The goal of OMA is to estimate the dynamic properties of Linear Time-Invariant (LTI) systems purely from records of their dynamic response. Thus, the unknown environmental and operational loads play a fundamental role in testing and in the subsequent modal analysis. While the environmental excitation is advantageous when large civil structures are tested, the data acquisition and, above all, data processing require supplemental attention to carry out successful, output-only modal tests.
 
There are a number of algorithms for comprehensive modal analyses which work in different domains such as the time domain, frequency domain, and time-frequency domain. In the frequency domain, one of the most common technique is Frequency Domain Decomposition (FDD) which is capable to extract the natural frequency and mode shape of the structure. Enhanced FDD (or EFDD) is a more developed version of the method that can identify a damping ratio in addition to the other parameters. Research shows that in the presence of low Signal Noise ratio (SNR), closed modes cannot be detected easily using frequency domain methods. Thus, the application of a robust technique in the time domain is required to detect all modes with any characteristics. The most common robust method in the time domain is called Stochastic Subspace Identification (SSI). The details of the algorithms will be explained in coming blogs.