Crack identification of a planar frame structure based on a synthetic artificial intelligence technique

It has been established that a crack has an important e ect on the dynamic behaviour of a structure. This e ect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a planar frame structure, a method is presented in this paper which uses a synthetic arti cial intelligence technique, i.e. adaptive-network-based fuzzy inference system (ANFIS) solved via a hybrid learning algorithm (the backpropagation gradient descent and the least-squares method) and continuous evolutionary algorithms (CEAs) solving single objective optimization problems with a continuous function and continuous search space e ciently are uni ed. With ANFIS and CEAs it is possible to formulate the inverse problem. ANFIS is used to obtain the input (the location and depth of a crack)–output (the structural eigenfrequencies) relation of the structural system. CEAs are used to identify the crack location and depth by minimizing the di erence from the measured frequencies. We have tried this idea on 2D beam structures and the results are promising