Load-Coupled Deformation Criterion-Driven Parametric Surface Reconstruction of Postservice Compressor Blades

Improving global shape consistency, local feature adaptability, authenticity, and reliability in surface reconstruction is crucial for key applications such as postservice compressor blade performance evaluation, damage diagnosis, and integrated repair. Traditional surface reconstruction methods typically rely on the original nominal model as a reference, ignoring the model mismatch problem caused by service deformation. Therefore, a load-coupled deformation criterion-driven parametric surface reconstruction algorithm is proposed. Specifically, a deformation criterion is quantitatively constructed by analyzing the coupling mechanisms of aerodynamic and centrifugal loads. An adaptive gridding algorithm for disordered point clouds is then developed, which confers the grid topology dependence while maintaining that the point cloud obeys the deformation distribution. In addition, a segmented trimming bicubic-nonuniform rational B-splines surface fitting algorithm is proposed to reconstruct a smooth and reliable real blade model. Experimental results demonstrate that the load-coupled deformation criterion could effectively guide the surface reconstruction, and the root mean square error is controlled within 0.013 mm, outperforming comparing algorithms.