A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life.To this end,distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages,such as lightweight and ease of embedding.However,identifying the precise location of damage from the optical fiber signals remains a critical challenge.In this paper,a novel approach which namely Modified Sliding Window Principal Component Analysis(MSWPCA)was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors.The proposed method is able to extract signal characteristics interfered by measurement noise to improve the accuracy of damage detection.Specifically,we applied the MSWPCA method to monitor and analyze the debonding propagation process in honeycomb sandwich panel structures.Our findings demonstrate that the training model exhibits high precision in detecting the location and size of honeycomb debonding,thereby facilitating reliable and efficient online assessment of the structural health state.

Sound absorption performance of acoustic metamaterials composed of double-layer honeycomb structure

The purpose of the research is to assess the sound absorption performance(SAP)of acoustic metamaterials made of double-layer Nomex honeycomb structures in which a micro-orifice corresponds to a honeycomb unit.For this purpose,the influences of structural parameters on the SAP of acoustic metamaterials were investigated by using experimental testing and a validated theoretical model.In addition,the sandwich structure was optimized by the genetic algorithm.The research shows that the panel thickness and micro-orifice diameter mainly affect the second resonant frequency and second peak sound absorption coefficient(SAC)of the structure.The unit cell size is found to influence the first and second resonant frequencies and two peaks of the SAC.An extremely low side-length of the honeycomb core decreases the SAP of the structure for low-frequency noise signals.Additionally,the sandwich structure presents a better SAP when the diameter of micro-orifices on the front micro-perforated panel(MPP)exceeds that of the back MPP.The sandwich structure shows better noise reduction performance after the optimization aiming at the noise frequency outside trains.