目的 实现六分束激光在Ni60/WC涂层表面烧蚀目标织构激光加工工艺参数的精确选择。方法 基于CCD响应面法，设计在不同的激光工艺参数下对Ni60/WC涂层表面进行织构烧蚀试验，以激光频率、扫描次数、扫描速度为影响因素，以圆凹坑织构直径、深度及由其直径和深度综合加权所得的综合目标为响应目标，建立目标织构所需激光工艺参数的预测模型，以织构直径、深度及综合目标作为优化条件，对预测模型进行实验验证。结果 扫描次数对织构直径的影响最显著，单个脉冲光斑上所聚集的能量大小是影响织构直径误差的关键因素。对织构深度影响最显著为扫描次数和频率，织构深度与扫描次数、频率呈正相关，不同因素间的交互作用是影响织构加工结果的关键。通过对预测模型所优选的参数进行实验验证发现，以织构直径和深度、综合目标建立的预测模型优选工艺参数所加工圆凹坑织构的质量评价指标与其预测指标的误差率分别为19.37%、3.57%。功率为6 W时，六分束激光加工最优工艺参数为速度5 500 mm/s、频率400 kHz、扫描2次。结论 通过综合目标建立的Ni60/WC涂层表面圆凹坑织构六分束激光加工参数优选预测模型精确程度较高，能够实现Ni60/WC涂层表面加工所需织构激光参数的准确预测，为涂层表面织构加工激光参数精确选择提供了理论依据。

The research shows that the bionic texture on the surface of the moving pair has a significant improvement on the surface interface wear resistance and lubrication properties, reasonable micro-pit texture design and laser beam splitting technology applied on the Ni60/WC coating can significantly improve the wear resistance of the fracturing pump plunger dynamic seal system. However, the efficiency of selecting texture laser processing parameters by experimental method is very low, which is not conducive to the fast and accurate selection of processing parameters of target texture. In order to directly obtain the functional relationship between process parameters and machining targets under beam splitting laser, the prediction model of processing target parameters and six-beam laser processing process parameters was established, and the interaction between laser frequency, scanning speed and scanning times and the influence of response target on the optimization of surface texture ablation parameters of the Ni60/WC coating were discussed. A six-beam picosecond laser micro-machining platform was established. A circular pit texture with a diameter of 200 μm was arranged on the surface of the Ni60/WC coating using the processing parameters designed by the CCD response surface method. The three-dimensional morphology of the circular pit morphology was tested with a white light interferometer. The laser processing parameters were optimized by the prediction models with different target suggestions, and the effects of laser frequency, scanning speed and scanning times on the pits were analyzed by the perturbation diagram generated by Design-Expert software and the 3D relationship diagram of different influencing factors. The results showed that:as the index of machining optimization, the scanning times had the most significant influence on the texture diameter; but as the preset value, the energy gathered on a single pulse spot was the key factor affecting the texture diameter error. The most significant influence on texture depth was the scanning frequency and the scanning frequency, and the texture depth was positively correlated with the scanning frequency and the laser frequency. The interaction between different influencing factors was a key point affecting the texture processing results. Through the experimental verification of the optimized parameters of the prediction model, it was found that the error rates of the quality evaluation index of the circular pit texture and its prediction index were 19.37% and 3.57%, respectively, in the optimization process parameters of the prediction model established with the texture diameter, depth and comprehensive target. When the laser power was 6 W, the optimal process parameter combination of six-beam laser processing was as follows:speed at 5 500 mm/s, frequency at 400 kHz and scanning times of 2. Taking the comprehensive objective obtained by the comprehensive weighting method as the response objective, the optimization prediction model of rounded pit texture six-beam laser processing parameters of the Ni60/WC coating surface established by the response surface method has a high accuracy, which can realize the accurate prediction of texture laser parameters required by Ni60/WC coating surface processing, and avoid the repetitive and tedious process in the selection of processing parameters by the experimental method. It lays an experimental foundation for the further research and application of bionic texture in the field of fracturing pump plunger processing.