Journal of Mechanical Engineering, Automation and Control Systems
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Development of gear fault identification of wind turbine’s transmission system based on VMD and FNN
Get PDFIn order to improve the safety of wind turbine, this paper takes the high-speed spur gear on output shaft in the transmission system of the wind turbine as the study object. The original signals of the gear in different fault states which obtained from the experimental platform decompose by the empirical mode decomposition method (EMD) and the variational mode decomposition method (VMD), respectively. Then the different gear fault types’ eigenvectors were built. Fuzzy neural network (FNN) is adopted to learn the fault types and eigenvector samples of gears, and then the fault types of gears are identified. It is found that the fault features decomposed by VMD method have reached a high accurate recognition rate point to the fact that VMD has good applicability in the fault recognition of gear in wind turbine
Gas parameter characteristics in Reflux Flotation Cell
Get PDFFlotation is a primary method for separating fine particles, and the growing demand for processing these particles has driven recent research efforts towards developing and designing more efficient flotation devices. Among these, the Reflux Flotation Cell (RFC) stands out as an innovative solution specifically tailored for fine particle flotation. Gas parameters are crucial factors influencing flotation and are essential indicators for evaluating flotation equipment. This study primarily investigates the gas characteristics within the RFC, including bubble size, gas holdup, and bubble surface area flux. The experimental results indicate that bubble diameters range from 0.4 to 0.8 mm, gas holdup ranges from 30 % to 50 %, and bubble surface area flux ranges from 120 to 400 s-1. These findings demonstrate that the RFC provides an optimal gas environment, conducive to effective mineral flotation
Problems of rutting on asphalt pavements
Get PDFIn the article, under field conditions (on the lane of a city road for public transport), using modeling and traffic flow analysis methods, the formation of ruts on an asphalt concrete pavement is studied. The maximum total rut depth on the road section under consideration reaches 110 mm. 715 buses and 25 trucks pass along a separate lane of the road per day, the relative rutting impact of which is from 5.68 to 16.41 compared to the design vehicle. The design of the road pavement on the experimental section with a total thickness of 48 cm is too weak for the actual traffic flow, which was the main reason for the premature failure of the road due to unacceptable rut sizes on the asphalt concrete pavement
Research on dynamic characteristics of wind turbine’s transmission system considering gear tooth lubrication
Get PDFTo improve wind turbines’ reliability and lifespan, taking the two-stage fixed shaft gearbox of wind turbines as study object. The oil stiffness and meshing stiffness of the transmission system are calculated, and the composite stiffness is obtained with the consideration of lubricating film. Then analyzed the dynamic characteristics of wind turbines’ transmission system before and after consider the oil stiffness in different operating conditions. The findings indicate that after considering the gear lubrication effect, the composite stiffness gradually decreases as rotational speed increase; within a certain rotational speed range, the tooth-surface load can be reduced, making the system run more smoothly. Therefore, the presence of oil film and its impact on its stiffness cannot be ignored. This study has certain guiding significance in improving the transmission efficiency and reducing noise of wind turbines
Logo recognition of vehicles based on deep convolutional generative adversarial networks
Get PDFVehicle logo recognition plays a critical role in enhancing the efficiency of intelligent transportation systems by enabling accurate vehicle identification and tracking. Despite advancements in image recognition technologies, accurately detecting and classifying vehicle logos in diverse and dynamically changing environments remains a significant challenge. This research introduces an innovative approach utilizing a Deep Convolutional Generative Adversarial Network (DCGAN) framework, tailored specifically for the complex task of vehicle logo recognition. Unlike traditional methods, which heavily rely on manual feature extraction and pre-defined image processing techniques, our method employs a novel DCGAN architecture. This architecture automatically learns the distinctive features of vehicle logos directly from data, enabling more robust and accurate recognition across various conditions. Furthermore, we propose a refined training strategy for both the generator and discriminator components of our DCGAN, optimized through extensive experimentation, to enhance the model’s ability to generate high-fidelity vehicle logo images for improved training efficacy. The technical core of our approach lies in the strategic integration of transfer learning techniques. These techniques significantly boost classification accuracy by leveraging pre-learned features from vast image datasets, thereby addressing the challenge of limited labeled data in the vehicle logo domain. Our experimental results demonstrate a substantial improvement in logo detection and classification accuracy, achieving an Intersection over Union (IoU) ratio of 42.67 % and a classification accuracy of 99.78 %, which markedly surpasses the performance of existing methods. This research not only advances the field of vehicle logo recognition but also contributes to the broader domain of measurement science and technology, offering a technically sound and logically coherent solution to a complex problem
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
An approach for assessment of CO2 leakage using mechanistic modelling: CO2 injection in deep saline aquifer of Lithuanian basin in presence of fault and fractures
Get PDFInjecting CO2 into deep saline aquifers is a prominent strategy for carbon capture and storage (CCS) to mitigate greenhouse gas emissions. However, ensuring the long-term integrity of CO2 storage is crucial to prevent leakage and potential environmental hazards. This paper investigates the impact of presence of faults and fracture on CO2 leakage volumes. Particular case of CO2 injection into a deep saline aquifer for carbon capture and storage (CCS) applications is investigated. This paper explores the relationship between fracture permeability and the potential for CO2 leakage
Determinated area (DA) treatment goal when treating malocclusions with jaw functional orthopedics (JFO): Contribution to scientific evidence
Get PDFOne of the goals of malocclusion treatment with Jaw Functional Orthopedics (JFO) is to obtain touch of the inferior incisors against the superior incisors in Determinate Area (DA). It is postulated that this touch would bring better stimuli and consequently faster results. Surface electromyographic study of the muscles was performed in Masseter, Temporal and suprahyoid muscles bilaterally from 159 patients undergoing malocclusion treatment with functional orthopedic appliances (FOA). To record muscle electric activity were used a conditioning signal module from Lynx Electronics Ltda with 8 channels, model EMG1000; software AqDAnalysis 4,18 from Lynx Electronics Ltda.; Software Lynx BioInspector 1,8r; passive surface electrodes (Ag/AgCl) from Noraxon Dual Electrodes (USA); dischargeable reference electrodes Kendall Meditrace (Ag/AgCl) – Canada. Frequency calibration was 2000 Hz, with 2048 sample by channel and time 1,024 seconds, and filters regulation was 20 Hz and 1000 Hz. The results found prove that there is a better electromyographic activity (bilaterally balanced) of the studied muscles when there is touch on DA. Conclusion. Touch in DA improves the neuromuscular response of patients treated with JFO. sEMG is a trustable tool to analyze masticatory muscles function for Diagnosis, Treatment and evaluation post treatment/gained objective
Optimization of reduction gear in anchor winch based on modal analysis
No full textIn order to achieve more scientific design of the reduction gear and reduce material waste, pre-stressed modal analysis method was combined with multi-objective optimization algorithm to optimize the structure of the reduction gear basic body. The model was simplified and parameterized and the maximum stress and equivalent stiffness under different parameter size combinations were obtained through finite element analysis. Separately, genetic clustering method, neural network method, and Kriging method were used to construct the response surface function. Through error verification and comparison, it was found that the Kriging method was more suitable for the gear model. In the design of variable extremum search, multi-objective genetic algorithm and sequential quadratic programming were compared and analyzed. The results show that the mass of the gear can be reduced by 39.9 %, while the maximum stress remains unchanged, the equivalent stiffness is not reduced, and a good optimization design effect is achieved
Dynamics analysis and collaborative optimization of vehicle steering mechanism
No full textIn order to improve the dynamic response characteristics of the steering mechanism, a research scheme for increasing the natural frequency based on lightweight design was proposed. Based on the finite element method and the collaborative optimization method, the modal characteristics and harmonic response characteristics of the model were studied and analyzed to verify the strength and stiffness performance of the optimized structure. The modal shapes between the free mode and the constrained mode were compared and analyzed. With the second-order natural frequency as the optimization objective, the response surface function of the equivalent stiffness was constructed. Through optimization calculation, the design variables that satisfy the constraint conditions can be obtained. The results show that the optimized structure can increase the second-order natural frequency by 14.4 % on the premise of reducing the mass by 5.2 %, effectively avoiding the excitation frequency of the engine