基于模糊逻辑的快速上肢评估方法(RULA)改进

Improvement of rapid upper limb assessment (RULA) based on fuzzy logic

摘要:

为更加有效地进行人机工效评估，基于模糊逻辑，对快速上肢评估(RULA)方法进行改进，以避免因为不精确的关节角度输入，产生差异较大的评估结果.利用梯形函数对关节角度、负荷和肌肉使用进行模糊化处理，利用三角形函数对RULA中间得分和最终得分进行模糊化表示，并选取重心平均法进行去模糊化.随机选取29个姿势进行相关性验证，结果表明：该方法和RULA的相关性为0.937(p＜0.01)，和工作体位分析系统(OWAS)相关性为0.725(p＜0.01)，能够良好地反应真实结果.通过运动捕捉实验，模拟控制台捕捉实验，获取12个操作姿势的精确关节数据进行分析，验证了该方法能够有效地改进RULA评估方法，并具有较高的可靠性，更有利于实现人机工效评估.

Abstract:

To prevent ergonomic injuries, proper assessment of ergonomic risk is a key to identify risk factors and modify work practice in a timely manner, and a fuzzy logical approach to posture-based ergonomic evaluation tools is proposed. Rapid Upper Limb Assessment (RULA) is selected as a case study to describe the fuzzy logic modelling of RULA scoring systems. The trapezoidal functions are used to represent the angle ranges of the inputs as well as the force and muscle use imposed on the worker, and the triangular functions are used for intermediate variables which represent the RULA intermediate scores and the final RULA total score. The results of validation reveal that the proposed system produces high correlation coefficients with RULA (0.937, p < 0.01) and OWAS (0.725, p < 0.01). By taking the control console of a enterprise as a case, two participants completed six separate operation tasks, the model was used to analyze 12 tasks. The result indicated that the model had high reliability and could help to minimize human errors in observation for reliable on-site ergonomic assessment.