Application of fuzzy neural network in the system of concrete undamaged inspection

Abstract

The accuracy of concrete strength inspection has a great influence on the safety evaluation of the building. In order to increase the accuracy, Fuzzy Neural Network (FNN) was built up to evaluate concrete stmngth: It takes full advantage of the characteristics of the common concrete testing methods: drill and rebound, and the abilities of FNN including automatic learning, generation and fuzzy logic inference. The experiment shows that the max relative error of the predicted results is 1.12%, which is satisfied with the requirements of the engineering. The method effieieatly maps the complex non-linear relationship between the drill values and the rebound values, and provides a efficient way for the concrete strength inspection and evaluation.