STUDY ON DAMAGE EVOLUTION OF CFRP BOGIE BASED ON ACOUSTIC EMISSION MONITORING

To investigate the damage mechanism and evolution laws of the carbon fiber reinforced polymer (CFRP) bogie under ultimate operating conditions, a static ultimate load failure test was conducted on the bogie. A multi-channel acoustic emission (AE) device was used to monitor the entire experimental process. The load data and AE signals were synchronously recorded throughout the test, ranging from initial loading and microscopic damage accumulation to the appearance of macroscopic structural delamination. Additionally, the main macroscopic failure modes of the side beams were analyzed after the test. Based on a systematic analysis of time-domain characteristic parameters such as amplitude, peak frequency, and root mean square (RMS), The continuous wavelet transform (CWT) was introduced to extract the time-frequency characteristics of the signals. The relationship between AE signal features and damage modes was established by combining the fuzzy C-means (FCM) clustering algorithm. Meanwhile, the primary failure modes during the loading process were identified. Simultaneously, by calculating the improved b-value (Ib-value), the damage severity was quantitatively evaluated, revealing the damage evolution laws of the bogie under ultimate load. The results indicate that the damage evolution of the bogie exhibits distinct staged characteristics: The dominant damage mode in the initial loading stage is microscopic damage such as matrix cracking and fiber debonding. As the load increases, the Ib-value presents a fluctuating downward trend and eventually drops into the low-level warning zone. Simultaneously, the proportion of high-energy and medium-to-high frequency signals increases significantly, which indicates a transformation in the internal damage mechanism. The delamination damage gradually expands and becomes dominant. The main macroscopic failure modes of the bogie after the test were basically consistent with the analysis results of the AE signal characteristics.