Abstract
Cooling fans are extensively used in industrial fields. However, performance degradation may cause serious damages to surrounding electronic devices. Hence, parameter identification and fan speed online diagnosis of the fan tray system are essential. To address parameter identification subject to measurement noise, an online filtering method is designed to alleviate the noise effect. A selection guide for the filtering coefficient is presented for improving the parameter identification results. Investigation shows that the filtering process for the nonlinear cooling fan parameter identification can be further reformulated by simple measurement equations. Based on this result, two well-known recursive algorithms can be integrated directly to realize the recursive version. Therefore, the limited on-board memory and computation time inefficiency issues can be solved for a cheap embedded system. Finally, numerical simulations as well as experiments are carried out to validate the feasibility of the proposed method for online parameters identification and speed diagnosis.
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