Structural damage diagnosis under varying environmental conditionsPart I: A linear analysis
A damage detection method is proposed for structural health monitoring under varying environmental and operational conditions. The method is based on principal component analysis (PCA) applied to vibration features identified during the monitoring of the structure. The advantage of the method is that it does not require to measure environmental parameters because they are taken into account as embedded variables. The number of principal components of the vibration features is implicitly assumed to correspond to the number of independent environmental factors. Since the environmental effects may be effectively eliminated by the proposed procedure, the residual error of the PCA prediction model remains small if the structure is healthy, and it increases significantly when structural damage occurs. Novelty analysis on the residual errors provides a statistical indication of damage. In the present paper, the environmental conditions are assumed to have a linear (or weakly non-linear) effect on the vibration features, and the PCA-based damage detection method is illustrated using computer-simulated and laboratory testing data. The extension of the proposed method to non-linear cases is addressed in a companion paper where the efficiency of the method is verified using data obtained from a 1-year in situ monitoring of a bridge.
structural health monitoring principal component analysis environmental variation temperature effect novelty detection bridge diagnosis