Aiming at the problem that various types of features in global navigation satellite system(GNSS)deformation monitoring sequences are intermingled with each other and difficult to extract features and analyze them independently in the structural health monitoring scenario,a time series decomposition algorithm based on multi-parameter adaptive variational mode decomposition(MA-VMD)is proposed.Firstly,the effects of multiple parameters in the variational mode decomposition(VMD)algorithm on the decomposition results are analyzed thoroughly.Then,according to the frequency domain characteristics of the original sequence and decomposition results,the MA-VMD algorithm is established by adaptively adjusting the decomposition mode number,penalty factor,initial center frequency and Lagrange multiplier.Experiments on the simulated sequences show that the correlation between the decomposition results of MA-VMD algorithm and real values is 98.77%,and the root mean square error is 0.1365 mm,which is close to the global optimum and significantly better than other decomposition algorithms like empirical mode decomposition,singular spectrum analysis and improved variational mode decomposition.Finally,based on the actual GNSS deformation monitoring data,the effectiveness of the proposed algorithm in engineering application is verified.
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