Finite element analysis of lifting platform of spreader based on the ANSYS workbench

Shiyu Huang; Bing Li; Jiahua Zhao; Weiqian Gao; Yulan Wei; Yuxia Huang

doi:10.1117/12.2674825

2 May 2023 Finite element analysis of lifting platform of spreader based on the ANSYS workbench

Shiyu Huang, Bing Li, Jiahua Zhao, Weiqian Gao, Yulan Wei, Yuxia Huang

Proceedings Volume 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023); 1264236 (2023) https://doi.org/10.1117/12.2674825
Event: Second International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT 2023), 2023, Xishuangbanna, China

Abstract

To solve the safety hazards caused by easy tilting and manual decoupling of the lifting platform, such as large weight, unstable force, and uncertain stiffness and strength in the overall device, according to the development status of the existing lifting spreader, combined with its mechanical structure and the balance of carrying, the finite element analysis of the lifting platform is carried out with the help of ANSYS Workbench software to obtain the deformation influence and force value. After calculating the maximum stress value and maximum pressure point of the platform, the parameters of the lifting platform are determined in combination with the needs of the factory work. As a result of the finite element analysis, the maximum elastic strain of the platform is 1.112×10^-3 mm, the maximum stress is 222.42 MPa, and its safety factor value is within a reasonable range. Analysis and simulation are conducive to optimizing the accuracy of platform structural details, making the design more reasonable, and preventing serious consequences caused by platform bending.

Citation Download Citation

Shiyu Huang, Bing Li, Jiahua Zhao, Weiqian Gao, Yulan Wei, and Yuxia Huang "Finite element analysis of lifting platform of spreader based on the ANSYS workbench", Proc. SPIE 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023), 1264236 (2 May 2023); https://doi.org/10.1117/12.2674825

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