Abstract
Nondestructive testing technology of wood acoustic emission(AE) signal is of great significance to evaluate wood internal damage. In order to achieve more accurate and adaptive evaluation, we propose an AE signal analysis method combining instantaneous frequency and power to extract the signal features of different the Intrinsic Mode Function(IMF) components. Then input the SVM classifier for classification and recognition, and adopt the Receiver Operating Characteristic (ROC) curve as the evaluation index to evaluate the classification model of different IMF components. The results show that the instantaneous frequency and power can clearly display AE signal features. The IMF components decomposed by EMD are classified by extracting features, and the classification accuracy of IMF 1 component up to 88% is the highest one. It indicates that IMF 1 component contains a large number of effective AE signal features, which can be utilized for the identification of wood damage and fracture state.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
