Research on Ship-radiated Noise evaluation and Experiment Based on OTPA Optimized by Operation Clustering

While evaluating Ship-radiated noise with operational transfer path analysis (OTPA), a question arises that the input of OTPA cannot meet the linear system requirement, which results in a large estimated error in several frequencies. Therefore, to reduce the estimated error, in this paper a method based on OTPA optimized by operation clustering is proposed. First, a complete clustering feature matrix is constructed and weighted principal component analysis (W-PCA) used for feature extraction. Then, several classes of operating mode(OM) are clustered by K-means based on the feature, and the classified OMs are taken as the input of OTPA, which can meet the linear system requirement of OTPA. Experiments with cabin in Thousand Islet Lake show that the statistical probability of the line spectrum with an estimated error less than 3 dB is more than 95%, which is an improvement of 16.7% compared to the error before optimization, and the maximum estimated error of the line spectrum is reduced by 11.3 dB. The estimated error of 1/3 Octave is less than 2 dB in all frequencies, which can be reduced by approximately 7 dB. The results verify the feasibility of OTPA optimized by operation clustering.