In the current study, a new structural damage detection algorithm is presented using the modified Hilbert–Huang transform and support vector machine. The modified Hilbert–Huang transform is an adaptive time–frequency analysis tool that alleviates the mode mixing issue encountered with Hilbert–Huang transform. On the other hand, since the measured vibration responses are generally nonlinear and non-stationary signals, the Fourier transform utilizing the sinusoidal functions is inadequate for their processing. Thus, the modified Hilbert–Huang transform is utilized to study the measured signals. The structural damage features are constructed with the Hilbert spectrum energy of selected intrinsic mode function obtained by decomposing the measured vibration signals with modified ensemble empirical mode decomposition. The support vector machine’s classification and regression algorithms are utilized to detect the location and extent of the damage, respectively. The offshore platform's experiment model is utilized for theoretical and experimental validation of the presented method's effectiveness.

在当前的研究中，提出了一种新的结构损伤检测算法，使用改进的 Hilbert-Huang 变换和支持向量机。改进的 Hilbert-Huang 变换是一种自适应时频分析工具，可缓解 Hilbert-Huang 变换遇到的模式混合问题。另一方面，由于测量的振动响应通常是非线性和非平稳信号，因此利用正弦函数的傅立叶变换不足以对其进行处理。因此，改进的 Hilbert-Huang 变换用于研究测量信号。结构损伤特征是用选定的本征模态函数的希尔伯特谱能量构建的，该本征模态函数是通过用改进的集合经验模态分解分解测量的振动信号获得的。支持向量机的分类和回归算法分别用于检测损伤的位置和程度。海上平台的实验模型用于理论和实验验证所提出方法的有效性。