DocumentCode :
1828117
Title :
PT01. Prognostics and systems health management within the Internet of Things
Author :
Pecht, Michael
Author_Institution :
Center for Adv. Life Cycle Eng. (CALCE), Univ. of Maryland, College Park, MD, USA
fYear :
2015
fDate :
7-10 March 2015
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.
Keywords :
Internet; Internet of Things; health care; security of data; Internet of Things; anomaly detection; in-situ assessment; operating condition; performance parameter; prognostics; sensor data; systems health management; Data models; Degradation; Internet of things; Monitoring; Physics; Prognostics and health management; Sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Physics and Technology of Sensors (ISPTS), 2015 2nd International Symposium on
Conference_Location :
Pune
Type :
conf
DOI :
10.1109/ISPTS.2015.7220157
Filename :
7220157
Link To Document :
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