Detection Of Reinforced Concrete Protecting Layer Thickness Based On The Neural Networks

The reinforced concrete structure is the construction of urban infrastructure, particular in residents housing, production and construction, a structure which is widespread used, and, reinforced concrete protective layer play an important role to ensure the structural mechanical properties, structure safety and persistence, structural fire resistance. Therefore, in the process of checking the reinforced concrete structure, especially the nondestructive testing, safety and accurate detection thickness of the protective layer, there is far-reaching significance in quality issues of construction engineering, society building and development of economy.The design studies on the reinforced concrete protective layer thickness detection system, uses the processor cores which is based on ARM as an application platform, uses the principle of electromagnetic induction method as the fulcrum of signal detection theory, uses the Elman neural network algorithm as the core technology which is processing and calculating the collected data. The system is made up of prompting signal module, detecting signal collection module, system disposal module. After the system powers, sending the excitation signal which has a certain frequency generated by the excitation signal module into the excitation coil, inducing the second magnetic field which feedback through the reinforce in the protective layer by the detection coil, using processor system to analysis and processing the real-time data, and calculate out the value of the thickness of reinforced concrete layer, and show the data on the LCD monitor. The design uses Prote199SE software to complete the construction of the system hardware circuit, at the same time, uses the ADS1.2 function environment and the modular structured software programming ideas to progress system software design, debugging and implementation, including data collection, control running system, data access and preparation of the man-machine interface software, forms hand-held detecting device combination of embed control, high-speed data acquisition and processtion, friendly human computer interaction interface to detect the reinforced concrete protective layer.The result of the designed experiment show that the system can solve the accuracy of detection problem created in the test by combining the software and hardware. Using the neural network to deal with the test data can improve the degree of automation and accuracy, reduce the detection time. The detection device have the function of detecting the reinforced concrete protective layer thichness. Getting a more accurate results by using of detection device and software to actually measure the protective layer thickness.