The structural vibration of the main beam of a crane causes fatigue damage and discomfort to the driver. The swing of the payload has an effect on positioning precision, especially for a ladle crane, and this directly affects production safety. To study the influence of system parameters on the vibration of a crane's main beam and the angle of the payload, a system consisting of the main beam, trolley, payload, and cabin was constructed. A rigid-flexible coupling dynamic model of a moving trolley with a hanging payload that moves on the flexible main beam with a concentrated cabin mass is established, and the direct integration method is used to solve the nonlinear differential equations of system vibration, which are obtained through Lagrange's equation. Then, the time domain responses of the flexible main beam, payload angle, and cabin vibration are obtained. The influences of the trolley running speed, quality of the payload, and quality and position of the cabin on the vibration of the main beam and payload angle are analyzed. The results indicate that the amplitude of the main beam is directly proportional to the quality of the trolley, payload, and cab; the position of the cabin is closer to the mid-span; the amplitude of the main beam is larger; the structural damping has some influence on the vibration of the main beam; and the swing angle of the payload is related to the maximum running speed of the trolley, acceleration time, and length of the wire rope. In order to reduce the vibration of the main beam and cabin, the connection stiffness of the cabin should be ensured during installation.
The three-party evolutionary game model of government, enterprises, and institutions of higher learning is established, and the dynamic evolution process of collaborative innovation behavior is discussed under the two strategies of “incentive” and “non-incentive” chosen by the government. The results show that under the premise of stronger innovation consciousness of the government and institutions and smaller the innovation cost of enterprises, the system is easier to reach the ideal state. The incentive degree of government should be controlled within a reasonable range to prevent enterprises from falling into a bad state because of the temptation of economic interests.
In the field of cranes, unreasonable structure design leads to high energy consumption. In order to solve the problems of heavy weight and serious steel consumption of a crane structure, a green energy-saving design method based on computational intelligence is proposed. For minimizing the weight of a structure, two optimization models are proposed. The specular reflection algorithm is used to make the green and lightweight design. A multi-objective optimization model for the green design is constructed. The minimum waste generated in the manufacturing process is the objective function of this model. Fuzzy mathematics theory is utilized to comprehensively evaluate the impact of crane structure weight and processing waste on the environment, and a structural optimization model with fuzzy comprehensive evaluation indicators for the green design is introduced. The results indicate that compared with the original design, the processing waste after fuzzy comprehensive optimization is 63.43% lower and the cross-sectional area of the main girder is reduced by 27.03%.
The operators of overhead traveling cranes experience discomfort as a result of the vibrations of crane structures. These vibrations are produced by defects in the rails on which the cranes move. To improve the comfort of operators, a nine-degree-of-freedom (nine-DOF) mathematical model of a “human–crane–rail” system was constructed. Based on the theoretical guidance provided in ISO 2631-1, an annoyance rate model was established, and quantization results were determined. A dynamic optimization design method for overhead traveling cranes is proposed. A particle swarm optimization (PSO) algorithm was used to optimize the crane structural design, with the structure parameters as the basic variables, the annoyance rate model as the objective function, and the acceleration amplitude and displacement amplitude of the crane as the constraint conditions. The proposed model and method were used to optimize the design of a double-girder 100 t–28.5 m casting crane, and the optimal parameters are obtained. The results show that optimization decreases the human annoyance rate from 28.3% to 9.8% and the root mean square of the weighted acceleration of human vibration from 0.59 m/s2to 0.38 m/s2. These results demonstrate the effectiveness and practical applicability of the models and method proposed in this paper.
The nominal values of structural design parameters are usually calculated using a traditional deterministic optimization design method. However, owing to the failure of this type of method to consider potential variations in design parameters, the theoretical design results can be far from reality. To address this problem, the specular reflection algorithm, a recent advancement in intelligence optimization, is used in conjunction with a robust design method based on sensitivity. This method not only is able to fully consider the influence of parameter uncertainty on the design results but also has strong applicability. The effectiveness of the proposed method is verified by numerical examples, and the results show that the robust design method can significantly improve the reliability of the structure.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.