Damage identification method for guide wall structures based on a hybrid algorithm of clonal selection and particle swarm optimization

The guide wall structure in hydraulic engineering is subjected to long-term complicated loads, such as, alternative water pressure and wind pressure, they may lead to the damage of structures. However, damage detection is difficult to implement in large hydraulic structures under ambient excitation because of the uncertainty of ambient excitation and the limitation of the test condition and precision. Here, a new damage detection method using a real encoding hybrid algorithm of clonal selection and particle swarm optimization to optimize the modal frequency index was proposed for guide wall structures. The proposed method only needed lower modal frequencies, thus it was suitable for nondestructive dynamic damage detection of large hydraulic structures under ambient excitation. Taking a certain guide wall structure as an example, the results showed that this method has advantages in the global searching performance and identification accuracy; the proposed method is effective and can be applied in many types of large hydraulic structures.