TY - GEN
T1 - Sensor-based modeling of radial fans
AU - Holzinger, Florian Christian
AU - Kommenda, Michael
AU - Strumpf, Erik
AU - Langer, Josef
AU - Zenisek, Jan
AU - Affenzeller, Michael
N1 - Publisher Copyright:
© Institute of Information Science. All rights reserved.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2018
Y1 - 2018
N2 - Predictive maintenance poses a new way to minimize costs and downtime of machinery. The combination of sensor data, intelligent algorithms and computing power allows this new approach to monitor the current health-state of machinery and detect possible failures early on or even in advance. Previous work in this field regarding radial fans focused on aspects such as vibration and noise, whereas this paper concentrates on the influence of multiple sensor data when modeling radial fans. In a case study multiple sensors are mounted on a radial fan and the importance of their signals on damage prediction is presented. The correlation between them is analyzed and the variable impact of sensor signals for approximating the rotational speed of a healthy and a damaged radial fan is identified.
AB - Predictive maintenance poses a new way to minimize costs and downtime of machinery. The combination of sensor data, intelligent algorithms and computing power allows this new approach to monitor the current health-state of machinery and detect possible failures early on or even in advance. Previous work in this field regarding radial fans focused on aspects such as vibration and noise, whereas this paper concentrates on the influence of multiple sensor data when modeling radial fans. In a case study multiple sensors are mounted on a radial fan and the importance of their signals on damage prediction is presented. The correlation between them is analyzed and the variable impact of sensor signals for approximating the rotational speed of a healthy and a damaged radial fan is identified.
KW - Condition Monitoring
KW - Predictive Maintenance
KW - Radial Fans
UR - http://www.scopus.com/inward/record.url?scp=85056697950&partnerID=8YFLogxK
M3 - Conference contribution
SN - 978-88-85741-03-4
T3 - 30th European Modeling and Simulation Symposium, EMSS 2018
SP - 322
EP - 330
BT - 30th European Modeling and Simulation Symposium, EMSS 2018
A2 - Merkuryev, Yuri
A2 - Piera, Miquel Angel
A2 - Longo, Francesco
A2 - Bruzzone, Agostino G.
A2 - Affenzeller, Michael
A2 - Jimenez, Emilio
PB - DIME UNIVERSITY OF GENOA
T2 - 30th European Modeling and Simulation Symposium, EMSS 2018
Y2 - 17 September 2018 through 19 September 2018
ER -