Analytical minimization of synchronicity errors in stochastic identification

Previous findings in the literature [12,13] attribute such degradation to the loss of physical phase consistency between sensor nodes.

“This trend aligns with previous findings in the literature [12,13], which attribute such degradation to the loss of physical phase consistency between sensor nodes.”

Previous works [12,13] suggested that natural frequencies and damping ratios are generally more robust to sampling variability.

“Since previous works [12,13] suggested that natural frequencies and damping ratios are generally more robust to sampling variability, convergence analysis on those parameters is reported in Figure 6.”

Previous works using different identification strategies arrived at the same conclusions: synchronization errors significantly affect mode shape estimation but have limited impact on frequency and damping estimates.

“Notably, previous works based on different identification strategies, such as [12] (using ARMAV models) and [13] (using SSI with corrective actions), arrived at the same conclusions: synchronization errors significantly affect mode shape estimation but have limited impact on frequency and damping estimates.”

Even minimal misalignment is sufficient to degrade mode shapes, making them unreliable for damage detection.

“whereas even minimal misalignment is sufficient to degrade mode shapes, making them unreliable for damage detection.”

Natural frequencies are generally robust to lack of synchronization.

“Results align with findings by Lei [12] and Bernal [13]: natural frequencies are generally robust to lack of synchronization”