A Distributed Fault Detection System based on IWSN for Machine Condition Monitoring

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00208770" target="_blank" >RIV/68407700:21230/14:00208770 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6661382" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6661382</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TII.2013.2290432" target="_blank" >10.1109/TII.2013.2290432</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Distributed Fault Detection System based on IWSN for Machine Condition Monitoring

Popis výsledku v původním jazyce

This paper introduces a novel framework for Industrial Wireless Sensor Networks used for Machine Condition Monitoring. Our approach enables the use of state-of-the-art computationally intensive classifiers in computationally weak sensor network nodes. The key idea is to split data acquisition, classifier building and training, and the operation phase, between different units. Computationally demanding processing is carried out in the central unit, while other tasks are distributed to the sensor nodes using over-the-air programming. The system is autonomously trained on the healthy state of a machine, and then monitors a change in behavior which indicates a faulty state. Thanks to one-class classification, there is no need to introduce the faulty stateof the machine in the training phase. We extend the diagnostic capability of the system using dynamic changes in the data acquisition and classification parts of the program in the sensor nodes. This enables the system to react to ambiguo

Název v anglickém jazyce

A Distributed Fault Detection System based on IWSN for Machine Condition Monitoring

Popis výsledku anglicky

This paper introduces a novel framework for Industrial Wireless Sensor Networks used for Machine Condition Monitoring. Our approach enables the use of state-of-the-art computationally intensive classifiers in computationally weak sensor network nodes. The key idea is to split data acquisition, classifier building and training, and the operation phase, between different units. Computationally demanding processing is carried out in the central unit, while other tasks are distributed to the sensor nodes using over-the-air programming. The system is autonomously trained on the healthy state of a machine, and then monitors a change in behavior which indicates a faulty state. Thanks to one-class classification, there is no need to introduce the faulty stateof the machine in the training phase. We extend the diagnostic capability of the system using dynamic changes in the data acquisition and classification parts of the program in the sensor nodes. This enables the system to react to ambiguo

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Industrial Informatics, IEEE Transactions on

ISSN

1551-3203

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

6

Strana od-do

1118-1123

Kód UT WoS článku

000336669800026

EID výsledku v databázi Scopus

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