关键词: 气缸套内表面;基准滤波;基准拟合;L回归稳健

Abstract: For lubrication, energy saving and emission reduction, some "valley" textures are required for the finishing cylinder liner inner surface to store oil, but some difficulties are brought by this hierarchical functional surface during the surface quality assessment .The reference which is extracted by traditional filtering method and the baseline fitting method often be lowered by the " valley " and eventually deviate from the ideal surface , resulting in the distortion of the reference plane , making the subsequent parameters can not be assessed precisely. Nowadays, to solve this problem, robust Gaussian regression filtering is highly recognized, but eventually being too time -consuming and can not be promoted. Therefore, a new robust regression fitting algorithm is proposed, which is based on quadratic function and trigonometric function, combined with the Levenberg- Marquardt algorithm’s minimizes the maximum deviation (least absolute value, L) regression method, making lower the impact of outlier on the hierarchical functional surface ,then, reconstruct the datum quickly and perfectly to be achieved. The simulation results show that compared with least squares (Ls), robustness is greatly improved by the proposed method; compared with Gaussian regression filter, it has the same robustness, but the speed increases nearly 105 times, and the deviation between the surface in three-dimensional amplitude parameters and function parameters with the true value do not exceed 2% in the ISO 25178-2 standard. Finally, the experiments are conducted on the actual cylinder liner inner wall surface, and the results show that the new method is more robust comparing with Ls, more time-saving comparing with Gaussian regression filter, and it has high precision and high efficiency during extracting datum.

Key words: inner wall of the cylinder jackets;the reference filter;the reference fitting;Lrobust regression