首页> 外文会议>International Conference on Mechatronics and Intelligent Materials >Lube Intelligent Diagnosis System Combining Bayesian and BP network based on IOT technology
【24h】

Lube Intelligent Diagnosis System Combining Bayesian and BP network based on IOT technology

机译:基于物联网技术的贝叶斯和BP网络结合润滑智能诊断系统

获取原文

摘要

The existing industrial lubrication depend on experience judgment, off-line inspection and regular oil change, whose maintenance requires rich personnel experience and still always have many errors. Line monitoring and quality diagnosis for industrial lube were studied to establish the distributed the online monitoring system based on hierarchical structure, information fusion diagnostic system based on Bayesian network and BP neural network. The filtering system for industrial lube has been developed to achieve unattended, automatic operation purposes, and trialed in the metallurgical industry. The results show monitoring data is stable, reliable, and the problem of high water content of lube in the steel industry is solved. At the same -time, lube filtering is transformed from the traditional blind continuous filtering to real-time targeted filtering. In the premise of guaranteeing the lube quality, the system can save electricity more than 30%.
机译:现有的工业润滑取决于经验判断,离线检查和规则的石油变化,其维护需要丰富的人员经验,并且仍然总是有很多错误。研究了工业润滑油的线路监测和质量诊断,建立了基于层次结构的分布式在线监测系统,基于贝叶斯网络和BP神经网络的信息融合诊断系统。已经开发出用于工业润滑油的过滤系统,以实现无人看管的自动运行目的,并在冶金工业中试验。结果表明监测数据稳定,可靠,钢铁工业中润滑油高含水量的问题得到了解决。与此同时,润滑油过滤从传统的盲连续滤波转换为实时瞄准过滤。在保证润滑油质量的前提下,系统可以节省30%以上的电力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号