TY - GEN
T1 - A B-Spline Based Gaussian Process Regression Approach for Fatigue Crack Length Estimation Using Ultrasonic Wave Data
AU - Wang, Rui
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The diagnosis and prognosis of fatigue cracks, which greatly influence the long-term durability of structures, is an important issue for structural health monitoring (SHM). This paper presents a study on the estimation of fatigue crack length using ultrasonic wave data. The measured signal is first denoised and truncated to extract the informative period of the signal. If a crack is detected, features are extracted to represent the distortion of the signals while reducing the influence of noise with a B-spline based method. Gaussian process regression obtained from an integration of mean and covariance functions is used for the estimation of the crack length. Real-world experiments validates the effectiveness of the proposed method.
AB - The diagnosis and prognosis of fatigue cracks, which greatly influence the long-term durability of structures, is an important issue for structural health monitoring (SHM). This paper presents a study on the estimation of fatigue crack length using ultrasonic wave data. The measured signal is first denoised and truncated to extract the informative period of the signal. If a crack is detected, features are extracted to represent the distortion of the signals while reducing the influence of noise with a B-spline based method. Gaussian process regression obtained from an integration of mean and covariance functions is used for the estimation of the crack length. Real-world experiments validates the effectiveness of the proposed method.
KW - Fatigue crack length estimation
KW - Gaussian process regression
KW - Ultrasonic wave
UR - https://www.scopus.com/pages/publications/85123410147
U2 - 10.1109/PHM-Nanjing52125.2021.9612894
DO - 10.1109/PHM-Nanjing52125.2021.9612894
M3 - 会议稿件
AN - SCOPUS:85123410147
T3 - 2021 Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021
BT - 2021 Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021
A2 - Guo, Wei
A2 - Li, Steven
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021
Y2 - 15 October 2021 through 17 October 2021
ER -