The invention relates to the technical field of electronic
manufacturing quality detection, and discloses a multilayer circuit board quality detection method and
system, and the method comprises the steps: collecting the surface interference fringe data of a circuit board through a computer-generated
holography technology, and reconstructing the three-dimensional position of an alignment mark;
internal stress distribution is detected through a photoacoustic
coupling system, and a three-dimensional stress
tensor field is reconstructed; establishing a PCB deformation dynamic model by using a multi-layer
time sequence deep learning network; establishing a stress deformation correlation model through a
physical information graph neural network; realizing feed-forward compensation and
process optimization according to a
dynamic prediction result; according to the method, computer-generated
holography, photoacoustic imaging and
deep learning technologies are integrated, the registration precision and
internal stress distribution of the multilayer circuit board can be detected in a lossless and high-precision mode, the dynamic change trend of the multilayer circuit board can be predicted,
active compensation and
process optimization are achieved, and the product quality and the manufacturing yield are effectively improved.