寻找未知量。数值分析表明,边界条件满足精度较高,应力分布的物理规律以及与同类研究结果的比较表明所得结果的准确性。本文提出的应力-应变状态计算方法可应用于具有柱状预埋支撑层的结构模型的计算。计算结果为预先确定待设计模型的几何参数提供了可能。
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引用次数: 0
Impact of Cross-Tie Material Nonlinearity on the Dynamic Behavior of Shallow Flexible Cable Networks 交叉连接材料非线性对浅层柔性电缆网络动力特性的影响
IF 2.2 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-09-01 DOI: 10.3390/computation11090169
Amir Younespour, Shaohong Cheng
Cross-ties have proven their efficacy in mitigating vibrations in bridge stay cables. Several factors, such as cross-tie malfunctions due to slackening or snapping, as well as the utilization of high-energy dissipative materials, can introduce nonlinear restoring forces in the cross-ties. While previous studies have investigated the influence of the former on cable network dynamics, the evaluation of the impact of nonlinear cross-tie materials remains unexplored. In this current research, an existing analytical model of a two-shallow-flexible-cable network has been extended to incorporate the cross-tie material nonlinearity in the formulation. The harmonic balance method (HBM) is employed to determine the equivalent linear stiffness of the cross-ties. The dynamic response of a cable network containing nonlinear cross-ties is approximated by comparing it to an equivalent linear system. Additionally, the study delves into the effects of the cable vibration amplitude, cross-tie material properties, installation location, and the length ratio between constituent cables on both the fundamental frequency of the cable network and the equivalent linear stiffness of the cross-ties. The findings reveal that the presence of cross-tie nonlinearity significantly influences the in-plane modal response of the cable network. Not only the frequencies of all the modes are reduced, but the formation of local modes is delayed to a high order. In contrast to an earlier finding based on a linear cross-tie assumption, with nonlinearity present, moving a cross-tie towards the mid-span of a cable would not enhance the in-plane stiffness of the network. Moreover, the impact of the length ratio on the network in-plane stiffness and frequency is contingent on its combined effect on the cross-tie axial stiffness and the lateral stiffness of neighboring cables.
枕木已证明其在减轻桥梁斜拉索振动方面的有效性。一些因素,如由于松弛或断裂导致的横拉杆故障,以及高能耗散材料的使用,都会在横拉杆中引入非线性恢复力。虽然先前的研究已经调查了前者对电缆网络动力学的影响,但对非线性交叉连接材料影响的评估仍有待探索。在目前的研究中,对现有的两层柔性电缆网络的分析模型进行了扩展,在公式中加入了交叉连接材料的非线性。采用谐波平衡法确定了横拉杆的等效线刚度。通过将含有非线性横拉杆的电缆网络与等效线性系统进行比较,来近似其动态响应。此外,该研究还深入探讨了电缆振幅、横拉杆材料特性、安装位置和组成电缆之间的长度比对电缆网络基频和横拉杆等效线性刚度的影响。研究结果表明,交叉连接非线性的存在显著影响了电缆网络的平面内模态响应。不仅降低了所有模式的频率,而且将局部模式的形成延迟到高阶。与早期基于线性横拉杆假设的发现相反,在存在非线性的情况下,将横拉杆移向电缆的中跨不会增强网络的平面内刚度。此外,长度比对网络平面内刚度和频率的影响取决于其对交叉连接轴向刚度和相邻电缆横向刚度的综合影响。
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引用次数: 0
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Computation
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