In this article, the horizontal hinged heavy duty servo cylinder is taken as the research object. In the actual working process, while the servo hydraulic cylinder outputs the curve force, the cylinder body will also rotate with the hinge point to a certain extent. Because the position of the center of gravity is constantly changing, and the weight of the cylinder body is too large, the friction causes damage to the sealing structure and seriously affects the working efficiency of the equipment. In order to improve the sealing performance of the servo hydraulic cylinder, a corresponding study is carried out. Firstly, the working angle interval of servo cylinder is optimized to ensure that the friction is the least in this range. Based on this, a new supporting structure is proposed, in which a small hydraulic cylinder is installed at the bottom of the servo hydraulic cylinder body. By controlling the output force of the small hydraulic cylinder, the cylinder body and piston rod are aligned all the time. The servo cylinder body is flexibly processed to more realistically see the adverse effect of the friction, and the co-simulation method using MSC.ADAMS and MATLAB/Simulink verifies the new support structure to improve the sealing performance. According to the simulation results and experiment results, and combined with the deformation curve of the hydraulic cylinder, when the maximum displacement is 336 mm, the maximum rotation angle is 15.6°, the friction is the smallest, about 5801.9 N. It is known from the experiment results that after adding the new support structure, the frictional force is reduced to 1365.9 N, which reduces the friction of nearly 76.5%.
In this article, the horizontal hinged heavy duty servo cylinder is taken as the research object. In the actual working process, while the servo hydraulic cylinder outputs the curve force, the cylinder body will also rotate with the hinge point to a certain extent. Because the position of the center of gravity is constantly changing, and the weight of the cylinder body is too large, the friction causes damage to the sealing structure and seriously affects the working efficiency of the equipment. In order to improve the sealing performance of the servo hydraulic cylinder, a corresponding study is carried out. Firstly, the working angle interval of servo cylinder is optimized to ensure that the friction is the least in this range. Based on this, a new supporting structure is proposed, in which a small hydraulic cylinder is installed at the bottom of the servo hydraulic cylinder body. By controlling the output force of the small hydraulic cylinder, the cylinder body and piston rod are aligned all the time. The servo cylinder body is flexibly processed to more realistically see the adverse effect of the friction, and the co-simulation method using MSC.ADAMS and MATLAB/Simulink verifies the new support structure to improve the sealing performance. According to the simulation results and experiment results, and combined with the deformation curve of the hydraulic cylinder, when the maximum displacement is 336 mm, the maximum rotation angle is 15.6°, the friction is the smallest, about 5801.9 N. It is known from the experiment results that after adding the new support structure, the frictional force is reduced to 1365.9 N, which reduces the friction of nearly 76.5%.
“…SVR is a machine learning technique based on statistical learning theory 24 that has been widely used to address problems in applications. 25–27 Compared with traditional regression methods, such as the kriging method and response surface method (RSM), 28 the SVR method can cope with a large number of independent variables and provides a sound generalization capacity. 29,30 Thus, based on the results of all orthogonal tests, relationships were developed based on the application repository of SVR 31,32…”
Section: Development Of the Multi-objective Optimization Functionmentioning
In the traditional design of a vehicle suspension system, mechanical parameters, such as spring stiffness and tire radial stiffness, are determined before optimizing the coordinates of suspension hard-points based on handling and stability. However, the mechanical parameters of vehicle suspension systems vary with repeated changes in ambient temperature and loading conditions. Consequently, the original hard-point coordinates cannot guarantee satisfactory handling and stability after long-term vehicle use. To address this issue, an A0 class vehicle with a MacPherson suspension was modeled in ADAMS/Car and was validated against the results of field tests. The relationships between the maximum absolute values of front wheel alignment parameters during parallel wheel travel analysis and the coordinates of suspension hard-points, spring stiffness, and tire radial stiffness were determined using support vector regression. Next, a multi-objective optimization function was formulated based on the interval analysis method. Finally, a novel double-loop multi-objective particle swarm optimization algorithm was designed for global optimization of hard-point coordinates. The ADAMS simulation results indicated that, compared with the vehicle with the original hard-point coordinates, the double-loop multi-objective particle swarm optimization algorithm, the traditional multi-objective particle swarm optimization algorithm, and the genetic algorithm can effectively reduce the variation ranges of front wheel alignment parameters, regardless of the values of the mechanical parameters. It also showed that the double-loop multi-objective particle swarm optimization algorithm performs better than the traditional multi-objective particle swarm optimization and the genetic algorithm with both the original and changed mechanical parameters. Except for an increase in the variation range of the caster angle by 9.24–10.69%, the variation ranges of the toe angle, camber angle, and kingpin inclination angle under various mechanical parameters using the double-loop multi-objective particle swarm optimization algorithm were observed to be reduced by 50.45–79.39%, 1.84–4.24%, and 2.11–2.96%, respectively. Last but not least, the proposed double-loop multi-objective particle swarm optimization algorithm provided better handling, stability, and ride comfort values than the traditional multi-objective particle swarm optimization algorithm and the genetic algorithm.
“…Sistem kemudi multi independent merupakan sistem kemudi dimana tiap roda dapat bergerak secara bebas ke segala arah dan merupakan tipe gerak holomonic [11]. Didukung dengan beberapa sensor yang merupakan alat untuk digunakan mendeteksi perubahan pada lingkungan fisik atau kimia baik itu perubahan mekanis, panas, cahaya dan sebagainya.…”
- Robot technology appears to ease human work. With devices such as fire fighting robots, rescue robots, surveillance robots, and robots whose functions differ according to field needs. In this paper, we have the idea of implementing an intelligent fire extinguisher robot with multi-independent steering that can be directed to the location of the fire to find the source of hotspots. With multi-independent steering, the wheels on the robot can navigate and move swiftly on each wheel that moves in all directions. In this paper we simulate by searching for candles as a source of hotspots. When this robot finds a source of fire, this robot will turn off the candle or source of the fire automatically. This robot contains the following functional components: ultrasonic to find out the surrounding field, a light sensor to look for sources of hotspots or light sources, and a fan to turn off the candle or the point of fire. In terms of design, although the designs of robots are minimalist and small, they provide protection at high temperatures, excellent waterproof when exposed to water spray, and a high impact resistance. As well as creating an automatic robot that aims to find a way automatically to find the presence of hotspots on the fire field without being controlled. This study aims to provide an automatic fire extinguisher system that can help and lighten the fire extinguishing profession which has a high level of risk in its operation. The results of this study will be able to create an intelligent robot that can minimize the risk of the work of a fire extinguisher profession with a multi-independent steering method. By using this method the steering system where each wheel can move freely. With this steering system the robot can move freely in all directions and is a type of holomonic motionKeyword : Fire extinguisher robot, robotic system, portable evacuation guide, multi-independent steering
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