Fault Detection and Identification on Pneumatic Production Machine

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F22%3APU144499" target="_blank" >RIV/00216305:26210/22:PU144499 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/record/display.uri?eid=2-s2.0-85128757643&origin=resultslist&sort=plf-f&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT:1" target="_blank" >https://www.scopus.com/record/display.uri?eid=2-s2.0-85128757643&origin=resultslist&sort=plf-f&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT:1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-98260-7_3" target="_blank" >10.1007/978-3-030-98260-7_3</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fault Detection and Identification on Pneumatic Production Machine

Popis výsledku v původním jazyce

Pneumatic cylinders have become integral parts of today's production machinery. In the age of just-in-time inventory system and with it the related production process, new, increased requirements were introduced. As a result, even the smallest fault in the system can lead to degradation in the product's quality in addition to this it can cause unplanned downtime leading to delays in production, not to mention higher costs. The availability of cheap sensors, big data, and algorithms from the field of predictive maintenance made the aforementioned problem tractable. This paper examines whether signal-based condition indicators provide commercially viable and affordable basis for development of a health monitoring system for pneumatic actuator-based production machinery. The experiments and their results presented in this paper served two objectives. The first was to examine if faults on such equipment can be detected. The second was to identify the best combination of sensors, which are able to detect and identify fault with required accuracy. The evaluation of the sensors was not solely based on fault detection capabilities, but other practical aspects (price and durability of the sensors) were also taken into account.

Název v anglickém jazyce

Fault Detection and Identification on Pneumatic Production Machine

Popis výsledku anglicky

Pneumatic cylinders have become integral parts of today's production machinery. In the age of just-in-time inventory system and with it the related production process, new, increased requirements were introduced. As a result, even the smallest fault in the system can lead to degradation in the product's quality in addition to this it can cause unplanned downtime leading to delays in production, not to mention higher costs. The availability of cheap sensors, big data, and algorithms from the field of predictive maintenance made the aforementioned problem tractable. This paper examines whether signal-based condition indicators provide commercially viable and affordable basis for development of a health monitoring system for pneumatic actuator-based production machinery. The experiments and their results presented in this paper served two objectives. The first was to examine if faults on such equipment can be detected. The second was to identify the best combination of sensors, which are able to detect and identify fault with required accuracy. The evaluation of the sensors was not solely based on fault detection capabilities, but other practical aspects (price and durability of the sensors) were also taken into account.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

Modelling and Simulation for Autonomous Systems

ISBN

978-3-030-98260-7

ISSN

1611-3349

e-ISSN

—

Počet stran výsledku

22

Strana od-do

39-60

Název nakladatele

SPRINGER INTERNATIONAL PUBLISHING AG

Místo vydání

Virtual, Online

Místo konání akce

virtual

Datum konání akce

13. 10. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000787774900003