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基于煤矿井下钻机作业状态判别的钻杆计数方法

胡佳恒 董立红 秦昳

工矿自动化2025,Vol.51Issue(12):56-62,7.
工矿自动化2025,Vol.51Issue(12):56-62,7.DOI:10.13272/j.issn.1671-251x.2025050080

基于煤矿井下钻机作业状态判别的钻杆计数方法

A drill rod counting method based on underground coal mine drilling rig operation state identification

胡佳恒 1董立红 1秦昳1

作者信息

  • 1. 西安科技大学人工智能与计算机学院,陕西西安 710054
  • 折叠

摘要

Abstract

Existing vision-based drill rod counting methods for underground coal mines mostly rely on single or local visual features.When state transitions such as drilling advance,drilling retreat,and short pauses occur during drilling operations,accompanied by common underground interferences including complex illumination,target occlusion,and target jitter,the counting features may exhibit abnormal fluctuations,leading to miscounting or missed counts.To address these issues,a drill rod counting method based on underground coal mine drilling rig operation state identification was proposed.First,a lightweight object detection model was constructed by introducing a Large Separable Kernel Attention(LSKA)module,a Generalized Efficient Layer Aggregation Network(GELAN),and a DynamicHead into the YOLOv11 model to stably detect key components of the drilling rig(the chuck and the gripper).Then,the DeepSORT algorithm was used to continuously track the chuck and the gripper,obtain the relative distance variation curve between them,and smooth the curve using Kalman filtering to suppress noise.Finally,trough positions were extracted from the smoothed curve;drilling advance and drilling retreat states were identified according to the spacing between adjacent troughs,and troughs under the drilling advance state were accumulated to achieve drill rod counting.Experimental results showed that the improved YOLOv11 model achieved an mAP@0.5 of 0.966 and accurately detected targets under complex conditions such as complex illumination,target occlusion,and target jitter.The proposed method achieved an average accuracy of 97.97%,meeting the accuracy requirements for automatic drill rod counting in underground environments.

关键词

钻杆计数/钻机作业状态/目标检测/YOLOv11/DeepSORT/波谷计数

Key words

drill rod counting/drilling rig operation state/object detection/YOLOv11/DeepSORT/trough counting

分类

矿业与冶金

引用本文复制引用

胡佳恒,董立红,秦昳..基于煤矿井下钻机作业状态判别的钻杆计数方法[J].工矿自动化,2025,51(12):56-62,7.

基金项目

国家自然科学基金青年科学基金项目(62303375). (62303375)

工矿自动化

OA北大核心

1671-251X

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