煤炭工程 ›› 2021, Vol. 53 ›› Issue (5): 28-34.doi: 10.11799/ce202105006

• 设计技术 • 上一篇    下一篇

大型储煤筒仓输煤智能化监控系统设计

刘喆1,马岩岩1,赵晏博1,邵建林1,尹丽辉1,邓旭2,张凯2   

  1. 1. 三河发电有限责任公司
    2. 中国矿业大学(北京)
  • 收稿日期:2020-10-19 修回日期:2021-01-04 出版日期:2021-05-20 发布日期:2021-05-17
  • 通讯作者: 张凯 E-mail:zhangkai@cumtb.edu.cn

Design of Intelligent Monitoring System for Coal Transportation in Large Coal Storage Silo

  • Received:2020-10-19 Revised:2021-01-04 Online:2021-05-20 Published:2021-05-17

摘要: 针对目前大型储煤筒仓输煤过程监控功能不完善、智能化程度不高的问题,设计了大型储煤筒仓输煤智能化监控系统,包括数据获取、机器人巡检、实时预测、趋势预测、故障判别、报警管理、历史回放、系统管理等模块。引入卷积神经网络和人工神经网络对输煤胶带状态进行建模,提出设备单一指标维度和残差指标来判断设备的异常状态,实现了对设备状态的实时准确预测和异常判断。完成了三河电厂储煤筒仓、碎煤机、给煤机、带式输送机等设备的智能监控改造,提高了自动化监管和控制水平,最大限度的减少了运行操作人员,促进了公司智能化经营,降低了运维成本提高了生产效率。

关键词: 智能输煤系统, 人工智能控制, 单一指标, 残差

Abstract: Aiming at the problem of imperfect monitoring function and low intelligence of coal transportation process in large coal storage silos, an intelligent monitoring system for coal transportation of large coal storage silos is designed, including data acquisition, robot inspection, real-time prediction, and trend prediction, fault identification, alarm management, historical playback, system management and other modules. Convolutional neural network and artificial neural network are introduced to model the equipment state, and a single indicator dimension and residual index of the equipment are proposed to judge the abnormal state of the equipment. The real-time accurate prediction and abnormal judgment of the equipment state are realized. The intelligent monitoring transformation of the Sanhe Power Plant’s coal storage silos, coal crushers, coal feeders, belts and other equipment are completed. The system improved the level of automated supervision and control, minimized operating personnel, and promoted the company’s intelligent operation. Moreover operation and maintenance costs are reduced, the production efficiency is improved.

中图分类号: