采用超声方法检测接收波纹管模型的回波信号，利用总体平均经验模态分解（EEMD）方法将信号分解成多个频带的本征模态分量（IMF）； 当波纹管内部出现脱浆缺陷时，回波信号在不同IMF内的能量分布会发生变化，将主要IMF分量的能量熵特征作为支持向量机（SVM）的输入向量，建立分类机制来区分波纹管结构。试验结果表明，文中提出的方法能有效地判断波纹管是否出现严重脱浆。

Ultrasonic detection was utilized to receive signal from corrugated pipe model and the EEMD method (ensemble empirical mode decomposition) was used to decompose signal into intrinsic mode function of multiple frequency spectrums (the IMF). When there is a defect in corrugated pipe, the echo signal's energy distribution in different frequency spectrums will be different. The main IMF component's energy entropy was taken as the input vector of SVM (support vector machine), then the mechanism of classification was set up to justify corrugated pipe's structure. The experimental results show that the proposed method can effectively judge the corrugated pipe's quality.