煤炭工程 ›› 2020, Vol. 52 ›› Issue (3): 127-131.doi: 10.11799/ce202003026

• 研究探讨 • 上一篇    下一篇

采煤机运行状态数据实时清洗技术研究

曹现刚,姜韦光,张国祯   

  1. 西安科技大学
  • 收稿日期:2019-04-17 修回日期:2019-08-24 出版日期:2020-03-10 发布日期:2020-05-11
  • 通讯作者: 姜韦光 E-mail:931776574@qq.com

Research of Real-time Data Cleaning Technology of Coal Mining Machine Operating Status

  • Received:2019-04-17 Revised:2019-08-24 Online:2020-03-10 Published:2020-05-11

摘要: 针对采煤机传动系统运行状态数据存在噪声点、缺失值的问题,建立了一种基于Storm的数据实时清洗平台。该平台使用ARIMA建立数据清洗模型,利用Storm中的Spout组件实时读取测点数据,将数据根据设定的样本容量进行封装并传递给Bolt组件,Bolt组件则完成噪声点判定、平稳化处理以及模型选参等具体的数据清洗工作。通过实验证明,该平台能够完成采煤机传动系统运行状态数据的实时清洗工作。

关键词: 采煤机, 数据清洗, 实时性, ARIMA, Storm

Abstract: Aiming at the problem of noise point and missing value in the operating status data of the coal mining machine drive system, a real-time data cleaning platform based on Storm is established. The platform uses ARIMA to establish a data cleaning model, uses the Spout component in Storm to read the point data in real time, encapsulates the data according to the set sample capacity and passes it to the Bolt component, and the Bolt component performs noise point determination, smoothing processing, model selection and other specific data cleaning tasks. The experiment proves that the platform can complete the real-time cleaning of the operating status data of the coal mining machine drive system.

中图分类号: