基于双频数据融合的电涡流焊接缺陷检测

焊缝表面纹理引起的干扰信号限制了电涡流检测技术对焊接中缺陷的检出，将矩形激励线圈和GMR器件相结合，设计了电涡流检测探头，仿真分析了在0.5,1和4 kHz激励频率条件下该探头检测的磁感应强度的分布规律，并选择0.5,4 kHz构成混频激励，针对这两个频率下的检测数据，提出了对于这两个激励频率数据的融合方法，以FPGA为核心，结合X-Y数控平台，构建了试验平台，针对实际铝合金焊接缺陷进行了试验. 结果表明，该方法在抑制焊接表面纹理造成的干扰信号的同时，也抑制了两个焊接铝合金板夹角引起的干扰，对于直径小于1 mm的亚表面缺陷，虽然两个激励频率下的数据很难清晰体现缺陷，但是采用该方法可被成功检测.

Eddy current defect detection on welds based on dual-frequency data fusion

The interference signal caused by weld surface texture leads to the difficulty of the defect detection in eddy current detection technology. A dual-frequency data fusion method combined with the design of the sensor was proposed. The sensor includes a rectangle excitation coil and a giant magneto resistance (GMR) element. 500 Hz and 4 kHz are chosen as the excitation frequencies, and the distribution of magnetic induction intensity at the excitation frequencies of 500 Hz, 1 kHz and 4 kHz were simulated by the finite element analysis. The affine transformation matrix of real part and imaginary part data at the two frequencies was constructed through the least square method. The detection affine transformation data at the reference frequency were fused with the data at the basic frequency. The experiment was carried out on aluminum-alloy welding defect. The result indicates that this method suppresses not only the interference signal of weld surface texture, but also the interference caused by the angle of two welded aluminum-alloy plate. The defects of less than 1 mm in diameter were hardly reflected though data at two excitation frequencies independently, but they can be successfully detected by the proposed method.