Chloride detection in concrete using wireless fidelity (Wi-Fi) signal

Corrosion is causing the gradual deterioration of a significant quantity of existing structures in many nations around the world. In reinforced concrete structures (RCS), chloride corrosion occurs more rapidly than carbonation corrosion. When affected, RCS must go through a repair or retrofitting process for further functioning. Therefore, early detection of corrosion attacks can save both the cost of repair and the expected/remaining service life of the structure. It is feasible to assess whether the structures are already corroding by measuring the level of chloride. This study reports a non-destructive method for detecting the chloride in concrete by using wireless fidelity (Wi-Fi) signal. A setup is developed with two Wi-Fi adapters and Wi-Fi analyzer software to detect the various amounts of chloride in concrete samples by means of attenuation (dB). Three different grades and thicknesses of concrete samples were prepared with known NaCl percentages of 0%, 5%, 10%, and 15%, and their attenuation values obtained by Wi-Fi signals were analyzed. An artificial neural network is employed to predict the actual NaCl with the model or predicted NaCl data. The result illustrated a measurable influence of the concrete grades, sample thickness, and percentages of NaCl on the attenuation values. Electrical resistivity, water absorption, and microstructures of the samples were investigated and correlated with the attenuation values. Successful use of this non-destructive technique can have a significant contribution in assessing the durability of many existing RCS.