Robotic Systems and Applications
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Secure metric dimension of new classes of graphs
Get PDFThe metric representation of a vertex v of a graph G is a finite vector representing distances of v with respect to vertices of some ordered subset S⊆V (G). If no suitable subset of S provides separate representations for each vertex of V(G), then the set S is referred to as a minimal resolving set. The metric dimension of G is the cardinality of the smallest (with respect to its cardinality) minimal resolving set. A resolving set S is secure if for any v∈V–S, there exists x∈S such that (S–{x})∪{v} is a resolving set. For various classes of graphs, the value of the secure resolving number is determined and defined. The secure metric dimension of the graph classes is being studied in this work. The results show that different graph families have different metric dimensions
Mathematical simulation modeling analysis of sub-sea tunnel blasting based on grey correlation
Get PDFBlasting in the ocean tunnel has a great impact on Marine life and seabed vegetation, so it is necessary to control the impact of blasting vibration on the surrounding Marine environment. In this paper, taking Xiamen Tunnel as an example, the blasting vibration response characteristics of undersea tunnel are studied, and the velocity attenuation rules of tunnel structure in different directions are obtained. The grey correlation theory is innovatively applied to analyze the correlation degree of factors affecting the blasting vibration effect of the undersea tunnel, and the key factors and secondary factors affecting the blasting vibration effect of the tunnel are determined. The grey correlation theory is used to analyze the correlation degree between the blasting vibration effect of the cross-tunnel, which is conducive to improving the safety and stability of tunnel construction. It provides a new idea and method for vibration control of similar projects
Analysis of aerodynamic characteristics of drone wing based on CFD
Get PDFIn order to improve the aerodynamic characteristics of the drone wings, CFD method was used to simulate and calculate the lift coefficient, drag coefficient, and lift-drag ratio under different relative inflow velocities, as well as the velocity and pressure fields under different attack angles. Modal calculations were conducted on the wing to obtain the first four modal shapes, providing a basis for analyzing flutter characteristics. An iterative calculation method of incompressible potential flow-boundary layer based on surface element method was combined with the software XFOIL to optimize the airfoil at low wind speeds. The results indicate that the airfoil is susceptible to stall at high angles of attack, with the pressure of the separation flow being nearly equivalent to that at the separation point. Subsequent to separation, there is an increase in differential pressure resistance, resulting in a marked rise in the drag coefficient. At the optimized angle of attack, the lift-drag ratio of the optimized wing increases by 12.58 %, while there is a decrease of 0.084 % in lift coefficient and an increase of 11.21 % in drag coefficient
Demagnetization optimization of hybrid excitation eddy current damper under intensive impact load
Get PDFThe hybrid excitation eddy current damper is a novel principle damper characterized by high reliability, simple structure, and controllable magnetic field. Under intensive impact loads, hybrid excitation electromagnetic damping can induce demagnetization effects, resulting in significant fluctuations of the electromagnetic damping force at 6-8 ms. To mitigate this phenomenon, this study established a finite element model of the hybrid excitation damper using COMSOL and developed a control module based on a BP neural network in Simulink. Through co-simulation of COMSOL and Simulink, the difference between the maximum and minimum electromagnetic damping force at 6-8ms is reduced from 45 kN to 5 kN. This research provides valuable technical references for the optimization and practical application of eddy current dampers
Analysis and optimization of abnormal noise in lubricating oil circuit of diesel engine
Get PDFEngine abnormal noise is one of the common engine faults, which will affect the comfort, power and safety of the automobile at the same time. In order to study the abnormal noise existing in the test process of diesel engine lubricating oil circuit system, 1D numerical simulation analysis of its flow field is carried out by using simulation software GT-power to verify the boundary conditions of the model and analyze the fluctuation of pressure at different speeds and temperatures. Through numerical analysis, it is found that there is almost no pressure fluctuation in the lubrication system before the pressure limiting valve is opened, but after the pressure limiting valve is opened, pressure fluctuation occurs in the pipeline, and the pressure fluctuation is different at different positions. Finally, the lubrication pipeline is simulated and analyzed by Pumplinx software, and the pressure fluctuation in the lubrication pipeline of diesel engine is reduced by optimizing the diameter of the oil pipeline and increasing the cavity structure
Visual reconstruction method of architectural space under laser point cloud big data
Get PDFIn order to solve the problem that the reconstruction accuracy and integrity are affected due to the large amount of point cloud data in the process of building space reconstruction, the visual reconstruction method of building space under laser point cloud big data is studied. The three-dimensional laser scanner is used to collect the laser point cloud big data in the building space, and the laser point cloud big data is organized and processed through three steps: hierarchical calculation of the point cloud pyramid, thinning treatment and block treatment. From the processing results of laser point cloud big data, the line features of building space are extracted based on the improved Mean-shift method, and the continuous broken lines in the point cloud data of building space are extracted by using the double radius threshold line tracing method. According to the feature extraction results of point cloud data in building space, the visual reconstruction of building space is completed through the process of translation matching and space matching. The experimental results show that this method can realize the visual reconstruction of architectural space, and the average reconstruction accuracy is higher than that of 97 %, and the reconstruction completion and smoothness are higher than 95 %
Enhancing non-destructive testing in concrete structures: a GADF-CNN approach for defect detection
Get PDFThis research introduces a novel approach for detecting defects in concrete structures. It utilizes the Gramian Angular Difference Field (GADF) in combination with a Convolutional Neural Network (CNN) enhanced by depthwise separable convolutions and attention mechanisms. The key contribution of this work is the use of GADF to transform one-dimensional impact-echo signals into two-dimensional images, thereby improving feature extraction and computational efficiency for analysis by the CNN. This advancement offers a new perspective in non-destructive testing technologies for concrete infrastructure. Comprehensive evaluation on a varied dataset of concrete structural defects reveals that our GADF-CNN model achieves an impressive test accuracy of 98.24 %, surpassing conventional models like VGG16, ResNet18, DenseNet, and ResNeXt50, and excelling in precision, recall, and F1-score metrics. Ultimately, this study enhances the integration of sophisticated image transformation techniques with deep learning, contributing to safer and more durable concrete infrastructure, and represents a noteworthy development in the field
Dynamic pupillometry system
Get PDFThe phenomena of miosis (constriction) and mydriasis (dilation) of the pupil are exhibited in response to varying levels of light intensity cast upon the eye. In general, the size and responsiveness of the human pupil are under the regulatory purview of the nervous system. Consequently, the study of the pupil offers a means to discern potential abnormalities in the human organism, as it permits an assessment of the nervous system’s behavior. However, the comprehension of pupillary dynamics remains incomplete in certain facets, and methodologies for enhancing diagnostic precision continue to evolve, primarily contingent upon current technological equipment advancements. Thus, the imperative lies in the advancement of technologies that meet these research needs, as the scrutiny of pupillary responses holds the capability to detect anomalies within the human body. Hence, the objective of this endeavor is to conduct preliminary trials of a dynamic pupillometry system, designed to both stimulate and capture images of human pupils, facilitating an investigation into their behavioral patterns. The findings elucidate various pupillary parameters and reveal significant alterations in pupillary conduct, thereby contributing to the advancement of research and technologies within the realm of pupillometry. Thus, this study undertakes an innovative exploration into pupillometry, particularly regarding stimuli of varying wavelengths, thereby providing improvements on the diagnostic, prognostic and preventive capacity with heightened reliability, given the pupil’s size and its reactions cannot be manipulated or falsified since they are involuntary
Connected metric dimension of the class of ladder graphs
Get PDFNumerous applications, like robot navigation, network verification and discovery, geographical routing protocols, and combinatorial optimization, make use of the metric dimension and connected metric dimension of graphs. In this work, the connected metric dimension types of ladder graphs, namely, ladder, circular, open, and triangular ladder graphs, as well as open diagonal and slanting ladder graphs, are studied
Influence of Copper-Iron (CuFe) and Copper-Tin (CuSN) alloys over mechanical strength properties in crimping process
Get PDFThis study investigates the comparative performance of Copper-Iron (CuFe) and Copper-Tin (CuSn) alloys in crimping processes, with a focus on their mechanical, electrical, and corrosion-resistance properties. Crimping is a critical method for creating reliable electrical and mechanical connections, particularly in environments subjected to significant mechanical stress and varying temperatures [1]. CuFe alloys, known for their superior mechanical strength and hardness, present challenges in crimping due to their increased resistivity and reduced ductility. Conversely, CuSn alloys offer a balance between electrical conductivity, ease of crimping, and corrosion resistance, making them a preferred choice in many industrial applications. This research aims to provide a comprehensive analysis of how the distinct properties of CuFe and CuSn alloys influence the crimping process, ultimately guiding material selection for optimized performance in various applications [2]. Experimental data will be drawn from tensile strength tests, electrical resistance measurements, and corrosion tests, providing a holistic understanding of the advantages and limitations of each alloy