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采用电沉积法在T8钢试样表面制备Ni-TiN纳米镀层,在正交试验基础上,通过RBF神经网络对Ni-TiN纳米镀层的腐蚀速率进行预测研究。利用原子力显微镜、扫描电镜和X射线衍射仪对镀层腐蚀前后的表面形貌及镀层物相组成进行分析。结果表明:当TiN粒子质量浓度为9 g/L、镀液温度为40℃、电流密度为0.6 A/dm~2时,RBF神经网络预测的腐蚀速率为3.152 mg/m~2·h,而实测值为3.163 mg/m~2·h,相对误差仅为0.35%;镀层表面较平整,颗粒较细小。腐蚀实验后,镀层的腐蚀坑较小且无明显腐蚀产物,耐腐蚀性能良好。
The Ni-TiN nano-coating was prepared on the surface of T8 steel by electrodeposition method. The corrosion rate of Ni-TiN nano-coating was predicted by RBF neural network on the basis of orthogonal experiment. Atomic force microscope, scanning electron microscopy and X-ray diffractometer were used to analyze the surface morphology and coating phase composition before and after coating corrosion. The results show that the predicted corrosion rate of RBF neural network is 3.152 mg / m ~ 2 · h when the mass concentration of TiN particles is 9 g / L, the bath temperature is 40 ℃ and the current density is 0.6 A / dm ~ 2 The measured value is 3.163 mg / m ~ 2 · h, the relative error is only 0.35%. The surface of the coating is relatively flat and the particles are finer. After the corrosion test, the corrosion pits of the coating are smaller and have no obvious corrosion products, and the corrosion resistance is good.