基于BP模型的截齿WC-Co涂层耐磨性预测研究

The Prediction of Wear Resistance of WC-Co Coatings of Shearer Pick Based on BP Model

为提高采煤机械上截齿的耐磨性能,在42Cr Mo钢表面利用超音速火焰喷涂法制备WC-Co涂层。用BP神经网络模型进行WC-Co涂层的耐磨性能的预测,当采用3×8×1的模型结构时,实测结果与预测结果很接近,效果比较好。采用扫描电镜和摩擦磨损试验机进行磨损形貌和磨损性能分析。分析表明,WC-Co涂层的磨损是粘着磨损和磨粒磨损两种机制共同作用的结果。当喷涂粉末丙烷流量32 L/min、喷涂距离290 mm和送粉率34 g/min时,WC-12Co涂层的磨损量较小;当喷涂粉末丙烷流量34 L/min、喷涂距离270 mm和送粉率36 g/min时,WC-17Co涂层的磨损量较小。

In order to improve the wear resistance of shearer pick on the coal mining machinery,WC-Co coatings were successfully prepared on the surface of 42 Cr Mo by using HVOF method. The wear resistance of WC-Co coatings was predicted using BP neural network model. When the model structure of 3 × 8 × 1 is used,the measured results are very close to the predicted results,showing good effects. The wear morphology and wear resistance were studied by SEM and abrasion tester. The analysis shows that the wear mechanism of coating is an interaction of adhesion and abrasion. It presents that the weight loss of the WC-12 Co coating is less at propane gas flow rate of 32 L / min,spraying distance of 290 mm,and powder feed rate of 34 g / min. The weight loss of the WC-17 Co coating is less at propane gas flow rate of 34 L / min,spraying distance of 270 mm,and powder feed rate of 36 g / min.