刮板输送机监测的数据挖掘与可视化分析

Analysis of monitoring data mining and visualization of scraper conveyor

刮板输送机动力部及其它关键零部件均安装了传感器,这些传感器采集了大量煤矿生产现场的数据,如何利用这些数据更好地为客户提供维修服务,有效利用这些数据提供更好的决策支持,从中发现符合一定规律隐含的有用信息并服务于刮板输送机的设计制造,是我们重要的研究方向。将数据挖掘与可视化技术相结合以提高整个数据挖掘过程的交互性,剖析了不同传感器监测点数据之间的关联性、有效性,通过这些结论信息更好地用于硬件选型及设计。Python语言在数据挖掘领域有很大的优势,它编程自由灵活,语法表达优美易读,代码开发效率高,因此许多数据科学领域的从业者都使用Python做数据挖掘。

The power part and other key parts of scraper conveyor are equipped with sensors,which collect a large number of data of coal mine production.How to use these data to provide better maintenance service and decision support for customers,and to serve the design and manufacture of scraper conveyor is an important research direction.In order to improve the interactivity of the whole data mining process,by combining data mining technology with visualization technology,the relevance and effectiveness of sensor monitoring data are analyzed for hardware selection and design.Python language has many advantages in the field of data mining,such as free and flexible programming,beautiful syntax and easy to read,high efficiency of code development,which is widely used by many practitioners in data science field.