【摘要】 结构状况可根据结构响应信号的异常进行判断,人工免疫系统能有效地应用于信号的异常检测。对基于免疫机制的正向选择算法进行了研究,利用具有时频局部化特性的小波包分解得到表征结构特征的小波包能量谱,通过正向选择算法检测小波包能量谱的异常来辨识结构状况。对正向选择算法进行了改进,可减少"自我"空间检测子的生成数目,加快检测速度,促进正向选择算法的实际应用。以ASCE学会提出的基准结构为对象,验证了正向选择算法在损伤诊断中的有效性,并与反向算法进行了比较。更多还原

【Abstract】 The structural condition can be identified by the abnormal behavior detection of the vibration response of the structure.The artificial immune system algorithm is an appropriate approach for anomaly detection.Therefore,artificial immune system is introduced to detect the damage in a structure.First,the positive selection algorithm inspired by immune system is discussed.Then the wavelet packet energy spectrums are extracted as features using wavelet packet decomposition with an arbitrary time-frequency resolution.At last,the positive selection algorithm is employed to detect the abnormality of the features.The improvement on the algorithm is implemented,helpful to the reduction of detector number and the acceleration of detection speed.For demonstration,a numerical study on health monitoring of the ASCE benchmark model is performed.The results show that the health condition of the structure can be accurately monitored by the proposed method and it is compared with the negative selection algorithm.更多还原