Flat plates and cylindrical shells are commonly used in large equipment. To locate the low-velocity impact points in these structures, this study proposes an error-index-based algorithm for impact localization. The time of arrival of an impact-generated A0 Lamb waves was first estimated based on the energy of the signal. Equations for calculating the error indices were proposed for flat-plate and cylindrical shell structures, and the probability distribution functions of the impact points are constructed for visual localization. The impact test results on a flat plate and cylindrical shell indicated that, compared to the Morlet wavelet method, the proposed algorithm improved the mean relative error of impact point localization on the flat plate by 0.22%, 15.64%, and 15.26% under three different noise conditions, respectively (i.e., no noise, and SNR = 5 and 0 dB). For the cylindrical shell, the mean relative error of impact localization improved by 1.8%, 3.97%, and 28.12% under the three conditions, respectively. The results indicated that the proposed localization algorithm can accurately locate the impact points on a flat plate and cylindrical shell, even under strong background noise conditions, providing a reference for future research on locating low-velocity impact points in large equipment.

The radiation impedance is an essential parameter in analyzing the vibroacoustic response of the planar source. In order to calculate the acoustic radiation impedance of the rectangular plate with arbitrary boundary conditions, a unified approximate approach is proposed in this study. The displacement function of the plate is expressed in the form of a supplemented two-dimensional Fourier cosine series, which can be solved by the Rayleigh–Ritz method. The radiated acoustic field from the plate is further determined by the Rayleigh integrals. The coordinate transformation is performed twice to convert the quadruple integrals into simple integrals, significantly reducing the computational effort of the acoustic calculation. Regardless of the wavenumber or frequency, the proposed approach is theoretically accurate because no assumptions or approximations are involved in the mathematical process. Furthermore, the correctness of the formulas is validated by the results obtained from previous studies. Several numerical examples are performed using this approach, and the effects of boundary conditions on the modal radiation impedance are discussed.

When a propeller is under a state of cavitation, it will experience negative effects, including strong noise, vibration, and even damage to the blades. Accordingly, the detection of propeller cavitation has attracted the attention of researchers. Propeller noise signal contains a wealth of cavitation information, which is a powerful method to identify the cavitation state. Considering the nonlinear characteristics of propeller noise, a feature describing the complexity of nonlinear signals, which is called refined composite multiscale fluctuation-based dispersion entropy (RCMFDE), is adopted as the indicator of propeller cavitation, and a framework for the identification of propeller cavitation state is established in this paper. Firstly, the propeller noise signal is decomposed by the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method, and the intrinsic mode function (IMF) components with cavitation characteristics are extracted. Secondly, the RCMFDE of the IMF components is computed. Finally, a hybrid optimization support vector machine (SVM) is established to classify the features, in which a Relief-F filter is utilized to reduce the feature dimension, and a particle swarm optimization (PSO) wrapper is utilized to optimize the parameters of the SVM. The experimental results demonstrate encouraging accuracy to apply this approach to identify the propeller cavitation states, with an identification accuracy of 91.11%.

No abstract

No abstract