The Application Of Underdetermined Blind Source Separation In Modal Parameter Identification

During the engineering structure servicing life,it is inevitably affected by various factors from itself and the outside world.That makes the structure's resistance performance to decline and reliability to decrease,which in turn leads to safety accidents,and causes huge personnel and economic loss of property.Therefore,it is of great significance to adopt effective means to carry out structural health monitoring of civil engineering structures.At present,structural modal analysis has become one of the core technologies of structural health monitoring system.In this paper,the theory of underdetermined blind source separation is introduced and applied to structural modal analysis,which provides a new choice for the underdetermined modal parameter identification problem that the number of sensors is less than the number of active modes in structural health monitoring.The main work and research of this paper are as follows:1.The Underdetermined blind source separation method based on density peak clustering algorithm is discussed in this paper.Firstly,the sensor signals in the time domain are transformed to the sparse time-frequency domain by the short-time Fourier transform.In view of the unpredictable number of active modes and the high-order vibration mode aliasing,a new method based on density peak clustering to identify the mode shapes is proposed.After obtaining vibration mode shapes,the smooth l₀algorithm,which can reconstruct the sparse signals quickly,is used to reconstruct the modal coordinate signals and extract modal frequencies.2.The underdetermined blind source separation method based on parallel factor analysis is discussed in this paper.Firstly,the signal is transformed to the time-frequency domain by the smoothed pseudo Wigner-Ville distribution.Then,a parallel factor model is constructed,and the modal vibration mode is identified by parallel factor analysis.Finally,modal coordinates are reconstructed using subspace algorithm to identify modal frequencies.3.The validity and practicability of these two algorithms are verified experimentally by a four-story shear steel frame model.The two underdetermined blind source separation methods both successfully identify the mode shapes and separate the modal coordinate signals with random vibration test data under the condition that only three sensors are arranged,which indicated that the method proposed in this paper can be used in modal parameters.