This research proposes a virtual restoration system and method for 3D digital cultural relics based on a fuzzy logic algorithm, aiming to solve the problems of the low classification accuracy and poor splicing effect of Terra Cotta Warrior fragments. This method adopts a series of steps to improve the efficiency and accuracy of fragment splicing. Firstly, features such as curvature, torsion, and left and right chord lengths were extracted from the fracture surface contour lines of the cultural relic fragments to form feature vectors. Then, the feature vector was fused and compressed by using the multilayer perceptron. The multilayer perceptron is a neural network model that can process and learn input data via multiple levels of computation, resulting in more expressive feature representations. Next, we used the calculation results of the multilayer perceptron to perform the splicing operation on the fragments. This means that, based on the calculation results of the feature vectors, the system can automatically select appropriate splicing methods to accurately match and splice fragments. Finally, by adjusting the weight of the multilayer perceptron, the error rate of fragment splicing can be reduced, further improving the accuracy of repair. The experimental results show that the method proposed in this article is significantly better than traditional methods in terms of time consumption and can effectively improve the efficiency of fragment matching and stitching. Conclusion: The fragment-stitching algorithm based on multi-feature adaptive fusion improved the speed and effectiveness of stitching in fragment-stitching tasks. In summary, the fragment-stitching algorithm based on multi-feature adaptive fusion can improve the speed and effectiveness of stitching in fragment-stitching tasks. The application of this method is expected to play an important role in the field of cultural relic protection, such as the restoration of Terra Cotta Warrior fragments.