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In the process of ultrasonic detection of nozzle fillet welds, due to the complex structure of the detected workpiece and the interference of the instrument itself by electrical signals, the detected A-scan signal has noise, and there will be "artifacts" in the detection image, thus causing detection difficulties. If we want to improve the quality of detection images, denoising of A-scan signals is particularly important. Therefore, this paper proposes a fillet weld defect signal reconstruction method combining wavelet denoising and empirical mode decomposition. Firstly, the structural characteristics of fillet weld are analyzed, and the phased array test is carried out to obtain the defect detection data. Secondly, the empirical mode decomposition and reconstruction of cracks and unfused defects are analyzed. Finally, the wavelet denoising and empirical mode decomposition and reconstruction of the original signal are carried out to achieve higher signal-to-noise ratio and lower mean square error than the traditional algorithm, which shows that this algorithm has better denoising effect and is more beneficial to the analysis of ultrasonic echo signal.