Impact Damage Identification for Composite Material Based on Transmissibility Function and OS-ELM Algorithm

摘要

A method is proposed based on the transmissibility function and the OnlineSequence Extreme Learning Machine (OS-ELM) algorithm, which is applied to theimpact damage of composite materials. First of all, the transmissibility functions of theundamaged signals and the damage signals at different points are calculated. Secondly,the difference between them is taken as the damage index. Finally, principal componentanalysis (PCA) is used to reduce the noise feature. And then, input to the online sequencelimit learning neural network classification to identify damage and confirm the damagelocation. Taking the amplitude of the transmissibility function instead of the accelerationresponse as the signal analysis for structural damage identification cannot be influencedby the excitation amplitude. The OS-ELM algorithm is based on the ELM (ExtremeLearning Machine) algorithm, in-creased training speed also increases the recognitionaccuracy. Experiment in the epoxy board shows that the method can effectively identifythe structural damage accurately.