首页> 外文会议>Recent advances in signal processing, robotics and automation >Fault Detection and Diagnosis of Distributed Parameter Systems Based on Sensor Networks and Artificial Intelligence
【24h】

Fault Detection and Diagnosis of Distributed Parameter Systems Based on Sensor Networks and Artificial Intelligence

机译:基于传感器网络和人工智能的分布式参数系统故障检测与诊断

获取原文
获取原文并翻译 | 示例

摘要

This paper presents some approaches on the new applications in fault estimation, detection and diagnosis emerged from three powerful concepts: theory of distributed parameter systems, applied to large and complex physical processes, artificial intelligence, with its tool adaptive-network-based fuzzy inference and the intelligent wireless ad-hoc sensor networks. Sensor networks have large and successful applications in the real world. They may be placed in the areas of distributed parameter systems, to be seen as a "distributed measuring sensor" for the physical variables. Using sensor networks multivariable estimation techniques may be applied in distributed parameter systems. Fault detection and diagnosis in distributed parameter systems become more easily and more performing using these concepts. The paper presents some applications in fault detection and diagnosis based on the adaptive-network-based fuzzy inference, allows treatment of large and complex systems with many variables by learning and extrapolation.
机译:本文介绍了从以下三个强大的概念中出现的在故障估计,检测和诊断中的新应用的一些方法:分布式参数系统的理论,应用于大型和复杂的物理过程,人工智能,其工具基于自适应网络的模糊推理和智能无线自组织传感器网络。传感器网络在现实世界中拥有大量成功的应用程序。它们可以放置在分布式参数系统的区域中,被视为物理变量的“分布式测量传感器”。使用传感器网络,可以将多变量估计技术应用于分布式参数系统中。使用这些概念,分布式参数系统中的故障检测和诊断将变得更加容易且性能更高。本文介绍了基于自适应网络的模糊推理在故障检测和诊断中的一些应用,通过学习和外推可以处理具有多个变量的大型复杂系统。

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