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The Rapid Identification and Evaluation of the Resonant Noise of a Cooling Module Based on the Frequency Difference Sensitivity Method.
- Source :
-
Sensors (14248220) . Dec2023, Vol. 23 Issue 23, p9568. 19p. - Publication Year :
- 2023
-
Abstract
- The energy amplification factor transmitted from the excitation source to the response end cannot be identified quickly and accurately using the method of obtaining modal frequency combined with damping through modal frequency resonance. As a result, the above method cannot be used to further evaluate the effect of structural improvement. In this paper, a frequency difference sensitivity method is proposed in order to improve the efficiency of the above identification and evaluation processes while also guaranteeing accuracy. Firstly, a theoretical model suitable for the damping and rigid-body-mode frequency range of the cooling module is established according to the frequency difference between the excitation frequency,.system mode frequency, and vibration response sensitivity. Then, the accuracy and effect of the model are studied from the perspective of a simulation and experiment. The model can be used to identify and evaluate the resonance problem of the vehicle cooling module quickly and accurately. The energy amplification factor of the fan to the passive end of the cooling module can be efficiently predicted using the frequency difference sensitivity method proposed in this paper while ensuring accuracy. The quantized noise-reduction effect of the interior before and after the improvement can be efficiently predicted and evaluated using said model. The literature shows that the resonance of a vehicle cooling module can be identified and evaluated quickly and accurately via the frequency difference sensitivity method, which can overcome the problems that the conventional modal frequency resonance method encounters in identifying and evaluating quickly. [ABSTRACT FROM AUTHOR]
- Subjects :
- *NOISE
*STOCHASTIC resonance
Subjects
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 23
- Issue :
- 23
- Database :
- Academic Search Index
- Journal :
- Sensors (14248220)
- Publication Type :
- Academic Journal
- Accession number :
- 174113179
- Full Text :
- https://doi.org/10.3390/s23239568