基于响应面的Q345C钢锈层激光清洗工艺参数优化

Optimization of Laser Cleaning Process Parameters for Q345C Steel Rust Layer Based on Response Surface

目的分析激光清洗工艺对Q345C钢表面质量的影响规律,优化激光清洗工艺参数,为Q345C钢管桩的激光除锈提供支撑。方法采用纳秒脉冲激光器对Q345C钢表面锈层进行清洗,分别使用Image-Pro-Puls软件、场发射扫描电镜以及共聚焦显微镜,测量Q345C钢表面去除率、表面氧元素含量及表面粗糙度。基于响应面分析,采用BOX-Benhnken组合方法进行试验设计,建立激光清洗工艺参数与清洗表面质量之间的数学关系,分析激光清洗工艺参数对清洗表面质量的交互影响趋势,在此基础上对工艺参数进行优化,并对优化结果进行试验验证。结果通过响应面分析可得,适用于100μm厚Q345C钢锈层的最佳清洗工艺参数为:激光功率53 W,重复频率80 kHz,振镜扫描速度5555 mm/s。清洗后表面质量良好,露出金属本身色泽,无残余锈层存在,达到Sa2.5级,表面去除率为91.37%,表面氧元素含量为2.41%,表面粗糙度为7.09μm,满足钢管桩除锈工艺要求。结论激光清洗工艺参数与清洗表面质量之间的数学关系,能够用于Q345C钢表面形貌预测及工艺参数优化。激光除锈采用合适的工艺参数,可以获得良好的表面质量和较高的除锈效率。

The work aims to analyze the influence of laser cleaning process on the surface quality of Q345 C steel rust layer and optimize the laser cleaning process parameters to provide support for laser derusting of Q345 C steel pipe pile. The rust layer on the surface of Q345 C steel was cleaned by nanosecond pulsed laser. The surface removal rate, surface oxygen content and surface roughness of Q345 C steel were measured respectively by Image-Pro-Puls software, field emission scanning electron microscope and confocal microscope. Based on the response surface methodology, the mathematical models between laser cleaning process parameters and cleaning surface quality were established under the combination design method of BOX-Benhnken to analyze the trend of interaction between laser cleaning process parameters on the cleaning surface quality. On this basis, the parameters were optimized and the optimization results were experimentally verified. According to the analysis of response surface, the optimum cleaning parameters for 100 μm thick Q345 C steel rust layer were: laser power of 53 W, repetition frequency of 80 kHz and scanning speed of galvanometer of 5555 mm/s. After laser cleaning, the surface quality was prestantious and exposed the color of the metal without residual rust layer, reaching the level of Sa2.5. Under the process parameters, the surface removal rate was 91.37%, the surface oxygen content was 2.41 wt%, and the surface roughness was 7.09 μm, which conformed to the requirements of rust removal technology for steel pipe pile. The mathematical model between the laser cleaning process parameters and the cleaning surface quality can be used for Q345 C steel surface topography prediction and process parameter optimization. Laser derusting can use the suitable process parameters to achieve good surface quality and high derusting efficiency.