Damage identification method of cable-stayed bridges based on CEEMD and statistical parameters

Here, to solve problems of intrinsic mode function ( IMF ) components with noise and unable to quantify damage existing in cable-stayed bridges, signal decomposition obtained only with complementary ensemble empirical mode decomposition ( CEEMD ), a damage identification method for cable-stayed bridge based on combining CEEMD and statistical parameters method was proposed. This method could adaptively decompose dynamic response signals of cable-stayed bridge based on CEEMD, determine applicable amplitude standard deviation of white noise, and derive the integration times of CEEMD to obtain various orders of IMF components. Euclidean distance was used to perform spectral clustering analysis for the decomposed IMF components and avoid modal aliasing phenomena. The effective weight kurtosis index method for kurtosis statistical parameters was used to filter out noisy IMF components, extract effective IMF components, and reconstruct them for forming the sum of effective IMF components. Coefficient of variation statistical parameters, second-order central difference method and Taylor expansion were used to derive damage localization indexes. Damage quantification indexes were derived according to the 4-order statistical moment kurtosis statistical parameters. The proposed method was used to study damage identification of a cable-stayed bridge, and the results showed that the accuracy of damage localization and identification in simulation analysis is 100%; the maximum error in damage quantification is 1. 80%; under Gaussian white noise interference, damage localization is not affected, and the maximum error in damage quantification is 1. 88%; conducting damage identification of an actual bridge, no damage to its main beam is found. © 2024 Chinese Vibration Engineering Society. All rights reserved.