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
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TM84; TN911.7

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国家自然科学基金(51807110)


Research on Comfort Evaluation Method of insulating poles Based on sEMG and PSO-GA-SVM
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The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    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(sEMG)和混合算法优化支持向量机(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(EMD)对sEMG进行分解重构,引入基于希尔伯特黄变换(HHT)的平均瞬时功率(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。

    Abstract:

    In order to evaluate the comfort of insulating pole-like live working tools, a comfort evaluation method based on surface electromyography and hybrid optimized support vector machine is proposed. Four typical types of insulating poles are selected as the evaluation objects. Determine the biceps brachii muscle as the target muscle through human anatomy and collect surface electromyographys. The empirical mode decomposition is used to decompose and reconstruct the surface electromyography. The average instantaneous power based on Hilbert Huang transform is introduced as the characteristic parameter. Construct a support vector machine model optimized based on the PSO-GA hybrid algorithm to evaluate the comfort of insulating poles. The results show that when using different insulating poles , there are significant differences in the surface electromyography characteristic parameters and comfort index of the workers. The accuracy rate of the model is 93.5%, which can effectively evaluate the comfort of different insulating poles, and provide a reference for their optimization design to reduce the labor intensity of the workers and the risk of work-related musculoske-letal disorders.

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吴田,夏圆,刘志华. 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[J]. 科学技术与工程, 2022, 22(1): 228-235.
Wu Tian, Xia Yuan, Liu Zhihua. Research on Comfort Evaluation Method of insulating poles Based on sEMG and PSO-GA-SVM[J]. Science Technology and Engineering,2022,22(1):228-235.

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  • 收稿日期:2021-07-14
  • 最后修改日期:2021-12-24
  • 录用日期:2021-08-26
  • 在线发布日期: 2022-01-11
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