排列熵算法在水工结构损伤诊断中的应用

Damage Diagnosis of Hydraulic Structure Based on Permutation Entropy

提出一种基于排列熵算法(permutation entropy,简称PE)的水工结构损伤诊断方法。首先,运用小波阈值-经验模态分解(empirical mode decomposition,简称EMD)降噪方法对原始信号进行降噪,减小环境噪声对结构损伤特征信息的干扰,提高信号的信噪比;其次,运用排列熵算法检测降噪后信号的复杂度,并计算其排列熵值。通过不同工况下信号熵值变化规律的对比,实现水工结构损伤的诊断。将该方法应用于泄流激励下悬臂梁模型的试验研究,结果表明,正常无损状态下结构振动信号的排列熵值最大;结构发生损伤时,其熵值降低,且损伤程度越大,熵值越小;排列熵对结构的初期损伤比较敏感;结构未发生损伤时,不同工况下的排列熵基本不变,说明排列熵能够有效确定结构的损伤,且具有较高的诊断精度。

In order to solve the difficulty of damage diagnosis for hydraulic structure during operation,a valid damage diagnosis method based on permutation entropy is proposed.Firstly,a kind of combined wavelet threshold and empirical mode decomposition(EMD)method is used to filter out the noises,which can reduce the disturbance of environmental excitation in structural damage characteristic information to improve the signal-to-noise ratio.Then the de-noised signals are analyzed by permutation entropy to extract their entropy values.Finally,the damage identification of hydraulic structure can be achieved by the contrast of entropy values under different working conditions.The proposed method is applied to study the vibration responses of cantilever beam model under environmental excitation.The results show that the permutation entropy of structural vibration signal is the largest in the normal state without damage.When there are certain damages,the permutation entropy decreases,the greater the damage degree,the smaller the permutation entropy.Permutation entropy is sensitive to structural initial damage.Permutation entropy is almost constant under different working conditions when there is no damage to structure.Therefore,the proposed method can effectively identify structural damage with high diagnostic accuracy.