Application of genetic algorithm in damage detection of reinforced concrete beams using piezo ceramic transducers

Abstract

Health monitoring of reinforced concrete bridges and other large-scale civil infrastructures has received considerable attention in recent years. However, traditional inspection methods (x-ray, C-scan, etc) are expensive and sometimes in-effective for large-scale structures. Piezo-ceramic transducers have emerged as new tools for the health monitoring of large-scale structures due to their advantages of active sensing, low cost, quick response, availability in different shapes, and simplicity for implementation. This study presents an experimental effort for the detection of damages in the reinforcement bars at lap zone of the reinforced concrete beams using Piezo-ceramic Transducers (PZTs) with the help of Genetic Algorithm (GA). An Electromechanical admittance (EMA) approach is used to evaluate the damages in the RC beams for standard lap length provided in IS 456 code and optimized lap length of bars. Tests are performed in i) steel reinforced bars with standard lap length embedded in a reinforcing concrete beam of 1.3m span subjected to flexural load for detecting the response and damages ii) steel reinforcing bar with optimized lap length given to a reinforced concrete beam of span 1.3m subjected to flexural load for detecting the response of healthy state beam. Test measurements of healthy and damaged steel bars in the lap zone of the reinforced concrete beam have been conducted using the developed monitoring system and piezo ceramic transducers.