Understanding and managing identification uncertainty of close modes in operational modal analysis

Close modes are much more difficult to identify than well-separated and their identification (ID) results often have significantly larger uncertainty or variability. The situation becomes even challenging in operational modal analysis (OMA), which is currently the most economically viable means for obtaining in-situ dynamic properties of large civil structures where ID management needed. To understand manage it field test planning, this work develops ‘uncertainty law’ close modes, i.e., closed form analytical expressions remaining parameters identified using output-only ambient vibration data. reveal a fundamental definition that quantifies ‘how close’ demystify roles various governing factors. verified with synthetic, laboratory Statistics factors from data OMA challenges different situations, now accountable within coherent probabilistic framework. Recommendations made planning tests taking into account. Up modelling assumptions use probability, law dictates achievable precision regardless algorithm used. mathematical theory behind paper presented companion paper.