Journal of Engineering and Thermal Sciences
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Biomechanical surface roughness analysis of ramie-low melt polyester nonwovens exposed to plasma
Get PDFThis study aims to characterize ramie-low melt polyester nonwoven fabrics treated with low-temperature plasma and to analyze 3-D images based on object-depth mapping (ODM) using the MATLAB® R2022a software. We examined the low-temperature plasma treatment of nonwoven ramie fabrics using a plasma generator with 30 kV output power, six-minute treatment times, and a 4.5 cm distance between electrodes. The fabric’s chemical properties and surface topography were investigated using scanning electron microscopy (SEM) and infrared spectroscopy (FTIR). An analysis of the SEM images was performed using a statistical approach and image processing to determine the level of surface roughness. FTIR analysis revealed that fabrics exposed for six minutes differed from those that were not. Our findings indicated that plasma treatment caused the following: 1) Ramie fabrics to become more hydrophilic, as shown by their increased T% in the FTIR of hydrophilic functional groups such as hydroxyl (O-H), carboxyl (-COOH), and carbonyl (C=O); 2) A higher surface roughness was observed in nonwoven fabric during SEM testing and image processing; 3) Plasma treatment of fabrics resulted in a higher coefficient of variation (CV) than untreated fabrics; 4) Nonwoven fabric mass reduction. Based on this study, we found the relationship between plasma-treated ramie fabric and textiles in biomechanics. Plasma treatment reduced the mass of ramie fabric by 0.11 %, according to our findings. We found that the greater the mass reduction, the greater the surface roughness value. The novelty of this study is the use of 3-D images based on object-depth mapping (ODM) using the MATLAB® R2022a software in SEM to observe surface roughness to the physical properties of ramie fabric for the first time
Gabor wavelet transform combined with area CNN in appearance intelligent detection of stayed cables
Get PDFThe major structure for transmitting forces in a cable-stayed bridge is the stay cable. If the stay cable system fails, the whole bridge will collapse. At present, there is no very mature technical means for the detection of bridge cables. The most common method is for workers to perform regular manual inspection and replacement of cables. Although the defect condition of the cable can be detected to a certain extent, the real-time monitoring of its health cannot be realized. Therefore, the research used the median filter, mean standardization method and Retinex algorithm to preprocess the image data. And after extracting the stay cable picture’s macroscopic characteristics using the Gabor wavelet transform, it implemented image segmentation using the OTSU approach. The obtained feature images were applied to the Faster Regional Convolution Neural Network (RCNN) recognition model to detect microscopic defects. During the research, the training efficiency of traditional Convolution Neural Network (CNN) was not high. Therefore, Faster RCNN built a cable defect recognition model. Based on this, the research built an intelligent detection model for apparent defects of stay cables based on Gabor wavelet transform and improved RCNN. Through the experimental analysis, the model built for the study has a recognition accuracy rate of 94.14 %, which can achieve dynamic bridge health monitoring and instantly identify the condition of the stay cables, and maintain the safety of the bridge
Influence of wheel web structure on the tight-curve short-pitch corrugation of metro
Get PDFShort-pitch corrugation is a common phenomenon that occurs on tight-curve rails in metro systems. However, the contributing factors of this problem are still not fully understood, and effective control measures have yet to be developed. In this study, we investigated the contributing factors of short-pitch corrugation on tight-curve rails in metro systems using the complex eigenvalue analysis method according to the theory of friction-induced vibration. We also explored control measures for short-pitch corrugation from the perspective of optimizing the wheel web structure. Our results indicate that friction-induced vibration is the primary contributing factor to short-pitch corrugation in the wheel-rail system. The shape of the web structure significantly affects rail corrugation, and compared to the straight web structure, unstable vibrations are more pronounced in the S-shape web structure. In contrast, the bow web structure can significantly improve the system stability of the wheel-rail interaction, and the greater the web curvature, the better the inhibitory effect. The wheel deformation under contact force varies with the web curvature, and when the axial deformation of the wheel extends toward the inner rail, the wheel-rail system no longer exhibits unstable vibrations. Conversely, when the axial deformation of the wheel extends toward the outer rail, the greater the deformation, the greater the instability of the wheel-rail system
Target detection algorithm based on super- resolution color remote sensing image reconstruction
Get PDFAn improved generative adversarial network model is adopted to improve the resolution of remote sensing images and the target detection algorithm for color remote sensing images. The main objective is to solve the problem of training super-resolution reconstruction algorithms and missing details in reconstructed images, aiming to achieve high-precision detection of medium and low-resolution color remote sensing targets. First, a lightweight image super-resolution reconstruction algorithm based on an improved generative adversarial network (GAN) is proposed. This algorithm combines the pixel attention mechanism and up-sampling method to restore image details. It further integrates edge-oriented convolution modules into traditional convolution to reduce model parameters and achieve better feature collection. Then, to further enhance the feature collection ability of the model, the YOLOv4 object detection algorithm is also improved. This is achieved by introducing the Focus structure into the backbone feature extraction network and integrating multi-layer separable convolutions to improve the feature extraction ability. The experimental results show that the improved target detection algorithm based on super resolution has a good detection effect on remote sensing image targets. It can effectively improve the detection accuracy of remote sensing images, and have a certain reference significance for the realization of small target detection in remote sensing images
Dynamic analysis of gear pairs with the effects of stick-slip
Get PDFThe instantaneous dynamic contact state analysis is carried out to reveal the process of scuffing failure of the gear tooth pair. A stick-slip dynamic model of a two-gear set is proposed and the coupling effects of time-varying mesh stiffness, tooth separations, friction between the gear teeth surfaces, and potential stick-slip are considered. Dynamic analysis shows that stick contact is an important source of tooth scuffing failure. Additionally, stick contact dramatically increases the vibration amplitudes and causes chaos. Parametric studies show that heavy load and rough tooth surfaces increase the probability of sticking and increase the time of stick state over a single mesh period. This study provides a design guard for avoiding scuffing failure and improving the reliability of gear transmission
Design of downhill regenerative braking control method for hybrid electric vehicle
Get PDFIn order to improve the downhill regenerative braking control effect of hybrid electric vehicle (HEV), this paper designs a downhill regenerative braking control method for hybrid electric vehicle (HEV). Firstly, the structures of regenerative braking system, auxiliary braking system and eddy current retarder (ECR) are analyzed. Secondly, the braking torque of ECR when HEV downhill braking is calculated. Then, the braking process of HEV is dynamically analyzed, and the braking force distribution constraint of HEV is realized according to the relevant laws and regulations. Finally, the downhill regenerative braking control of HEV is realized based on the braking force distribution coefficient. The results show that when the vehicle speed is up to 120 km·h, the speed control can still be completed within 2 s by using the proposed method, indicating a good regenerative braking effect
Sensitivity analysis of numerical model parameters for optimized PEH responses
Get PDFWith the increasing popularity of wearable devices, typically employed in fitness and health monitoring, there is an evident need to extend their autonomy and replace the conventional power sources with environmentally friendly alternatives. Piezoelectric energy harvesting systems, optimized for collecting kinetic energy from random human motion and transduce it into electrical energy, represent a viable option for powering autonomous wearables. Since established analytical methods are unable to model the behaviour of piezoelectric harvesters with complex optimized geometries, suitable numerical models need to be employed for their design. This implies the need of a thorough study focused on the mechanical engineering design optimization purposes of how the finite element type and mesh density affect the uncoupled modal and coupled transient responses of a new class of optimised design configurations of the studied devices
Research and design of program complexity measurement technology based on OINK framework
Get PDFWith the expansion of software system scale, the study of software complexity has become a hot topic in software engineering. However, the domestic research on software complexity analysis technology is not mature, especially the measurement and evaluation methods of software complexity are not perfect. In order to solve the problem of prediction and evaluation of program structure complexity in software engineering more effectively, this paper proposed a program complexity measurement technique based on OINK framework. The technology uses the data sharing interface design to analysis target program by extracting the complex relationship between OINK components. On this basis, the technology adopts the layered software architecture to realize the automatic design of the function of the measurement data acquisition module, the complexity measurement module and the data management module of measurement results, thus, the structure complexity of the target program can be analyzed more clearly and accurately. At the same time, this technique applies multiple measurement methods to quantify the complexity of program structure, such as McCabe, HalStead, and Line Count. Experimental results show that this method can effectively measure the complexity of program structure. The solution on software complexity based on the open source ONIK framework will be open up worldwide, and will be continuously supported and improved by global communities and teams under the constraints of common driving forces
Designing and controlling a self-balancing platform mechanism based on 3-RCC spherical parallel manipulator
Get PDFMotion control platforms have various applications in the manufacturing and automation industries. Different literature provides multiple issues related to the kinematics and dynamics of self-guided robots for transportation regarding platform balancing. Self-balancing platforms are utilized in many deliveries, stabilization, and transportation systems, and they are especially well suited for outdoor activities when the ground surface is not flat or structured. This paper describes developing a control technique for a self-balancing platform using the 3-RCC spherical parallel manipulator. This mechanism was designed to support an AGV (Automated Guided Vehicle) for transporting and lifting heavy weights for industrial applications. The AGV carries a robotic arm on top for different tasks. When the AGV encounters a steep slope or a rough surface, the AGV tilts, and the robotic arm’s performance is significantly affected. So, this study gives a solution to avoid these circumstances with a novel approach for the platform’s self-balancing mechanism consisting of a 3-RCC spherical parallel manipulator. Real-time stabilization and kinematics analysis methods are used to achieve the self-balancing system of the platform. When both methods are observed through different tilting angles for automation stability, Kinematic analysis performs more efficiently with less time duration when compared with the real-time stabilization method
Supplementation of synthetic object replicas for increasing precision of microrobot trajectory keypoints
Get PDFArtificial neural networks are becoming more popular with the development of artificial intelligence. These networks require large amounts of data to function effectively, especially in the field of computer vision. The quality of an object detector is primarily determined by its architecture, but the quality of the data it uses is also important. In this study, we explore the use of novel data set enhancement technique to improve the performance of the YOLOv5 object detector. Overall, we investigate three methods: first, a novel approach using synthetic object replicas to augment the existing real data set without changing the size of the data set; second - rotation augmentation data set propagating technique and their symbiosis, third, only one required class is supplemented. The solution proposed in this article improves the data set with a help of supplementation and augmentation. Lower the influence of the imbalanced data sets by data supplementation with synthetic yeast cell replicas. We also determine the average supplementation values for the data set to determine how many percent of the data set is most effective for the supplementation