摘要
基于目标检测技术的强磁机系统异常识别在工业和生产现场扮演着重要角色。强磁机系统广泛应用于矿业等领域,其正常运行对生产过程至关重要。目标检测算法有助于准确定位和标记强磁机系统的异常区域,及时发现问题,降低维修成本,避免突发事件的发生。通过建立深度学习的目标检测模型,能够更好地学习和捕捉不同异常情况下的特征,实现对异常情况的精准检测。基于此,本文结合知识蒸馏技术,构建了轻量化目标检测算法。该方法能够完成强磁机系统异常识别,实现工业设备的智能监测和预防性维护,提高生产效率和设备可靠性。
The anomaly recognition of strong magnetic machine systems based on object detection technology plays an important role in industrial and production sites.The strong magnetic machine system is widely used in mining and other fields,and its normal operation is crucial to the production process.Object detection algorithms help accurately locate and mark abnormal areas in strong magnetic machine systems,detect problems in a timely manner,reduce maintenance costs,and avoid the occurrence of emergencies.By establishing a deep learning object detection model,it is possible to better learn and capture features under different abnormal conditions,achieving accurate detection of abnormal situations.Based on this,this article combines knowledge distillation technology to construct a lightweight object detection algorithm.This method can identify anomalies in strong magnetic machine systems,achieve intelligent monitoring and preventive maintenance of industrial equipment,and improve production efficiency and equipment reliability.
作者
徐凯
刘嘉奇
侯卫钢
石连跃
左逢源
XU Kai;LIU Jiaqi;HOU Weigang;SHI Lianyue;ZUO Fengyuan(Equipment Operation and Maintenance Center of Guanbaoshan Mining Co.,Ltd.,Anshan Liaoning 114000;Ansteel Group Mining Co.,Ltd.,Anshan Liaoning 114000;Ansteel Group Mining Design and Research Institute Co.,Ltd.,Anshan Liaoning 114000;Ansteel Mining Machinery Manufacturing Co.,Ltd.,Anshan Liaoning 114000;College of Information Science and Engineering,Northeastern University,Shenyang Liaoning 110819)
出处
《中国科技纵横》
2025年第4期88-90,共3页
China Science & Technology Overview
关键词
智能监控
损伤检测
强磁机系统
目标检测
intelligent monitoring
damage detection
strong magnetic machine system
object detection
