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• A MWI approach is proposed for ill-conditioned inverse problem in dynamics. • The unbiasedness and convergence of the proposed MWI method are proved. • MWI is superior to TSVD and Tikhonov regularization in application cases. • MWI has high accuracy and anti-noise property. Many problems in dynamics can be formulated as inverse problems that require the determination of the unknown input from the known output. Limited by the measurement noise, the computational cost, the error in numerical computation, etc., solving ill-conditioned inverse problems in dynamics is a big challenge. In this paper, we propose Maximumly Weighted Iteration (MWI) approach to solve ill-conditioned inverse problems in dynamics generally. The ill-condition of the system coefficient matrix is controlled by iterative weighted decomposition and a weighted term, also avoiding matrix inversion of solving and reconstruction process. As an iterative method, MWI has been theoretically proven to have consistency, absolute convergence, and conditional unbiasedness. The numerical results demonstrate that MWI is superior to Truncated Singular Value Decomposition and Tikhonov regularization in terms of accuracy and anti-noise property. Two application cases are used to demonstrate the potential of MWI in engineering practice. The first is elastic vibrations identification combined with randomized resonant metamaterials, and the second is fault diagnosis of mechanical transmission systems. [Display omitted] [ABSTRACT FROM AUTHOR]

• An in-situ transfer path analysis method is proposed to avoid physical decoupling ;. • A virtual decoupling method is applied to estimate the decoupled frequency response function;. • The effectiveness of the proposed method is verified both numerically and experimentally ;. • The proposed method is capable of tracing the fault location by determining the dominant transfer path;. • A physically-interpretable signal decomposition method is proposed to enhance the fault feature. A transfer path analysis method based on the in-situ measurement is proposed for the fault tracing of parallel axis gear systems. A virtual decoupling technique is used to achieve the in-situ measurement of the decoupled frequency response function (FRF) between bearing positions and measuring points on housing, avoiding the tedious test procedure and non-representative assembly conditions caused by the physical decoupling. Based on the decoupled FRF and the responses of the gearbox housing, the bearing force is identified using the Tikhonov regularization theory. Then the frequency-dependent path contribution, which will be used to perform the transfer path analysis, is obtained by multiplying the decoupled FRF and the bearing force. Finally, the fault-specific path rank order is determined using the path contribution within the resonant frequency band. This band is located by the spectral kurtosis algorithm. Based on the proposed in-situ path analysis, fault tracing is conducted by determining the dominant transfer path. The effectiveness of the proposed path analysis method is verified both numerically and experimentally. A two-stage parallel axis gear test rig with localized defects is utilized to demonstrate the efficacy of the proposed fault tracing strategy. Moreover, based on the path analysis, a physically-interpretable signal decomposition method is proposed to enhance the fault feature. Through this decomposition method, the fault indicator of the weakest fault type (chipped tooth) can be magnified by 204%. The proposed transfer path analysis method provides a feasible strategy for fault tracing, feature enhancement and incipient fault diagnosis of parallel axis gear systems. [Display omitted] [ABSTRACT FROM AUTHOR]