PT01. Prognostics and systems health management within the Internet of Things

M. Pecht
{"title":"PT01. Prognostics and systems health management within the Internet of Things","authors":"M. Pecht","doi":"10.1109/ISPTS.2015.7220157","DOIUrl":null,"url":null,"abstract":"Prognostics and health management is a method within the concepts of the Internet of Things, that permits the assessment of a system under its actual application conditions. It integrates sensor data with models that enable in-situ assessment of the “health” (e.g. deviation or degradation) of a system from an expected normal operating condition and also predicts the future state of the system based on current and historic conditions. This presentation discusses some methods used for anomaly detection and prognostics, including the monitoring and reasoning of parameters that are precursors to impending “failure”, such as shifts in performance parameters; and the modeling of stress and damage utilizing life cycle loads (e.g., usage, temperature, vibration, radiation). Examples of implementation methods and results are given.","PeriodicalId":6520,"journal":{"name":"2015 2nd International Symposium on Physics and Technology of Sensors (ISPTS)","volume":"26 1","pages":"i-i"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 2nd International Symposium on Physics and Technology of Sensors (ISPTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPTS.2015.7220157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Prognostics and health management is a method within the concepts of the Internet of Things, that permits the assessment of a system under its actual application conditions. It integrates sensor data with models that enable in-situ assessment of the “health” (e.g. deviation or degradation) of a system from an expected normal operating condition and also predicts the future state of the system based on current and historic conditions. This presentation discusses some methods used for anomaly detection and prognostics, including the monitoring and reasoning of parameters that are precursors to impending “failure”, such as shifts in performance parameters; and the modeling of stress and damage utilizing life cycle loads (e.g., usage, temperature, vibration, radiation). Examples of implementation methods and results are given.
PT01。物联网中的预测和系统健康管理
预测和健康管理是物联网概念中的一种方法,允许在实际应用条件下对系统进行评估。它将传感器数据与模型相结合,能够对系统的“健康状况”(例如偏差或退化)进行现场评估,使其脱离预期的正常运行状态,并根据当前和历史条件预测系统的未来状态。本报告讨论了用于异常检测和预测的一些方法,包括对即将发生“故障”的前兆参数的监测和推理,例如性能参数的变化;以及利用生命周期载荷(例如,使用、温度、振动、辐射)对应力和损伤进行建模。给出了实现方法和结果的实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信