摘要
煤炭带式输送机容易发生偏移现象,导致安全事故发生,应用计算机视觉技术监测其偏移故障,通过监控设备采集井下输送机作业视频图像,结合加权引导滤波与双边滤波算法实现对采集图像的增强去噪处理,运用Canny算子检测处理后图像的边缘,通过霍夫变换算法由边缘检测后图像内提取出输送带的边缘直线特征,运算出边缘直线斜率值,依据所设定的斜率范围判别输送带是否出现偏移故障。结果表明,该方法有效监测传送带的扭动偏移故障,为煤炭企业工作的安全提供保障。
Coal belt conveyors are prone to deviation,leading to safety accidents.Computer vision technology is used to monitor the deviation faults.The video image of underground conveyor operation is collected through the monitoring equipment,and the enhanced denoising of the collected image is realized by combining weighted guidance filtering and bilateral filtering algorithm,Canny operator is used to detect the edge of the processed image,the edge straight line feature of the conveyor belt is extracted from the image after edge detection through Hough transform algorithm,the edge straight line slope value is calculated,and whether the conveyor belt has offset fault is judged according to the set slope range.The results show that the method effectively monitors the twisting and deviation faults of the conveyor belt,and provides a guarantee for the safety of coal enterprises.
作者
吴丽
WU Li(Wuxi Vocational College of Science and Technology,Wuxi 214028,China)
出处
《煤炭技术》
CAS
北大核心
2022年第7期202-205,共4页
Coal Technology
基金
2020江苏省高等学校自然科学研究面上项目(17KJB510051)。
关键词
计算机安全
煤炭企业
图像增强
去噪处理
边缘检测
computer security
coal enterprises
image enhancement
denoising processing
edge detection
