基于表面肌电和混合算法优化支持向量机的绝缘杆类工器具舒适度评估方法

Comfort Evaluation Method of Insulating Poles Based on sEMG and PSO-GA-SVM

为评估绝缘杆类带电作业工器具的舒适性,提出基于表面肌电信号(surface electromyography,sEMG)和混合算法优化支持向量机(particle swarm optimization-genetic algorithm-support vector machines,PSO-GA-SVM)的舒适度评估方法。选取了4种典型绝缘杆类工器具作为评估对象,通过人体解剖学确定肱二头肌为目标肌肉并采集sEMG信号,运用经验模态分解(empirical mode decomposition,EMD)对sEMG进行分解重构,引入基于希尔伯特黄变换(Hilbert-Huang transform,HHT)的平均瞬时功率(averaged instantaneous frequency,AIF)作为特征参数,构建了基于混合算法优化支持向量机的评估模型,对绝缘杆类工器具的舒适度进行评估。结果表明:使用不同绝缘杆类工器具时,作业人员sEMG特征参数及舒适度指数有显著差异;模型的准确率为93.5%,可有效量化评估绝缘杆类工器具的舒适度,并为其优化设计提供参考依据,以降低作业人员的劳动强度和罹患肌肉骨骼疾病的风险。

In order to evaluate the comfort of insulating pole-like live working tools,a comfort evaluation method based on surface electromyography(sEMG)and hybrid optimized support vector machine was proposed.Four typical types of insulating poles were selected as the evaluation objects.The biceps brachii muscle was determined as the target muscle through human anatomy,and the sEMG signal was collected.The empirical mode decomposition(EMD)was used to decompose and reconstruct the surface electromyography.The average instantaneous(AIF)power based on Hilbert-Huang transform(HHT)were introduced as the characteristic parameter.An evaluation model based on hybrid algorithm optimization support vector machine was constructed to evaluate the comfort of insulated rod tools and instruments.The results show that there are significant differences in sEMG characteristic parameters and comfort index of operators when using different insulating rod tools and instruments.The accuracy of the model is 93.5%,which can effectively quantitatively evaluate the comfort of insulated rod tools and instruments,and provide a reference basis for their optimal design,so as to reduce the labor intensity of operators and the risk of musculoskeletal diseases.