A Fast Complexity Pursuit-Based Blind Source Separation Method for Structural Modal Identification
Zhixiang Hu, Qidong Yang, Lunhai Zhi, Feng Hu, Lei Huang · International Journal of Structural Stability and Dynamics · 2025
Complexity pursuit (CP) is an effective method for solving blind source separation (BSS) problems. Combined with the gradient descent algorithm, the complexity pursuit-gradient descent (CP-GD) algorithm can extract the structural modal contributions from vibration responses without measuring the inputs. However, the computational efficiency of CP-GD algorithm is very low since all data should be used in each iteration step of the gradient descent. This paper introduces the fast complexity pursuit-gradient descent (FCP-GD) algorithm, optimizing the traditional complexity calculation formula and using the subspace search method for calculating the de-mixing vectors, which significantly saves computation time. Furthermore, a comparative study between the FCP-GD and temporal predictability-generalized eigenvalue decomposition (TP-GED) algorithms was conducted using two-degree-of-freedom and three-degree-of-freedom systems and revealed an equivalence of these two algorithms. Finally, numerical simulations and experiments on multi-degree-of-freedom free vibration systems confirmed the effectiveness, efficiency, and robustness of the FCP-GD algorithm.