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负载自适应重力平衡机构的建模与基于生成式人工智能的设计

Modeling and Generative-AI-Based Design of Load-Adaptive Gravity Balancing Mechanisms

Ryotaro Kayawake, Kazuki Abe, Shota Miyake, Masahiro Watanabe, Kenjiro Tadakuma

arXiv 2609.31386首次发表:更新:

发表机构

Tohoku University; The University of Osaka(东北大学; 大阪大学)

机构由 AI 辅助整理,请以论文原文为准。

AI 中文总结

本文提出一种基于生成式人工智能的负载自适应重力平衡机构通用设计方法,通过势函数中间表示生成候选设计方案,无需预设机构架构。

AI 中文摘要

负载自适应重力平衡机构(LA-GBMs)能够通过被动地改变自身特性以响应载荷变化,从而适应各种负载条件。然而,其设计较为困难,因为必须同时满足期望的机构运动以及在可变载荷下的静态平衡。本研究提出了一种不依赖于特定机构架构或机械元件的LA-GBMs通用设计方法。本文阐述了LA-GBMs势场存在的必要条件,并推导出两种通用形式:一种表示载荷质量效应的仿射形式,以及一种表示与负载自适应和重力平衡相关的状态转换的分解形式。随后,将这些形式作为设计需求提供给生成式人工智能,以生成候选势函数。对生成的函数进行了解析验证,检查其是否符合上述两种通用形式以及有效LA-GBMs所需的条件。此外,将获得的势函数分解为各个项,并给出了一种通过组合弹簧、配重和函数生成连杆机构来构建LA-GBM的方法示例。通过使用势函数作为中间表示,所提出的框架无需预先指定机构架构即可生成LA-GBM设计候选方案。所生成势场的机械可实现性和可制造性仍是未来工作的重要问题。

英文摘要

Load-adaptive gravity balancing mechanisms (LA-GBMs) can accommodate various loading conditions by passively changing their characteristics in response to payload variations. However, their design is difficult because both the desired mechanism motion and static equilibrium under variable payloads must be satisfied simultaneously. This study proposes a general design methodology for LA-GBMs that does not depend on specific mechanism architectures or mechanical elements. The necessary conditions for the potential fields of LA-GBMs are formulated, and two general forms are derived: an affine form representing the effect of payload mass and a factorized form representing state transitions associated with load adaptation and gravity balancing. These forms are then provided to generative AI as design requirements to generate candidate potential functions. The generated functions are analytically verified in terms of their conformity to the two general forms and the conditions required for valid LA-GBMs. Furthermore, the obtained potential functions are decomposed into individual terms, and an example of a method for constructing an LA-GBM by combining springs, counterweights, and function-generating linkage mechanisms is presented. By using potential functions as an intermediate representation, the proposed framework enables the generation of LA-GBM design candidates without prescribing a mechanism architecture in advance. Mechanical realizability and manufacturability of the generated potential fields remain important issues for future work.

Comments13 pages, 9 figures. To be submitted to the Journal of Mechanical Design

论文原文

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