TY - GEN
T1 - Parameter fault estimation in distributed heating/cooling systems
AU - Kurniawan, Wijaya
AU - Hangos, Katalin M.
AU - Marton, Lorinc
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/11/22
Y1 - 2022/11/22
N2 - In this paper, the problem of fault estimation and localization in the connecting dynamic elements of distributed heating and cooling systems are treated. The fault represents the physical parameter change related to the heat transfer between the system and the external environment. First, based on the bi-linear dynamic state space model of the system in the presence of a fault, structural observability analysis using Signed Directed Graph (SDG) has been performed to investigate the sensor placement problem. Then, a nonlinear observer with a parameter adaptation algorithm was proposed for fault estimation. The simulation results show that it can successfully detect and estimate the fault. Fault localization along the length of the element has also been attempted, but it has been found that the localization cannot be performed using practically changeable input variables. Frequency domain analysis is presented to discuss this phenomenon.
AB - In this paper, the problem of fault estimation and localization in the connecting dynamic elements of distributed heating and cooling systems are treated. The fault represents the physical parameter change related to the heat transfer between the system and the external environment. First, based on the bi-linear dynamic state space model of the system in the presence of a fault, structural observability analysis using Signed Directed Graph (SDG) has been performed to investigate the sensor placement problem. Then, a nonlinear observer with a parameter adaptation algorithm was proposed for fault estimation. The simulation results show that it can successfully detect and estimate the fault. Fault localization along the length of the element has also been attempted, but it has been found that the localization cannot be performed using practically changeable input variables. Frequency domain analysis is presented to discuss this phenomenon.
KW - Fault diagnosis
KW - Heating/cooling system
KW - Nonlinear Observer
KW - Parameter estimation
KW - Structural observability
UR - https://www.scopus.com/pages/publications/85146919796
U2 - 10.1145/3568231.3568256
DO - 10.1145/3568231.3568256
M3 - Conference contribution
AN - SCOPUS:85146919796
T3 - ACM International Conference Proceeding Series
SP - 111
EP - 118
BT - SIET 2022 - Proceedings of 7th International Conference on Sustainable Information Engineering and Technology 2022
PB - Association for Computing Machinery
T2 - 7th International Conference on Sustainable Information Engineering and Technology, SIET 2022
Y2 - 22 November 2022
ER -