计算机集成制造系统 ›› 2021, Vol. 27 ›› Issue (4): 1099-1107.DOI: 10.13196/j.cims.2021.04.014

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基于工件注意力的车间作业行为在线识别方法

王佳铖,鲍劲松+,刘天元,李志强   

  1. 东华大学机械工程学院
  • 出版日期:2021-04-30 发布日期:2021-04-30
  • 基金资助:
    国家自然科学基金资助项目(51905091)。

Online method for worker operation recognition based on attention of workpiece

  • Online:2021-04-30 Published:2021-04-30
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.51905091).

摘要: 车间作业人员的行为在线监测对于提高车间数字化管理的能力至关重要。传统的识别方法仅通过人的行为信息作判断,忽略了工件对行为识别的辅助作用。鉴于车间中常出现的错乱工序和违规操作大多能通过工件的使用来体现,提出一种基于工件注意力的车间行为在线识别模型。该模型以门控循环单元(GRU)为基础模型对从监控视频中提取的人体关节序列进行检测;其次使用实例分割模型对车间常见工件进行预训练,并提取出视频中工件的语义特征;最后将工件特征作为注意力融入GRU基础模型的输入输出环节进行联合训练。在自建样本数据和公共数据集上进行实验,并使用时序交并比进行召回率与准确率的计算。实验结果表明,所提方法可对车间作业人员的行为进行有效监测。

关键词: 行为识别, 门控循环单元, 注意力机制, 工件特征

Abstract: The online recognition of the worker's operation is important to improve the ability of digital management in workshop.The traditional recognition method only makes the judgment through the human information,ignoring the auxiliary function of work piece to the operation recognition.Owing to the fact that the disorder of working procedure or the illegal operation could be reflected by workpiece utilization,an online operation recognition method based on the attention of workpiece was proposed.The Gated Recurrent Unit (GRU) model was used as the base model to recognize the human joint sequence detected from the monitoring video.Then the feature of the workpiece was extracted from the monitoring video by the pre-trained instance segmentation model.The workpiece features were viewed as attention information integrated into the basic GRU model for joint training.The experiments were performed in both self-built data sets and public data sets and used intersection over union in time to compute the precision and recall.The experimental results showed that the proposed method could effectively monitor the operations of worker.

Key words: operation recognition, gated recurrent unit, attention mechanism, workpiece features

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