矿井通风机运行状态诊断系统的应用分析
Application Analysis of Mine Ventilator Operation State Diagnosis System
张彦武1
作者信息
- 1. 山西离柳鑫瑞煤业有限公司,山西 吕梁 033299
- 折叠
摘要
针对矿井通风系统运行时缺乏故障诊断和预警机制导致风机运行时故障率高,给井下通风安全造成较大隐患的问题,提出了一种新的矿井通风机异常状态诊断系统.该系统通过时域特征参数、卷积神经网络判断的方式实现了对风机运行状态的自动诊断和分析.根据实际应用表明,该风机异常状态诊断系统对风机异常状态判断的准确性达到了 98.6％,极大地提升了风机运行的可靠性.
Abstract
Aiming at the lack of fault diagnosis and early warning mechanism during the operation of mine ventilation system,which leads to the high failure rate of fan operation and causes big hidden danger to the safety of underground ventilation,a new abnormal state diagnosis system for mine ventilation fan is proposed,which realizes the automatic diagnosis and analysis of the fan operation state by the way of the time domain feature parameter and the judgment of convolutional neural network.According to the practical application,the accuracy of the fan abnormal state diagnosis system in judging the abnormal state of the fan reaches 98.6％,which greatly improves the reliability of fan operation.
关键词
通风机/异常状态/自动诊断Key words
ventilator/abnormal state/automatic diagnosis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据