输送带跑偏故障的机器视觉检测技术

杨彦利; 苗长云; 亢伉; 李现国

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输送带跑偏故障的机器视觉检测技术

机械与动力工程 | 更新时间：2026-09-14

- 输送带跑偏故障的机器视觉检测技术
- Machine Vision Inspection Technique for Conveyor Belt Deviation
- 中北大学学报（自然科学版） 2012年33卷第6期页码：667-671
- 作者机构：
  
  天津工业大学电子与信息工程学院
- 作者简介：
- 基金信息：
  
  天津市自然科学基金重点资助项目(12JCZDJC27800)
- DOI：
  中图分类号：
- 纸质出版：2012
- 稿件说明：
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杨彦利, 苗长云, 亢伉, 等. 输送带跑偏故障的机器视觉检测技术[J]. 中北大学学报（自然科学版）, 2012,33(6):667-671.

杨彦利, 苗长云, 亢伉, et al. Machine Vision Inspection Technique for Conveyor Belt Deviation[J]. 2012, 33(6): 667-671.
杨彦利, 苗长云, 亢伉, 等. 输送带跑偏故障的机器视觉检测技术[J]. 中北大学学报（自然科学版）, 2012,33(6):667-671. DOI：

杨彦利, 苗长云, 亢伉, et al. Machine Vision Inspection Technique for Conveyor Belt Deviation[J]. 2012, 33(6): 667-671. DOI：

摘要

针对矿用输送机运行过程中易发生跑偏的工程背景

研究了基于机器视觉的输送带跑偏故障检测.采用线阵CCD相机实时采集输送带图像

经二值化处理后

从二值图像中提取故障特征来识别跑偏故障.着重分析了输送带图像的快速处理和故障识别方法

提出了一种灰度平均法用于输送带与背景的快速分割;通过将二值图像映射为一维故障特征函数

设计了由跑偏角和偏移量构成的跑偏特征向量用于跑偏检测.开发了一个输送带跑偏故障视觉在线检测系统

实验室测试结果验证了该监测系统的有效性.

Abstract

Under the background that mining conveyor belts are prone to deviation in operation

a belt deviation detection technique based on machine vision was investigated.The digital images were captured through a line CCD camera.The fault of belt deviation was identified by using features extracted from binary images after binary processing.The fast image processing method and the fault identification method were analyzed in detail.The average graying method was proposed as a fast image segmentation algorithm and the deviation feature vector composed by deviation degrees and by offsets was designed to inspect belt deviation through mapping the binary image to a fault eigenfunction.An on-line vision inspection system for conveyor belt deviation detection was developed.The laboratory testing results testify the validity of the inspection system.

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references

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