• Journal of Mechanical Science and Technology
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• v.20 no.11
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• pp.1781-1789
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• 2006

Fourier methods are not generally an appropriate approach in the investigation of faults signals with transient components. This work presents the application of a new signal processing technique, the Hilbert-Huang transform and its marginal spectrum, in analysis of vibration signals and faults diagnosis of gear. The Empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) and marginal spectrum are introduced. Firstly, the vibration signals are separated into several intrinsic mode functions (IMFs) using EMD. Then the marginal spectrum of each IMF can be obtained. According to the marginal spectrum, the wear fault of the gear can be detected and faults patterns can be identified. The results show that the proposed method may provide not only an increase in the spectral resolution but also reliability for the faults diagnosis of the gear.

• Structural Engineering and Mechanics
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• v.23 no.2
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• pp.163-175
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• 2006

In this paper, the dynamic response of a piezoelectric layer with a penny-shaped crack is investigated. The piezoelectric layer is subjected to an axisymmetrical action of both mechanical and electrical impacts. Two kinds of crack surface conditions, i.e., electrically impermeable and electrically permeable, are adopted. Based upon integral transform technique, the crack boundary value problem is reduced to a system of Fredholm integral equations in the Laplace transform domain. By making use of numerical Laplace inversion the time-dependent dynamic stress and electric displacement intensity factors are obtained, and the dynamic energy release rate is further derived. Numerical results are plotted to show the effects of both the piezoelectric layer thickness and the electrical impact loadings on the dynamic fracture behaviors of the crack tips.

• Bulletin of the Korean Mathematical Society
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• v.40 no.3
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• pp.351-363
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• 2003

In the present paper, some general convergence principles are established in metric spaces and then theses principles are applied to the convergence of the iterative sequences for approximating fixed points of certain classes of mappings. By virtue of our principles, most of the latest results obtained by several authors can be deduced easily.

• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1089-1099
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• 2010

An SIR epidemic model with pulse vaccination and time delay describing infection period is investigated. The global attractiveness of the infection-free periodic solution is discussed, and sufficient condition is obtained for the permanence of the system. Our results indicate that a large vaccination rate or a short period of pulsing leads to the eradication of the disease.

• Structural Monitoring and Maintenance
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• v.5 no.1
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• pp.67-78
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• 2018

The stability of cutting slope influences the safety of railway operation, and how to identify the stability of the slope quickly and determine the rational monitoring plan is a pressing problem at present. In this study, the attribute recognition model of risk assessment for high cutting slope stability in the heavy haul railway is established based on attribute mathematics theory, followed by the consequent monitoring scheme design. Firstly, based on comprehensive analysis on the risk factors of heavy haul railway loess slope, collapsibility, tectonic feature, slope shape, rainfall, vegetation conditions, train speed are selected as the indexes of the risk assessment, and the grading criteria of each index is established. Meanwhile, the weights of the assessment indexes are determined by AHP judgment matrix. Secondly, The attribute measurement functions are given to compute attribute measurement of single index and synthetic attribute, and the attribute recognition model was used to assess the risk of a typical heavy haul railway loess slope, Finally, according to the risk assessment results, the monitoring content and method of this loess slope were determined to avoid geological disasters and ensure the security of the railway infrastructure. This attribute identification- risk assessment- monitoring design mode could provide an effective way for the risk assessment and control of heavy haul railway in the loess plateau.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4682-4705
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• 2020

The Unmanned Aerial Vehicles (UAV) networks consisting of low-cost UAVs are very vulnerable to smart jammers that can choose their jamming policies based on the ongoing communication policies accordingly. In this article, we propose a novel cloud and edge-aided mobile communication scheme for low-cost UAV network against smart jamming. The challenge of this problem is to design a communication scheme that not only meets the requirements of defending against smart jamming attack, but also can be deployed on low-cost UAV platforms. In addition, related studies neglect the problem of decision-making algorithm failure caused by intermittent ground-to-air communication. In this scheme, we use the policy network deployed on the cloud and edge servers to generate an emergency policy tables, and regularly update the generated policy table to the UAVs to solve the decision-making problem when communications are interrupted. In the operation of this communication scheme, UAVs need to offload massive computing tasks to the cloud or the edge servers. In order to prevent these computing tasks from being offloaded to a single computing resource, we deployed a lightweight game algorithm to ensure that the three types of computing resources, namely local, edge and cloud, can maximize their effectiveness. The simulation results show that our communication scheme has only a small decrease in the SINR of UAVs network in the case of momentary communication interruption, and the SINR performance of our algorithm is higher than that of the original Q-learning algorithm.

• Wind and Structures
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• v.37 no.1
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• pp.25-38
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• 2023

Due to the complexity and difficulty in meeting the multiphase flow complexity, similarity, and multiscale characteristics, the mechanism of snow drift is so complicated that the snow deposition prediction is still inaccurate and needs to be far improved. Meanwhile, the validation of prediction methods is also limited due to a lack of field-measured data about snow deposition. To this end, a field measurement activity about snow deposition around a cube with time was carried out, and the snow accumulation process was measured under blowing snow conditions in northwest China. The maximum snow depth, snow profile, and variation in snow depth around the cube were discussed and analyzed. The measured results indicated three stages of snow accumulation around the cube. First, snow is deposited in windward, lateral and leeward regions, and then the snow depth in windward and lateral regions increases. Secondly, when the snow in the windward region reaches its maximum, the downwash flow erodes the snow against the front wall. Meanwhile, snow range and depth in lateral regions have a significant increase. Thirdly, a narrow road in the leeward region is formed with the increase in snow range and depth, which results in higher wind speed and reforming snow deposition there. The field measurement study in this paper not only furthers understanding of the snow accumulation process instead of final deposition under complex conditions but also provides an important benchmark for validating prediction methods.

• Wind and Structures
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• v.36 no.3
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• pp.175-200
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• 2023

The large eddy simulation (LES) of the flow around a circular cylinder is not only affected by the sub-grid scale (SGS) model but also by the grid resolution of the computational domain. To study the influence of different grids on the LES results, the LES simulations of the flow around a circular cylinder with different grids at Reynolds number (Re) = 3900 was performed. A circular computational domain with different radial growth rates and circumferential and spanwise grid numbers was adopted for the simulations. Meanwhile, the aerodynamic forces, wind pressure coefficients, mean and instantaneous flow fields, and the effect of grid resolution on them were comprehensively analyzed. The results indicate that the lift coefficient, wind pressure coefficient, and recirculation length are significantly affected by the radial growth rate of the grid and the circumferential grid number. The spanwise grid number has a significant influence on the three-dimensionality of the flow and plays an important role in velocity fluctuations in the wake region. Nevertheless, the aerodynamic coefficients and recirculation length are not sufficiently sensitive to the grid number in the spanwise direction. By comparing the results, it can be concluded that suitable and reliable LES results can be obtained when the radial growth rate is 1.03 or 1.05, the circumferential grid number is 160, 200, or 240, and the spanwise grid number is 64. A radial growth rate 1.05, circumferential grid number 160, and spanwise grid number 64 are recommended to reduce the grid amount and further improve the efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5631-5652
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• 2019

The existing defense strategy selection methods based on game theory basically select the optimal defense strategy in the form of mixed strategy. However, it is hard for network managers to understand and implement the defense strategy in this way. To address this problem, we constructed the incomplete information stochastic game model for the dynamic analysis to predict multi-stage attack-defense process by combining Bayesian game theory and the Markov decision-making method. In addition, the payoffs are quantified from the impact value of attack-defense actions. Based on previous statements, we designed an optimal defense strategy selection method. The optimal defense strategy is selected, which regards defense effectiveness as the criterion. The proposed method is feasibly verified via a representative experiment. Compared to the classical strategy selection methods based on the game theory, the proposed method can select the optimal strategy of the multi-stage attack-defense process in the form of pure strategy, which has been proved more operable than the compared ones.

• Computers and Concrete
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• v.17 no.5
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• pp.613-628
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• 2016

In this study, the influence of coarse aggregate size and type on chloride penetration of concrete was investigated, and the grey correlation analysis was applied to find the key influencing factor. Furthermore, the proposed 6-10-1 artificial neural network (ANN) model was constructed, and performed under the MATLAB program. Training, testing and validation of the model stages were performed using 81 experiment data sets. The results show that the aggregate type has less effect on the concrete permeability, compared with the size effect. For concrete with a lower w/b, the coarse aggregate with a larger particle size should be chose, however, for concrete with a higher w/c, the aggregate with a grading of 5-20 mm is preferred, too large or too small aggregates are adverse to concrete chloride diffusivity. A new idea for the optimum selection of aggregate to prepare concrete with a low penetration is provided. Moreover, the ANN model predicted values are compared with actual test results, and the average relative error of prediction is found to be 5.62%. ANN procedure provides guidelines to select appropriate coarse aggregate for required chloride penetration of concrete and will reduce number of trial and error, save cost and time.