Damage mode identification and premature failure prevention for composite structures by acoustic emission have drawn a great deal of attention. Feature evaluation on streaming acoustic emission data is one of the significant issues in research of acoustic emission signal processing. This work conducts dynamic feature evaluation on 15 conventional acoustic emission features so as to seek a deeper insight into different features with damage accumulation. First, the procedure of dynamic feature evaluation is presented based on three basic algorithms. Second, the streaming acoustic emission data are collected from the adhesively bonded composite single-lap joint subjected to quasi-static tensile loads. Third, further efforts are made so as to explore the information contained as well as to interpret the effect of damage accumulation. It is found that different conventional acoustic emission features show distinctive functions, including damage mode identification, damage process indication, and both of them. Informative features for damage pattern recognition are independent on damage accumulation. Useful features for damage process description show sensitive dynamic characteristics with damage accumulation, especially before the complete failure of the specimen. Furthermore, dynamic feature evaluation can be used to detect singular signals.

声发射对复合结构的损伤模式识别和防止过早失效引起了广泛的关注。流声发射数据的特征评估是声发射信号处理研究的重要课题之一。这项工作对15种常规声发射特征进行了动态特征评估，以寻求对具有损伤累积的不同特征的更深入的了解。首先，基于三种基本算法提出了动态特征评估的程序。第二，从经受准静态拉伸载荷的粘合复合单搭接接头中收集流声发射数据。第三，进一步努力以探索其中包含的信息并解释损害累积的影响。发现不同的常规声发射特征显示出独特的功能，包括损伤模式识别，损伤过程指示以及两者。损伤模式识别的信息功能与损伤累积无关。损伤过程描述的有用功能显示出具有损伤累积的敏感动态特性，尤其是在样品完全失效之前。此外，动态特征评估可用于检测奇异信号。损伤过程描述的有用功能显示出具有损伤累积的敏感动态特性，尤其是在样品完全失效之前。此外，动态特征评估可用于检测奇异信号。损伤过程描述的有用功能显示出具有损伤累积的敏感动态特性，尤其是在样品完全失效之前。此外，动态特征评估可用于检测奇异信号。