TY - JOUR
T1 - Multiway principal component analysis contributions for structural damage localization
AU - Ruiz, Magda
AU - Mujica, Luis Eduardo
AU - Sierra, Julián
AU - Pozo, Francesc
AU - Rodellar, José
N1 - Publisher Copyright:
© The Author(s) 2017.
PY - 2018/9/1
Y1 - 2018/9/1
N2 - In this article, a novel methodology for damage localization is introduced. The approach is based on a multiactuator system. This means that the system itself has the ability of both exciting the specimen and measuring its response at different points in a pitch-catch mode. Once one of its actuators excites the specimen, the damage affects the normal travel of the guided wave, and this change is mainly detected by sensors in the direct route to the excitation point. In previous works by the authors, it can be observed that the progression using data-driven statistical models (multivariable analysis based on principal component analysis) of all recorded signals to determine whether the damage is present. However, the main contribution of this article is the demonstration of the possibility of localizing damages by analyzing the contribution of each sensor to this index which have detected it (T2-statistic and Q-statistic). The proposed methodology has been applied and validated on an aircraft turbine blade. The results indicate that the presented methodology is able to accurately locate damages, analyzing the record signals from all actuation phases and giving a unique and reliable region.
AB - In this article, a novel methodology for damage localization is introduced. The approach is based on a multiactuator system. This means that the system itself has the ability of both exciting the specimen and measuring its response at different points in a pitch-catch mode. Once one of its actuators excites the specimen, the damage affects the normal travel of the guided wave, and this change is mainly detected by sensors in the direct route to the excitation point. In previous works by the authors, it can be observed that the progression using data-driven statistical models (multivariable analysis based on principal component analysis) of all recorded signals to determine whether the damage is present. However, the main contribution of this article is the demonstration of the possibility of localizing damages by analyzing the contribution of each sensor to this index which have detected it (T2-statistic and Q-statistic). The proposed methodology has been applied and validated on an aircraft turbine blade. The results indicate that the presented methodology is able to accurately locate damages, analyzing the record signals from all actuation phases and giving a unique and reliable region.
KW - Principal component analysis
KW - contribution analysis
KW - damage localization
UR - http://www.scopus.com/inward/record.url?scp=85042140045&partnerID=8YFLogxK
U2 - 10.1177/1475921717737971
DO - 10.1177/1475921717737971
M3 - Artículo en revista científica indexada
AN - SCOPUS:85042140045
SN - 1475-9217
VL - 17
SP - 1151
EP - 1165
JO - Structural Health Monitoring
JF - Structural Health Monitoring
IS - 5
ER -