基于图像识别技术的刮板链故障检测方法研究

Research on Method for Fault Detection of Scraper Chain Based on Image Recognition Technology

煤矿井下刮板输送机链条断裂多发于使用初期磨合和后期疲劳阶段,主要由设备刮卡、链条磨损及变形引起。现有基于霍尔传感器和电感类接近开关的监测手段在复杂矿井环境下效果有限,尤其是在预测链条临近断裂状态方面。因此提出了采用图像识别技术的刮板链故障检测方法,详细介绍了该技术的基本原理与实际应用,旨在提高刮板链组件故障的识别精度和预警能力。

For scraper conveyor chains in underground coal mine,chain breakages predominantly occur during the initial running-in phase and later stages of fatigue,primarily due to equipment abrasion,chain wear and deformation.Current monitoring techniques using Hall sensors and inductive proximity switches have limited effect in complex mine environments,especially in predicting the pre-fracture state of chains.Therefore,proposed scraper chain fault detection method using the image recognition technology.Introduced the fundamental principles and practical applications of this technology in detail,so as to enhance the accuracy of fault identification and early warning capabilities for scraper chain component.