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The environment of production site in industrial enterprises is complex and dangerous, so operating personnel is required to wear labour protection appliance to ensure to be protected against personal injury in the operation process. In this paper, a detection system for personnel to wear labour protection appliance based on deep learning is designed to detect such objects as the personnel, safety helmet and CO alarm apparatus in the image as well as normalize the inference algorithm of wearing based on the deep learning object detection model so that the automatic identification of wearing labor protection appliance for operating personnel is realized and the accuracy rate is over 90%.

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工业企业生产现场环境复杂、具有一定的危险性，要求作业人员穿戴劳保用品以保证作业过程不受人身伤害。文章设计了基于深度学习人员劳保用品佩戴检测系统，基于深度学习目标检测模型，检测图像中的人员、安全帽、CO报警仪等目标和规范佩戴推断算法，实现了作业人员劳保用品佩戴自动识别，准确率达到90%以上。

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芦建文（1969-），男，山西省朔州市人，硕士，高级工程师，从事计算机与自动化工作。

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芦建文（1969-），男，山西省朔州市人，硕士，高级工程师，从事计算机与自动化工作。

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