Frequency Domain Decomposition (FDD) Program for Mode Shape and Frequency Identification

When implementing the Frequency Domain Decomposition (FDD) Program for mode shape and frequency identification, the initial step involves proper data sampling and preprocessing of required measurement data. The core algorithm employs singular value decomposition (SVD) on the power spectral density (PSD) matrix, where peak picking in the singular value plots helps identify dominant natural frequencies. Decomposed signals are then analyzed through modal assurance criterion (MAC) and automatic clustering techniques to accurately extract mode shapes. During analysis, various algorithmic approaches can be tested including enhanced frequency domain decomposition (EFDD) for better modal parameter estimation. The implementation typically involves functions for PSD matrix computation, SVD processing, and modal validation checks. Ultimately, this methodology provides comprehensive understanding of structural dynamic response characteristics, establishing essential foundations and references for subsequent engineering applications and research developments.