TY - GEN
T1 - Soft computing feature extraction for health monitoring of rotorcraft structures
AU - Escamilla-Ambrosio, P. J.
AU - Lieven, N.
PY - 2007
Y1 - 2007
N2 - Structural Health Monitoring (SHM) is the process of implementing a damage identification strategy for aerospace, civil and mechanical engineering infrastructure Under this context, feature extraction is the process of identifying damage-sensitive information from measured data. Feature extraction is an essential component of a SHM system needed to convert raw sensor data into useful information about the structural health condition. The need for robust health monitoring and prognosis of components in remote or difflcult-to-access locations is driving the advancement of sensing hardware and processing algorithms. In this paper a feature extraction algorithm, referred to as soft computing feature extraction algorithm, is developed to extract damage-sensitive information from measured response data of helicopter rotor-head components. The proposed feature extraction algorithm is based on a combination of discrete wavelet transform theory and fuzzy logic theory. The results of applying the proposed feature extraction approach to tie bar data are presented. Results show that the proposed algorithm is capable of extracting features sensitive to the degradation of tie bar systems.
AB - Structural Health Monitoring (SHM) is the process of implementing a damage identification strategy for aerospace, civil and mechanical engineering infrastructure Under this context, feature extraction is the process of identifying damage-sensitive information from measured data. Feature extraction is an essential component of a SHM system needed to convert raw sensor data into useful information about the structural health condition. The need for robust health monitoring and prognosis of components in remote or difflcult-to-access locations is driving the advancement of sensing hardware and processing algorithms. In this paper a feature extraction algorithm, referred to as soft computing feature extraction algorithm, is developed to extract damage-sensitive information from measured response data of helicopter rotor-head components. The proposed feature extraction algorithm is based on a combination of discrete wavelet transform theory and fuzzy logic theory. The results of applying the proposed feature extraction approach to tie bar data are presented. Results show that the proposed algorithm is capable of extracting features sensitive to the degradation of tie bar systems.
UR - http://www.scopus.com/inward/record.url?scp=50249127311&partnerID=8YFLogxK
U2 - 10.1109/FUZZY.2007.4295544
DO - 10.1109/FUZZY.2007.4295544
M3 - Contribución a la conferencia
AN - SCOPUS:50249127311
SN - 1424412102
SN - 9781424412105
T3 - IEEE International Conference on Fuzzy Systems
BT - 2007 IEEE International Conference on Fuzzy Systems, FUZZY
T2 - 2007 IEEE International Conference on Fuzzy Systems, FUZZY
Y2 - 23 July 2007 through 26 July 2007
ER -