This paper proposes a method for optimizing cabin inner-sound monitoring points using quantum-behaved particle swarm optimization(QPSO)to address the challenges of online monitoring of cabin noise and prediction of sound fields.The proposed method first determines the desired mode order of the acoustic cavity based on the fre-quency range.Subsequently,it calculates the sound field distribution for various mode orders of the acoustic cavity at all potential monitoring points.Utilizing the modal confidence matrix as the objective function,the positions of the monitoring points are optimized based on the QPSO algorithm.Herein,the quadrature of acoustic mode sam-pling and the responses of internal and external acoustic fields are compared with other arrangement schemes.The results show that the optimized measuring-point arrangement scheme proposed herein is more effective in collecting acoustic-cavity-mode information.This effectively improves the accuracy of sound field reconstruction within a cabin and the prediction accuracy of underwater radiation noise.
维普
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