TY - GEN
T1 - Dynamics modeling and parameter identification of a cooling fan system
AU - Peng, Chao Chung
AU - Lin, Yung I.
N1 - Funding Information:
This work was supported in part by the Ministry of Science and Technology under Grant No. MOST 106-2218-E-006-004 and MOST 107-2221-E-006-114-MY3.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Cooling fan system has been widely used in industrial equipment such as computation host, product line junction box, manufacturing facilities, CNC machining systems and many other power cooling systems. Those systems usually involve high computation power and unavoidably release high dense heat. In order to guarantee long-term performance and healthy status of the kernel operation systems, surrounding temperature is going be controlled through the cooling fan systems. Once the cooling fan system is malfunctioned or the cooling efficiency is degraded, it could cause damage to the core operation system or lower its performance. Therefore, to prevent this condition, status of the cooling fan systems needs be monitored. In this paper, dynamics modeling and parameter identification of a cooling fan system is presented. Once the parameters can be precisely estimated, it can be extended for on-line health monitoring and diagnosis applications. To this aim, modeling of the cooling fan is firstly derived. In this paper, three discrete approximation models are derived for the parameter estimation. Finally, numerical studies are carried to verify the feasibility of the proposed identification method.
AB - Cooling fan system has been widely used in industrial equipment such as computation host, product line junction box, manufacturing facilities, CNC machining systems and many other power cooling systems. Those systems usually involve high computation power and unavoidably release high dense heat. In order to guarantee long-term performance and healthy status of the kernel operation systems, surrounding temperature is going be controlled through the cooling fan systems. Once the cooling fan system is malfunctioned or the cooling efficiency is degraded, it could cause damage to the core operation system or lower its performance. Therefore, to prevent this condition, status of the cooling fan systems needs be monitored. In this paper, dynamics modeling and parameter identification of a cooling fan system is presented. Once the parameters can be precisely estimated, it can be extended for on-line health monitoring and diagnosis applications. To this aim, modeling of the cooling fan is firstly derived. In this paper, three discrete approximation models are derived for the parameter estimation. Finally, numerical studies are carried to verify the feasibility of the proposed identification method.
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U2 - 10.1109/AMCON.2018.8614957
DO - 10.1109/AMCON.2018.8614957
M3 - Conference contribution
AN - SCOPUS:85062236497
T3 - Proceedings of the 2018 IEEE International Conference on Advanced Manufacturing, ICAM 2018
SP - 257
EP - 260
BT - Proceedings of the 2018 IEEE International Conference on Advanced Manufacturing, ICAM 2018
A2 - Meen, Teen-Hang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Advanced Manufacturing, ICAM 2018
Y2 - 16 November 2018 through 18 November 2018
ER -