Robotic Systems and Applications
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Design of automotive mechanical automatic transmission system based on torsional vibration reduction
Get PDFAutomatic transmission system is the core part of vehicle transmission processing, which can improve driving safety. In order to improve the shift effect of automotive automatic mechanical transmission and narrow the gap between the vehicle speed and the expected speed, an automotive automatic mechanical transmission system based on torsional damping was designed in the experiment. On the basis of hardware composed of different modules and fuzzy control algorithm, the system realizes the software design of vehicle automatic mechanical transmission system. The experimental results show that when the system is applied in practice, the gear selection time of the vehicle is between 0.2 s-0.3 s, and the gear shift time is between 0.3 s-0.4 s. The gap between the vehicle speed and the expected speed, and between the vehicle speed and the expected speed is small. The practical application effect is good
A mathematical model and microcontroller-based method for measuring dielectric permittivity and discharge characteristics with Arduino ATmega 328: a case study in a physics laboratory
Get PDFA microcontroller-based measuring instrument and a new mathematical model are used to investigate capacitor permittivity and dielectric materials' charge-discharge characteristics. In this study, a prototype capacitive permittivity measurement apparatus for dielectric materials was carefully developed using an Arduino microcontroller, a resistor, and a capacitor. The experimental setup comprises a capacitor-resistor circuit, wherein a 5-volt power supply sourced from the microcontroller interfaces with a computer. During the charging process, a comprehensive evaluation of model-data alignment was performed, yielding values of 0.54252156, 0.9951, and 111.2508701 for the sum of squares error (SSE), the coefficient of determination (R-squared), and the sum of squares total (SST), respectively. Similarly, the analysis extended to the discharging process, unveiling values of 5.10174756, 0.962805684, and 137.1647082 for SSE, R-squared, and SST, respectively. These findings confirm the accuracy of the microcontroller that was programmed by incorporating a model in precisely measuring the relative permittivity of dielectric materials and capacitance values, with an R-squared value above 0.95 following capacitor literature benchmarks. The novelty of this study is that this configuration enabled the precise assessment of both permittivity and the charge-discharge characteristics of the dielectric materials within the capacitor. This methodology made it possible to accurately measure the permittivity and charge-discharge characteristics of dielectric materials within a capacitor. The scientific significance of this research lies in its ability to provide a carefully developed instrument capable of investigating the permittivity of dielectric materials and capacitor capacitance measurements. Scholars, international engineering communities, and academics can use this technological breakthrough to advance research into dielectric material properties and capacitor characteristics
Characterization of 3D-Radar images of pavement devoid damage based on FDTD
Get PDFAccurate judgement of devoid damage information by 3D-Radar is an effective way of repairing damage in nondestructive pavements. In order to systematically analyse the characteristics of devoid damage under nondestructive pavements in 3D-Radar response. In this study, the 3D-Radar response to devoid damage of different sizes, locations and moisture contents was quantified by FDTD orthorectified simulations. Data acquisition of the pre-buried devoid damage on site was carried out using 3D-Radar, compared with the orthorectified simulation results and numerical analysis. The detection effect was also verified by relying on the project. The results show that the radar wave characteristics of the devoid damage are obvious. Different colour and waveform image characteristics in B-Scan in the presence and absence of water at the location; the size of the devoid also has an impact on the image characteristics. It depends on the footprints and size of the devoid. It creates “upward-convex”, “down-concave” and straight features; the presence of the devoid characteristics in the 3D-Radar mapping will enhance the confidence of the devoid identification through field tests and engineering verification
Joint effects of thermal diffusion and diffusion thermo on MHD three dimensional nanofluid flow towards a stretching sheet
Get PDFThis communication reports the joint effects of Thermal Diffusion and Diffusion Thermo on viscous and incompressible three-dimensional nanofluid flow towards a stretching sheet in connection to the influence of a magnetic field. In this study, nanofluid model is employed for the effects of thermophoresis and Brownian motion. Following that, similarity variables are chosen to turn the dimensional nonlinear system into dimensionless expressions and the resultant transformed equations are solved numerically using Finite Element method. Special emphasis has been given to the parameters of physical interest. These findings are visually presented through graphical representations, providing a clear and insightful understanding involved in this flow scenario. In addition, the final results are examined in light of past research and it is determined that they meet the convergence standards to an exceedingly satisfactory degree. The study’s findings are beneficial for many technical and commercial endeavours
Application of optimized CNN algorithm in landslide boundary detection
Get PDFLandslide, as a natural geological phenomenon with great harm, seriously threatens human social activities and life safety. It has a variety of latent and immeasurable destructiveness, which has a significant impact on the economic losses in rural areas. Therefore, it is urgent to take measures to accurately identify landslides to reduce their negative impacts. However, traditional manual visual interpretation has been unable to meet the current needs for emergency rescue of landslides, so computer intelligent methods have been paid attention to. This study proposes a new recognition network to address the problem of low accuracy of intelligent landslide boundary recognition methods. Firstly, the experiment incorporated boundary structure information into the Full Convolutional Network (FCN) for optimization, and constructed an Improved Full Convolutional Network (IFCN) model to better achieve image reconstruction. After that, Attention Mechanism (AM) is further introduced to achieve accurate detection of landslide boundaries in images, namely the IFCN-AM model. The attention mechanism introduced include spatial attention mechanism and multi-channel attention mechanism. Both are responsible for enhancing the language representation ability of the model and aggregating the interrelated features between different channels. The experimental results show that IFCN-AM has a 3 % to 7 % improvement in accuracy, recall, F1 value, and MIoU value
Anterior crossbite treatment using functional orthopedic appliance: a case report
Get PDFAnterior crossbite can affect primary, mixed, and permanent dentitions. Early treatment is recommended, as it can impact facial, aesthetic, functional, and developmental aspects. The etiology of anterior crossbite is multifactorial, including dental, skeletal, and postural origins. Treatment should be defined based on age and etiology, with various therapeutic resources available for correction. In primary dentition, direct flat tracks, different types of functional orthopedic appliances, quad-helix, and facial mask can be used. In mixed dentition, fixed segmented or continuous orthodontics, elastics, and other devices can be added to the treatment. In permanent dentition, orthognathic surgery may be indicated for adults, especially in cases of anterior crossbite associated with skeletal Class III that cannot be compensated dentally. This case report describes the treatment of early mixed dentition anterior crossbite with a functional orthopedic appliance at the Orthodontic Specialization, Postgraduate Course at Modal college, Belo Horizonte, Minas Gerais, Brazil. After correction, proper chewing functions were reestablished with ideal developmental stimuli
Overview of the prospects for the introduction of ultrasonic oil treatment in the main pipeline transport
Get PDFThis paper considers the most common methods of pipeline transport of high solidified oil existing at the moment. The effects of treating oil with magnetic and electric fields are given. The positive and negative effects of ultrasonic treatment in oil transport processes are considered. The totality and quality of the facts requires much more in-depth analysis on a number of issues in this area because with a lot of positive effects are present and negative, which do not allow to implement
Trajectory planning and control algorithm of industrial robot manipulator
Get PDFAs the industrial robot task becomes more complex, the difficulty of trajectory planning and tracking control of manipulator is gradually increasing. To minimize the vibration during the manipulator motion and improve the planning accuracy, the method of quintic polynomial combined with non-uniform B-spline interpolation is studied for joint space (JS) planning. The trajectory tracking system is easily affected by friction nonlinearity and parameters. So a JS trajectory tracking controller based on based on fuzzy neural network (FNN) is designed. Through simulation experiments, the curve obtained by the planning method studied is smoother and the planning error is minimum. The maximum position error is 0.09 rad, and the speed error is not more than 0.1 rad/s. The controller performance test results under different parameters show that the W^, c^, κ^ parameter in FNN can be adjusted in real time, and the value will not affect the performance of the controller. The fluctuation range of trajectory error of different joints is within ±0.2×10-5rad, which indicates that the performance of AFNNC controller studied is better. And its response time is the shortest and its robustness is better when the load changes suddenly
The application of fault diagnosis techniques and monitoring methods in building electrical systems – based on ELM algorithm
Get PDFThe reliability of modern building electrical systems are receiving increasing attention as they become more intelligent and complex. As the majority of building electrical systems use neutral point grounding, earth faults or short circuits can get worse over time and damage both the distribution system and the electrical equipment. To this end, the corresponding three phases and four categories, namely three-phase voltage, three-phase current after fault, three-phase voltage distortion rate, three-phase current distortion rate, a total of 12 dimensional fault feature vectors and 10 fault simulation types, were summarised and extracted in conjunction with the actual operating conditions of the system. Using traditional fault identification ideas and neural network algorithm as reference, a 12-dimensional fault feature vector is used as the model input to construct a building electrical fault diagnosis and detection model based on ELM algorithm. Results showed that the ELM-based model’s classification accuracy for this experimental sample was 97.56 %, its AUC was 0.92, and its RMSE was 0.3521. These figures were higher than the classification accuracy and performance of the BP algorithm and GA-BP algorithm fault diagnosis models, and they also demonstrate better robustness and generalizability. The model also has a 97.27 % correct rate in fault discrimination, while the computation time is only 0.201 s, and its fault identification and diagnosis speed is faster than other algorithmic models. At the same time, this research model has a good fault monitoring accuracy of up to 98.6 % for building electrical systems. The research can provide a more sensitive, accurate and rapid fault monitoring method for the current building electrical system. It also improves the reliability of the building electrical system in a complex environment and achieves better protection of the system. This has a certain significance for the development of the building electrical industry
Applications of collaborative robots in agile manufacturing: a review
Get PDFCollaborative robots are machines that work hand in hand with humans; or as the name suggests, collaborate with them in a specific workspace. These robots are not enclosed in confined safety zones like traditional robots, as they interact very closely with humans. Though this is the case, appropriate measures are captivated while designing these robots considering human safety. These robots are well-versed in adapting to changes and frequent upgrades. They are flexible enough to carry out complex tasks. Due to these abilities, they become a significant asset in the manufacturing field. It’s been many years now since cobots are introduced in the industry sector. So, this is the right time to review various applications of cobots in manufacturing. First, the paper starts with a brief introduction followed by an extensive literature review which was structured after reviewing 76 research papers and articles. It ends with some essential conclusions. This paper discusses the diverse applications of cobots used in the manufacturing sector and their advantages. Further, it highlights the future of cobots and how they will be a boon for a technology-driven world