Nonparametric Monitoring for Geotechnical Structures Subject to Long-Term Environmental Change

Table 1

A summary of the nonparametric identification approaches employed in the case study for a full-scale retaining wall, subjected to long-term environmental variations.

Methods	Data type	Purposes
Empirical mode decomposition (EMD)	Univariate	To decompose nonlinear and nonstationary environmental variations of daily, seasonal and long-term trends from raw sensor measurements
		To decompose complex raw measurements into simpler and physically “well-behaving” intrinsic mode functions for better understanding of the system
Hilbert-Huang transform (HHT)	Univariate	To obtain the instantaneous frequencies for nonlinear, non-stationary, time-varying systems
		The obtained instantaneous frequencies could be used to detect changes in “abnormal” system characteristics in time
Principal component analysis (PCA)	Multivariate	To find interchannel relationships with multi-input data (note that the EMD and HHT are single-channel data processing techniques)
		To visualize the mode shapes of the system decomposed by the corresponding orthogonal principal components
		To quantify the energy of inter-channel motions for each mode shape and find the dominant one