A Damage Sensing Method of Carbon Fiber Reinforced Polymer Composites Via Multi-frequency Electrical Impedance Fusion

Background Electrical-based self-sensing methods for damage monitoring of carbon fiber reinforced polymer are promising for online and in-situ damage monitoring. Objective Multi-frequency electrical impedance fusion will be used to realize damage sensing and damage mode identification. Methods In order to correlate the electrical impedance response with damage, monotonic tensile tests were performed on 0°-orientation, 45°-orientation and woven fabric laminates. Electrodes configurations were optimally selected for effective detection of damage. The electrical impedance characteristics of the laminates over a wide frequency range were studied and the corresponding macroscopic equivalent circuit models were established. A manifold learning algorithm was applied for multi-frequency electrical impedance fusion and damage-related features extraction. Results Results showed that there is a linear relationship between electrical impedance of the laminates and their mechanical damage. Different damage modes including matrix cracking, fiber-matrix debonding and fiber breakage can be distinguished in the measured data. Conclusions The damage mode identification method based on electrical impedance is validated by acoustic emission test results and microscopic images, making this method preferable for online monitoring.