【摘要】 同步带是普通FDM 3D打印设备普遍采用的传动定位部件,同步带失效会直接对打印产品质量造成影响.利用声发射(AE)传感器监测3D打印过程中同步带不同健康状态下的声发射信号,利用集合经验模态分解(EEMD)方法提取其信号特征,并通过隐半马尔可夫模型(HSMM)方法构建针对同步带健康状态的识别模型,进而对同步带正常、磨损和裂纹等三种健康状态进行识别,通过实验表明该方法是可行的.更多还原

【Abstract】 The synchronous belt is a commonly used driving and positioning part in ordinary FDM 3 D printing equipment. The failure of synchronous belts will directly affect the quality of printing products. Acoustic emission( AE) sensors were used to monitor the AE signals in different healthy states of the synchronous band during 3 D printing processes. The signal features were extracted by the method of ensemble empirical mode decomposition( EEMD). The recognition model for the healthy state of the synchronous band was constructed by using the hidden semi-Markov model( HSMM) method,and then the synchronous band was positioned. Three health states such as normal,wear and crack were identified. Experiments show that the method is feasible.更多还原