Research On Alternating Current Field Measurement Intelligent Identification Technology For Defects Based On FPGA

Aiming at the detection requirements of surface defect contour extraction and intelligent recognition,the finite element simulation models of different types of cracks are established in this paper based on the principle of alternating current field measurement(ACFM).The induced current distribution on the surface of the structure is analyzed.The law of defect shape—current disturbance—magnetic field distortion is explored.An intelligent defect recognition algorithm based on crack characteristic signal is proposed.The hardware platform of ACFM is developed with FPGA,the algorithm hardware is transplanted with Verilog HDL language.Finally,a set of ACFM defect identification system based on FPGA is constructed.The artificial prefabricated crack identification experiments are carried out to realize the intelligent identification of linear cracks and complex cracks from different angles,which provides theoretical basis and key data support for the reliability evaluation of structures.The thesis mainly researches from the following four aspects:(1)Theoretical research and simulation analysis of ACFMBased on the principle of ACFM,the finite element simulation models of different types of cracks are established by using ANSYS software.The distribution characteristics of induced current on the surface of structures are analyzed.The spatial magnetic field distortion signals of different types of defects are picked up.The law between different types of defects and defect characteristic signals is explored,which lays a theoretical foundation for subsequent defect surface contour reconstruction and intelligent recognition research.(2)Design of ACFM hardware platform based on FPGAAccording to the requirements of ACFM,the signal generation module with adjustable frequency and amplitude,AD acquisition module,root mean square processing module,data cache module and display driver module are designed based on the FPGA platform using the Verilog HDL.Functional simulation and timing verification of the above hardware modules are carried out to complete the functional debugging based on FPGA.The function of signal generation,acquisition,processing,caching and display are realized,which provides hardware support for the subsequent defect detection and intelligent identification experiments.(3)Research on intelligent defect recognition algorithmAccording to the law of characteristic signals of different types defects obtained by simulation,the inverse characteristic signals of intelligent recognition of defects are determined.The intelligent recognition algorithm is proposed for defects based on the characteristic signals,The algorithm function is simulated by the Verilog HDL language.By removing the background of defect characteristic signal and extracting the contour of defect surface,the intelligent identification of linear cracks and complex cracks with different angles is realized finally.(4)Development and testing of ACFM defect identification system based on FPGABased on the high-precision magnetic field sensor,the ACFM probe is designed,An ACFM case that integrated the detection probe and hardware platform is developed.The algorithm transplantation of the system is completed with the defect intelligent recognition algorithm as the core.A complete ACFM defect identification system is finally constructed based on FPGA.Laboratory tests of the artificial prefabricated cracks are carried out,which mainly includes the identification experiments of linear cracks and the complex cracks from different angles.The accuracy of the defect identification algorithm and the functional integrity of the system are verified.The results show that the intelligent identification of defects can be realized.