A PCA-based algorithm for structural health monitoring using frequency response functions

作者：Zhu Jun Hua; Yu Ling^*

来源：Journal of Vibration and Shock, 2011, 30(5): 111-115.

• Damage state
• Damaged structures
• Efficient method
• Frequency response FRF)
• Frequency response functions
• Orthogonal transformation matrices
• Principle component
• Principle component analysis
• Structural damage detection
• Structural health
• Transformation techniques
• Two-dimensional PCA

Based on measured frequency response functions (FRFs), an easier and more efficient method for structural health monitoring was proposed by using principle component analysis (PCA) here. The FRFs of a healthy structure were used as the initial data. With this method a PCA transformation technique was used to obtain the features of the intact structure, i.e., its principle components (PCs) with which an orthogonal transformation matrix packed using the first few eigenvectors of the covariance matrix was found. Further, the orthogonal transformation matrix was used to transform the FRFs of a damaged structure so as to find the corresponding damage state features of the structure. Both structural damage detection and structural health monitoring could be achieved by comparing the two-dimensional PCA distribution charts corresponding to the damaged state and the healthy one of the structure. Two numerical simulation examples showed that the proposed method is correct, effective and feasible.

• 出版日期2011-5
• 单位暨南大学