To increase the accuracy and reliability of the transmissibility function evaluation, a combined crosstalk cancellation method based on wavelet packet denoising and Welch’s method for operational transfer path analysis (OTPA) is proposed. Firstly, prior tests are carried out with pulsed excitation, and the signals at reference points are measured concurrently. Secondly, wavelet packet denoising is adopted to process the measured signals, which can effectively reduce the effects of measurement noises and other random errors. Thirdly, Welch’s method is adopted to evaluate auto-power spectrums and cross-power spectrums, and thus the prior transmissibility functions can be accurately obtained. Fourthly, a crosstalk cancellation method is proposed and the signals at reference points without crosstalk are obtained. Finally, the crosstalk problem is solved and an efficient and accurate OTPA is obtained. Furthermore, numerical case studies and experimental case studies on a test bed with shell structures are carried out to study comparatively the performances of the proposed method. Generally, this study provides an effective crosstalk cancellation method for OTPA, which can increase the accuracy and reliability of transfer path identification and contribution evaluation, and thus benefit vibration and noise monitoring, reduction and control.
To quantitatively identify the transfer paths and evaluate path contributions of shell structures, an singular value decomposition- (SVD-) and principal component analysis- (PCA-) based operational transfer path analysis method is constructed and studied in this paper. Firstly, SVD is used to determine the contribution of each path and reduce crosstalk. Secondly, PCA is applied to reduce the influence of unwanted frequency components and thus reduce noises. This allows the presented OTPA to be more accurate than its traditional counterpart. Once the transmissibility function is obtained, the response synthesis is determined, and the transfer path analysis and path contribution evaluation can be effectively carried out. Numerical and experimental case studies are carried out to validate and test the performance of the presented method. Furthermore, a comprehensive observing the influences of correlation between sources and distance of sources and receiver is also provided. Generally, this paper provides accurate transfer path analysis and path contributions for mechanical systems, which can benefit vibration and noise monitoring and reduction through vibration reduction structure design for new equipment or vibration damping on the major vibration transfer paths for current equipment.
To accurately estimate source signals from their post-nonlinear mixtures, a post-nonlinear blind source separation (PNLBSS) method with kurtosis constraints is proposed based on augmented Lagrangian particle swarm optimization (PSO). First, an improved contrast function is presented by combining mutual information of the separated signals and kurtosis ranges of source signals. Second, an augmented Lagrangian multiplier method is used to convert PNLBSS into an unconstrained pseudo-objective optimization problem. Then, improved PSO is applied to update the parameters in complex nonlinear spaces. Finally, numerical case studies and experimental case studies are provided to evaluate the performance of the proposed method. By adding the kurtosis ranges constraints, the estimation accuracy of source signals could be improved, which would benefit vibration and acoustic monitoring and control.
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