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基于优化的人体力学搬运模型在手工物料搬运中的应用:综述。

Optimization-based biomechanical lifting models for manual material handling: A comprehensive review.

机构信息

School of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK, USA.

Human-Centric Design Research Lab, Department of Mechanical Engineering, Texas Tech University, Lubbock, TX, USA.

出版信息

Proc Inst Mech Eng H. 2022 Sep;236(9):1273-1287. doi: 10.1177/09544119221114208. Epub 2022 Jul 26.

Abstract

Lifting is a main task for manual material handling (MMH), and it is also associated with lower back pain. There are many studies in the literature on predicting lifting strategies, optimizing lifting motions, and reducing lower back injury risks. This survey focuses on optimization-based biomechanical lifting models for MMH. The models can be classified as two-dimensional and three-dimensional models, as well as skeletal and musculoskeletal models. The optimization formulations for lifting simulations with various cost functions and constraints are reviewed. The corresponding equations of motion and sensitivity analysis are briefly summarized. Different optimization algorithms are utilized to solve the lifting optimization problem, such as sequential quadratic programming, genetic algorithm, and particle swarm optimization. Finally, the applications of the optimization-based lifting models to digital human modeling which refers to modeling and simulation of humans in a virtual environment, back injury prevention, and ergonomic safety design are summarized.

摘要

举升是手动物料搬运(MMH)的主要任务,它也与下腰痛有关。文献中有许多关于预测举升策略、优化举升动作和降低下背部受伤风险的研究。本调查侧重于基于优化的 MMH 生物力学举升模型。这些模型可以分为二维和三维模型,以及骨骼和肌肉骨骼模型。本文回顾了具有各种成本函数和约束的举升模拟的优化公式。简要总结了相应的运动方程和敏感性分析。不同的优化算法被用于解决举升优化问题,例如序列二次规划、遗传算法和粒子群优化。最后,总结了基于优化的举升模型在数字人体建模(指在虚拟环境中对人体进行建模和模拟)、背部损伤预防和人体工程学安全设计中的应用。

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