A factor analysis based automatic optimization method of vibration sensor points for ship acoustic reconstruction

To address the challenge associated with optimizing the number and positioning of accelerometer points in ship acoustic reconstruction, factor analysis is applied to the automatic optimization of accelerometer position in this work according to the source independence of ship’s underwater radiated noise. Based on the numerical simulation method that calculates the vibration noise response under specific operation conditions, the minimum number and the optimal position of the accelerometers can be obtained through the factor analysis and multi-parameter comprehensive evaluation method. The results of acoustic reconfiguration and testing are compared using one test cabin as a validation object to verify the effectiveness of the proposed method. The results show that the automatic optimization algorithm can improve the reconstruction accuracy concerning the uniform distribution method. The error is reduced from 15.46% (1.5 dB) to 8.35% (0.8 dB), and the correlation coefficient is improved from 0.86 to 0.89. The semi-automatic optimization method is slightly lower in terms of errors and correlation coefficients compared to the automatic optimization algorithm. After increasing the number of monitoring positions for automatic optimization, the acoustic reconstruction accuracy is further improved, while the average error is reduced to 7.37% (0.7 dB) and the correlation coefficient is improved from 0.89 to 0.92. The experimental results are proximate to the conclusions of the simulation calculation. Even under the circumstance of multi-factor noise interference, the correlation coefficient of multi-position automatic optimization can still reach 0.8, in comparison with the uniform distribution method, the error is reduced from 32.49% (3.4 dB) to 25.94% (2.6 dB). The proposed method effectively captures the dynamic characteristics of complex structures and their impact on underwater radiated noise, and the integration of factor analysis can prominently enhance the computational efficiency, thereby providing technical support for engineering applications to the ship acoustic reconstruction.