煤炭工程 ›› 2015, Vol. 47 ›› Issue (1): 63-65.doi: 10.11799/ce201501020

• 生产技术 • 上一篇    下一篇

煤矿井下机械设备管理与故障诊断

董晓钧   

  1. 平煤神马建工集团安装处
  • 收稿日期:2014-01-18 修回日期:2014-01-30 出版日期:2015-01-10 发布日期:2015-01-10
  • 通讯作者: 董晓钧 E-mail:zhang_lin1116@126.com

Coal mine machinery and equipment management and fault diagnosis

  • Received:2014-01-18 Revised:2014-01-30 Online:2015-01-10 Published:2015-01-10

摘要: 针对当前机械设备的复杂化,且煤矿井下设备工作环境的多样性的特点,研究了一种基于专家系统和人工神经网络的机械设备故障诊断系统,该系统首先能够较精确的定位机械设备的故障,其次通过专家系统能够为故障提出解决方案,为维护人员提供参考,并且该系统具有能够对设备工作状态的实时监控的功能,为保障煤矿井下机械设备的安全正常运转提供保障,经实际测试,发现该系统具有较好的收敛性,经过6000次迭代,误差小于0.005,达到了实际工作的要求。

关键词: 井下机械设备, 故障诊断, 专家系统, 神经网络

Abstract: For complicated machinery and equipment, and the characteristics of the coal mine equipment diversity of the current work environment, a study based on expert systems and artificial neural network fault diagnosis system of mechanical equipment. Such a system can be more precise positioning mechanical equipment failures, followed by the fault can propose solutions through expert systems, to provide a reference for the maintenance personnel. And the system has a device capable of real-time monitoring of the work function of the state, to protect the safety of coal mine machinery functioning to provide protection.

Key words: Coal, Machinery and Equipment, Fault Diagnosis, Expert System, Neural Network

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