SPARSE COMPONENT ANALYSIS METHOD FOR STRUCTURAL MODAL IDENTIFICATION DURING QUANTITY INSUFFICIENCY OF SENSORS

摘要

The present invention relates to the technical field of structural health monitoring, and provides a sparse component analysis method for structural modal identification during quantity insufficiency of sensors. The method comprises: performing short-time Fourier transform on structural acceleration response data for conversion to a time-frequency domain; detecting, on the basis that a real part and a virtual part have the same direction, a time-frequency point with modal of only one order participating in contribution, i.e., a single source point, as the initial result of single source point detection; purifying the initial result of the single source point detection according to the fact that the single source point is located in the vicinity of a power spectrum peak value, and clustering the single source point to obtain a modal matrix; constructing a generalized spectrum matrix by using a short-time Fourier transform coefficient; performing singular value decomposition on the generalized spectrum matrix at the single source point; and considering the first singular value as an auto-power spectrum of a single-order modal, obtaining frequency of each order by picking up the peak value of the auto-power spectrum, and converting the auto-power spectrum to a time domain by means of inverse Fourier transform to extract a damping ratio of each order. According to the method, modal parameters of structures are obtained under the condition that sensors are insufficient, and therefore, the identification accuracy of the sparse component analysis method is improved.