Maintenance, Reliability and Condition Monitoring
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Assessment of the impact of TE33A diesel locomotive wheelsets on the railway track in a straight section of the track
Get PDFThe purpose of the article is an experimental study of the impact of the wheelsets of a mainline diesel locomotive on the railway track on straight sections of the track. The measurements were performed on a vibration measuring device consisting of MV25 DV type sensors and an oscillation converter for a digital signal. It is proved that the indicators of dynamic characteristics comply with regulatory requirements. As a result of the conducted research, digital data was collected from the ADC and general monitoring was carried out. Measurement and signal processing are carried out using special software of a personal computer such as a “Notebook”. Vertical static load of a wheelset of a railway rolling stock unit on rails: the load of a railway rolling stock unit on rails attributed to one wheelset, taking into account the actual location of the center of gravity of the superstructure
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
Common fixed-point theorem for commuting maps on a metric space
Get PDFSeveral novel uses of theorems for fixed points in commuting mapping in a fully metric domain are presented. Several conclusions from full metric fixed point theory are improved and extended by our work. Our proofs are inspired by the study of commuting mappings [B. Fisher and S. Sessa, on a fixed point theorem of Gregus, 1986] and [P. Sumati Kumari, Fixed and periodic point theory in certain spaces, 2013]
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
Exploring additive manufacturing in assistive technologies to transform the educational experience: empowering inclusion
Get PDFThis study explores additive manufacturing's potential in creating tailored assistive technologies, fostering inclusion in education. To design ergonomic solutions for diverse user needs, promoting inclusion and autonomy. A sequential approach involves assessment, 3D modeling, additive manufacturing, and aligning with the Inclusion Support and Accessibility Promotion Program (PIPA). Various assistive technologies were developed, addressing specific needs. The “Ergonomic Pen and Pencil Reamer” improves grip accuracy, and the “Folding Handle for Folding Cup” offers an ergonomic solution. The “Guideline Ruler” supports music education, with accessories like the “Template for Clefs and Musical Notes” and “Thimble with Support Base for Musical Instrument Strings” enhancing versatility. The “Ring with Front Support” aids art education, and the “Support for Scissors” promotes independence. These innovations contribute to inclusion and autonomy. The research underscores the importance of additive manufacturing in crafting personalized solutions, propelling inclusion in education and daily activities. Identified challenges, including material selection and adaptation to diverse needs, signal areas for future research. Continuous collaboration with end-users and professionals remains crucial for enhancing usability and effectiveness, reinforcing the commitment to promoting inclusion and autonomy
Adaptive robust control of electromagnetic actuators with friction nonlinearity and uncertainty compensation
Get PDFFriction nonlinearity and uncertainty are the main factors affecting the highly performance control of electromagnetic actuators. In this paper, a nonlinear adaptive robust control strategy is proposed of electromagnetic actuators with friction nonlinearity and uncertainty compensation. First, the dynamical model of the electromagnetic actuator is established considering nonlinearity and uncertainty. Then, an adaptive robust controller is designed based on the continuously differentiable friction model to ensure that the control input is continuously and bounded. In the design of the controller, the unfavorable effects of unknown parameters in the electromagnetic actuator are eliminated by constructing a parameter adaptive law. Meanwhile, in order to improve the tracking accuracy of the electromagnetic actuator, a nonlinear robust control law is designed to ensure the robustness of the controller. The stability analysis by Lyapunov function shows that the asymptotic tracking effect can be obtained when only parameter uncertainty exists in the closed-loop system of the electromagnetic actuator, and the consistent bounded stability can be ensured when the system also exists uncertain nonlinearity. Extensive comparative results verify the effectiveness of the proposed control method
Optimization and experimental validation of the air intake holes of the lithium-ion battery pack
Get PDFEnergy storage systems enable the storage of energy and provide access to carbon-neutral, environmentally friendly energy whenever or wherever it is needed. Lithium-ion batteries are currently the most preferred type among various battery technologies and are widely used in energy storage systems. Some of the features that make lithium-ion batteries advantageous include high energy density, long life, low maintenance requirements, and high operating voltage. The growing demand for energy throughout the day increases the need for batteries with high storage capacity. However, the increased capacity also leads to heating issues in lithium-ion batteries. The heating problem in lithium-ion batteries can result in nonhomogeneous temperature distribution, shortened lifespan, thermal runaway, increased internal resistance, and performance loss. Therefore, an effective thermal management system is essential for cooling lithium-ion batteries. This study aims to provide insight into the forced air cooling of prismatic 280 Ah LiFePo4 batteries, which have limited information in the literature and are more prone to overheating compared to lower-capacity batteries. In this study, five different battery pack case designs, each with different sizes and numbers of air intake holes, were determined and modelled using the SolidWorks program. Within the battery pack cases, 16 280 Ah lithium-ion batteries are placed, and an axial fan is used to cool these batteries. Initially, computational fluid dynamics analyses of the five different designs were performed in the SolidWorks Flow Simulation program. An experiment was then conducted on the design that provided the most efficient thermal management to validate the numerical results. The selected design, fulfilling the purpose of homogeneous temperature distribution and having the minimum temperature difference between batteries, was designated as Design 5. It exhibited a 62 % improvement in cooling performance with a 0.25 °C temperature difference, indicating successful temperature homogeneity between batteries. During a two-hour experiment with a 140 A discharge current, temperature measurements were taken from the surfaces of the batteries using thermocouples. Finally, the maximum error rate between experimental and numerical studies was determined to be 1.47 %, indicating successful validation of the numerical study. The air intake hole optimization, a novel design approach, prevents temperature distribution inhomogeneity caused by the distance of the batteries to the fan and offers an effective way to cool down high-capacity 280 Ah batteries
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
Trajectory-based synthesis of a slider-crank mechanism for applications in inertial vibration exciters
Get PDFSlider-crank mechanisms are widely used in various industrial and technological machines. This paper considers a generalized diagram of a slider-crank mechanism, on the connecting rod of which an imbalanced mass can be fixed. In such a case, the slider-crank mechanism can be employed as an inertial vibration exciter. The aim of this research is to justify the geometric parameters of the mechanism to ensure a predetermined elliptical trajectory of the imbalanced mass motion. The research methodology involves the analytical derivation of the motion equations for a connecting rod point and solving the problem of synthesizing the geometric parameters of the mechanism based on the given trajectory of this point. The obtained results are presented in the form of displacements and trajectories for the connecting rod point of a specific slider-crank mechanism. The major novelty of this research lies in the further development of the theory of slider-crank mechanism synthesis for use in inertial vibration exciters. The derived analytical dependencies can be utilized by designers and engineers in the development of new types of vibration exciters for various industrial and technological vibratory equipment
Multi-source partial discharge pattern recognition in GIS based on Grabcut-MCNN
Get PDFPartial discharge (PD) surveillance constitutes a pivotal methodology for diagnosing insulation failures in electrical equipment. Enhancing comprehensively the precision of identifying PD anomalies in Gas Insulated Switchgear (GIS) is of paramount significance for ensuring the steady functioning of power grids. This study introduces a novel framework that integrates Phase-Resolved PD Graph Segmentation (PRPD-Grabcut) with a tailored MobileNets-based Convolutional Neural Network (MCNN) to classify GIS-related PD issues. Leveraging image segmentation via PRPD-Grabcut, crucial features are extracted from PRPD diagrams, which then facilitate the construction of the MCNN model. This model employs depth-wise separable convolutions alongside inverted residual architectures to tackle the vanishing gradient dilemma inherent in Deep Convolutional Neural Networks (DCNNs) during GIS PD pattern discernment. Upon the model's subsequent training and validation, empirical evidence illustrates that the PRPD-Grabcut-MCNN hybrid significantly alleviates the computational load and storage requisites of the model, concurrently enhancing the recognition precision and expediting the training process of the neural network. Relative to diverse established lightweight neural network architectures, MCNN manifests superior performance in terms of recognition accuracy, reduced cross-entropy loss, and expedited training duration