论文部分内容阅读
为实现在线磨损状态监测技术在矿用减速器的工程应用,进行了在线铁谱磨粒特征与减速器磨损状态的映射关系的研究。首先,利用在线铁谱图像自动采集系统获取磨粒图像。进而利用数字图像处理技术获取磨损颗粒信息,主要包括:采用Otsu’s自动阈值分割法将目标磨粒从图像背景中分离出来;通过像素扫描和边缘检测等方法提取磨粒的相对浓度和最大宽度尺寸信息。最后,获取设备运行过程中磨粒的统计学特征在时间序列上的变化趋势,实现矿用减速器的磨损状态在线分析。所提出的方法通过在线磨损的工程试验结果进行了有效性验证,为矿用设备的自动化监测与智能维护提供了新的技术手段。
In order to realize the application of on-line wear status monitoring technology in mine retarder, the mapping relationship between on-line iron particle wear characteristics and retarder wear status was studied. First of all, the use of online ferrographic image automatic acquisition system to obtain abrasive images. Then, the wear particle information is acquired by using digital image processing technology, including: the Otsu’s automatic threshold segmentation method is used to separate the target abrasive from the image background; the relative concentration and the maximum width size information of the abrasive particles are extracted by pixel scanning and edge detection . Finally, the trends of the statistical characteristics of the abrasive grains in the process of operation are obtained and the on-line analysis of the wear status of the mining retarder is achieved. The proposed method is validated through the engineering test results of on-line wear, which provides a new technical measure for the automatic monitoring and intelligent maintenance of mining equipment.