Robotic Systems and Applications
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Lubrication optimization of high-speed train drive gearbox
Get PDFThe gears in the high-speed heavy-duty gearbox of the high-speed train are typical high-speed heavy-duty gears. Combined with the transmission principle and structural characteristics of the high-speed train drive gearbox, to ensure adequate lubrication of meshing gears and bearings, an optimization of the lubricating oil flow inside the gearbox was conducted. The oil and gas two-phase flow model inside the gearbox adopts the VOF model, and the turbulence model adopts the standard κ-ε model. Fluent is used for simulation calculation. The results show that the exhaust port position of the gearbox has little effect on the flow of lubricating oil inside the gearbox; the overall pressure distribution inside the gearbox is relatively uniform, with higher pressure only at the meshing gears; the distribution of lubricating oil inside the gearbox is related to the rotation of the gears, and the flow velocity of lubricating oil is mainly affected by the rotation of the gears, with the maximum flow velocity appearing around the gears; the flow of lubricating oil inside the gearbox meets the lubrication requirements of the gearbox. These results provide support for the lubrication design, flow channel structure improvement, and effectiveness evaluation of high-speed train transmission gearboxes
Research on quantitative design methods for the durability of reinforced concrete structures in a hot ocean environment
Get PDFThis paper establishes a quantitative design method for the durability of concrete structures in cross-sea bridges through investigation, rapid chloride migration coefficient method (RCM) and theoretical calculation, considering the impact of temperature on chloride ion diffusion rates in a hot marine salt erosion environment. Combined with the RCM test and bridge service data, a quantitative design method for bridge concrete durability is proposed. Test results show that the growth rate of the chloride ion diffusion coefficient of concrete is approximately 1.028 for every 1 °C increase. For every 5 °C increase, the growth rate of the chloride diffusion coefficient of concrete is about 1.15, and the cover depth of the concrete structure should be multiplied by a coefficient of 1.07. Therefore, the concrete cover depth should be appropriately increased, considering the influence of ambient temperature. Furthermore, fly ash, slag, and stone powder can increase the concrete’s resistance to chloride corrosion. When the influence of temperature on the chloride ion diffusion coefficient is considered, the durability design of the concrete structure of the sea-crossing bridge is conducted, which is beneficial for ensuring their service life
Identification and characteristic statistics of surface microstructure of titanium metal based on cavitation water jet
Get PDFThe application of cavitation water jet technology to modify medical implant surfaces facilitates the formation of distinctive microporous structures, thereby enhancing the contact area between the implant and alveolar bone, and improving osseointegration. Therefore, the microstructure characteristics of the modified implant are one of the important evaluation indicators of the modification effect. This paper proposes a processing method for the identification and statistical analysis of surface micro-morphology images. The method incorporates techniques such as image enhancement, image segmentation, morphological image processing methods, and pixel matrix operations, enabling automated quantification of pit counts, the relative positions of the pits, and other topographic characteristics of the material surface. Simultaneously, the microstructure of each pit is spatially fitted and reconstructed to standardize measurement benchmarks for pit diameter and depth characteristics. This facilitates in-depth multi-dimensional analysis of material surface characteristic information and provides foundational support for further exploration of cavitation jet modification technology. In the study, the modification effect of processing time on the surface morphology of titanium metal was used as an application case. A surface morphology feature information database was established under different processing times, and statistical analysis was conducted on proportion, structural distribution, and other characteristics in the focus areas. The results show that the diameter and proportion distribution of the pits produced by cavitation jet modification tend to be stable when the jet pressure and standoff distance remain constant, while the depth of the pit increases with the increasing processing time
Research on the relationship between feature extraction time and training samples of hyperspectral image based on spatial domain
Get PDFHyperspectral image (HSI) feature extraction is an important means to improve the classification of different ground features. According to the structural characteristics of hyperspectral data, the general feature extraction scheme can extract features from the point of view of spectral dimension, spatial and spatial spectrum. And the feature extraction time is also an index to measure the feature extraction method. Therefore, from the perspective of spatial dimension, this paper explores the relationship between HSI feature extraction time and training sample ratio. Three groups of HSIs sets were used for correlation test and analysis in the experiment. According to the characteristics of different data sets, the best selection scheme between spatial domain feature extraction method and training samples is given
Modal characteristics analysis of agricultural vehicle support frame
Get PDFThe support frame of large agricultural vehicles was simulated using the finite element method to ensure stability and reliability. Modal experiments were conducted to verify the simulation accuracy, and mesh division and optimization were performed based on different size and structure types. Three types of loads were applied according to different working conditions. The natural frequency, vibration mode, stress, and deformation characteristics of the model under prestressed mode condition were calculated to determine the weak structure of the support frame. Modal measurement points for calibration during test modal analysis were used to generate a test modal model with force hammer, acceleration sensor, signal acquisition instrument, and other devices. The results showed that there was good agreement between finite element modal analysis and experimental modal analysis with a maximum error in natural frequency of 2.2 %, verifying the accuracy of the finite element model
Numerical analysis of the influence of air flow channel on ear pressure during door closure
Get PDFIn this paper, Numerical simulation analysis was conducted on the ear pressure of a certain vehicle model during door closing process. Firstly, relevant airflow channel parameters are formulated based on the benchmark vehicle data, and transient closing ear pressure simulation calculation is carried out using overset grid technology. Then, the impact of key structural parameters on the interior ear pressure of the car was analyzed. Finally, based on the requirements of actual engineering design, the design scheme for the peak pressure of the car was determined, and the results will be a reference for the development and design of later vehicle
Prediction of concrete sulfuric acid corrosion evaluation index model based on grey system theory
Get PDFIn order to predict the impact of sulfate corrosion on concrete, based on grey system theory, GM(1,1) and GM(1, N) models were used to predict and analyze the compressive strength and relative dynamic elastic modulus of concrete under sulfuric acid corrosion. The results show that the prediction error of the GM(1,1) model for concrete sulfate corrosion attenuation is within 5 %, and the residual size test of the GM(1, N) model for concrete sulfate corrosion is within 10 %
A one-dimensional high-order dynamic model for twin-cell box girders with deformable cross-section
Get PDFA one-dimensional high-order dynamic model for single-box twin-cell box girders is presented together with the pattern recognition algorithm. The model takes into account the deformable cross-section and can accurately predict its 3D dynamic behaviors. The cross-section deformation is captured by basis functions satisfying displacement continuity condition, which is essential to construct the initial model formulation based on the Hamilton principle. The axial variation patterns of generalized coordinates are decoupled by solving the eigenvalue problem. On this basis, the combinations of basis functions are obtained to bring out cross-section deformation. The cross-section deformation, hierarchically organized and physically meaningful, are used to update the basis functions in the reconstructed high-order model. Numerical analysis has verified the accuracy and applicability of the reconstructed one-dimensional high-order model
Optimal path for automated pedestrian detection: image deblurring algorithm based on generative adversarial network
Get PDFThe pedestrian detection technology of automated driving is also facing some challenges. Aiming at the problem of specific target deblurring in the image, this research built a pedestrian detection deblurring model in view of Generative adversarial network and multi-scale convolution. First, it designs an image deblurring algorithm in view of Generative adversarial network. Then, on the basis of image deblurring, a pedestrian deblurring algorithm in view of multi-scale convolution is designed to focus on deblurring the pedestrians in the image. The outcomes showcase that the peak signal to noise ratio and structural similarity index of the image deblurring algorithm in view of the Generative adversarial network are the highest, which are 29.7 dB and 0.943 dB respectively, and the operation time is the shortest, which is 0.50 s. The pedestrian deblurring algorithm in view of multi-scale convolution has the highest peak signal-to-noise ratio (PSNR) and structural similarity indicators in the HIDE test set and GoPro dataset, with 29.4 dB and 0.925 dB, 40.45 dB and 0.992 dB, respectively. The resulting restored image is the clearest and possesses the best visual effect. The enlarged part of the face can reveal more detailed information, and it is the closest to a real clear image. The deblurring effect is not limited to the size of the pedestrians in the image. In summary, the model constructed in this study has good application effects in image deblurring and pedestrian detection, and has a certain promoting effect on the development of autonomous driving technology
Lightweight small target detection based on aerial remote sensing images
Get PDFWith the upgrading of aviation space technology, the amount of information contained in remote sensing images in the aviation is gradually increasing, and the detection technology based on small targets has developed. For lightweight small targets, pixels per unit area contain more information than large targets, and their area is too small, which is easily overlooked by conventional detection models. To enhance the attention of such algorithms, this study first introduces a Control Bus Attention Mechanism (CBAM) in the fifth generation You Only Look Once (YOLOv5) algorithm to increase the algorithm’s attention to small targets and generate optimization algorithms. Then convolutional neural network is used to mark feature pixels of the optimization algorithm, eliminate redundant information, and generate fusion algorithm, which is used to generate redundant information with high similarity when the optimization algorithm surveys pixel blocks. The novelty of this study lies in using CBAM to improve YOLOv5 algorithm. CBAM module can extract important features from images by adaptively learning the channel and spatial attention of feature maps. By weighting the channel and spatial attention of the feature map, the network can pay more attention to important features and suppress irrelevant background information. This attention mechanism can help the network better capture the characteristics of small targets and improve the accuracy and robustness of detection. Embedding CBAM module into YOLOv5 detection network can enhance the network's perception of small targets. CBAM module can improve the expressive ability and feature extraction ability of the network without increasing the complexity of the network. By introducing CBAM module, YOLOv5 can better capture the characteristics of small targets in aerial remote sensing images, and improve the detection accuracy and recall rate. Finally, the proposed fusion algorithm is used for experiments on the Tiny-Person dataset and compared with the fifth, sixth, and seventh generations of You Only Look Once. When the fusion algorithm tests the target, the classification accuracy of Sea-person is 39 %, the classification accuracy of Earth-person is 31 %, and the probability of being predicted as the background is 56 % and 67 %, respectively. And the overall accuracy of this algorithm is 0.987, which is the best among the four algorithms. The experimental results show that the fusion algorithm proposed in the study has precise positioning for lightweight small targets and can achieve good application results in aerial remote sensing images