Low Velocity Impact Energy Monitoring and Recognition of Composite Laminates with Variable Thickness Based on Optical Fiber Sensor Network

Abstract

At present, most of the research on low velocity impact of composite laminates focuses on load location and damage assessment. To provide further early warnings about structural impact damage, impact energy can be monitored and identified. For high strength composite laminates with variable thickness, in order to further accurately evaluate the impact energy, it is necessary to adopt more suitable dynamic load signal analysis and impact energy identification methods. Therefore, a new low velocity impact monitoring and identification method for composite plates with variable thickness is proposed. All impact sample signals collected by optical fiber sensor network are decomposed by whitening Empirical Mode Decomposition (EMD); the energy feature set is established according to the impact energy eigenvalue of sample signal; according to the first order component of signal decomposition, the thickness coefficient is determined and the energy feature set is modified to evaluate the actual impact energy. Meanwhile, combined with optical fiber sensing and signal processing technology, an impact energy monitoring system has been established, and the low velocity impact monitoring and identification experiments of composite laminates with variable thickness were carried out. The proposed energy identification method successfully identified 1–3 J impact energy with an average error of 4.82%, and the average error of large thickness area with low sensitivity was significantly reduced from 13.25% to 5.67%. The results show that the thickness coefficient correction method based on whitening EMD can evaluate the low velocity impact energy more accurately, and the thickness coefficient correction step significantly improves the recognition performance.