In this paper, a type of planetary gear system in the wind turbine was studied by taking into account the actual conditions where the planetary gear system works. A nonlinear multi-gap planetary gear system finite element method model was established, and the engagement stress, the displacement, and the velocity curve with time of nodes of the planetary gear system were obtained by using explicit dynamic solution method. Under different speeds and different load, the variation of planetary gear system dynamic transmission error was then studied combined with the theory of gearing. The results showed that it is different from the dynamic transmission error of planetary gear system and planetary gear. Time-varying mesh stiffness of sun gear and the ring gear are also different along with their speed change. There are some correlation among time-varying mesh stiffness, meshing impact stress, and dynamic transmission errors. Therefore, it is suggested that the meshing stiffness and impact stress effect on the dynamic transmission error should be considered in the study of transmission error of wind turbine planetary gear system.
Transmission tower plays important role in the power system and it is security sensitive in various working conditions, such as wind and ice. In this paper, a method to obtain the dynamic response of a cat head type transmission tower under strong fluctuating wind was proposed. The coupled tower-lines finite element model was established in ABAQUS, and the equivalent acceleration of fluctuating wind was simulated by MATLAB. Then the displacements and stresses time histories were obtained. The method introduced in this paper can be used to assess the safety of tower under different fluctuating wind with different directions and provide a reference of the tower in the design stage.
In order to meet the needs of special structural gears in the development of aviation, aerospace and automobile industries, the existing gear processing methods can not meet the processing precision. If it is necessary to pay a large cost to meet the processing precision, a new Processing methodhobbing processing method of spiral face gear. On the basis of a large number of previous studies, based on the differential geometry and spatial meshing principle, the tooth surface equation of the helical face gear is derived and the threedimensional model is simulated by coordinate transformation and meshing relationship; considering the assembly mode and motion of the hob and the helical face gear Relationship, the machining coordinate system is established, and the helical face gear tooth surface and meshing equation are obtained from the hob-based worm tooth surface equation and the Archimedes worm hob is designed. Finally, the conclusion is given and the research work that needs further development is proposed.
The face gear is the core component used in the helicopter transmission system. Compared with other gear transmissions, the face gear transmission has large coincidence degree, stable transmission, low noise, no axial force, small space occupied by the transmission device, and torque splitting effect. It is a good advantage, so it is generally used in the aerospace field. In this paper, in the face gear transmission process, the contact lens sensitivity caused by the surface gear installation error, using the combination of theoretical analysis and computer simulation, the application of differential geometry and gear meshing transmission theory, combined with the surface topology design technology, The face tooth surface design method with low sensitivity of meshing impression error and stable meshing quality is used, and Gauss curvature is used as the installation sensitivity coefficient to analyze the sensitivity of surface gear mounting error.
With the development of internet technology, the Internet of Things (IoT) has been widely used in several aspects of human life. However, IoT devices are becoming more vulnerable to malware attacks due to their limited computational resources and the manufacturers’ inability to update the firmware on time. As IoT devices are increasing rapidly, their security must classify malicious software accurately; however, current IoT malware classification methods cannot detect cross-architecture IoT malware using system calls in a particular operating system as the only class of dynamic features. To address these issues, this paper proposes an IoT malware detection approach based on PaaS (Platform as a Service), which detects cross-architecture IoT malware by intercepting system calls generated by virtual machines in the host operating system acting as dynamic features and using the K Nearest Neighbors (KNN) classification model. A comprehensive evaluation using a 1719 sample dataset containing ARM and X86-32 architectures demonstrated that MDABP achieves 97.18% average accuracy and a 99.01% recall rate in detecting samples in an Executable and Linkable Format (ELF). Compared with the best cross-architecture detection method that uses network traffic as a unique type of dynamic feature with an accuracy of 94.5%, practical results reveal that our method uses fewer features and has higher accuracy.
Let k be a positive integer and G be a graph. If d(u) + d(v) ≥ 4k − 3 for any uv ∈ E(G), then G admits a star decomposition in which all stars have size at least k. In particular, every graph G with δ(G) ≥ 2k − 1 admits such a decomposition. The bounds are best possible, in the sense that there exist infinitely many graphs G with δ(G) ≥ 2k − 2 and without such a decomposition.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.