用GA-BP算法研究超音速电弧喷涂JCW-S-AM涂层显微硬度与工艺参数间的关系  

Study on Relation between the Microhardness of JCW-S-AM Coatings Prepared by High Velocity Arc Spray and the Process Parameters Using GA-BP Arithmetic

作　　者：汪刘应[1] 王汉功[1] 华绍春[1] 曹小平[2] 

机构地区：[1]第二炮兵工程学院,陕西西安710025 [2]国防科技大学,湖南长沙410073

出　　处：《稀有金属材料与工程》2006年第4期634-637,共4页Rare Metal Materials and Engineering

摘　　要：采用超音速电弧喷涂设备在不同工艺参数条件下制备JCW-S-AM涂层,利用显微硬度计测定各种涂层的显微硬度。根据测试结果,运用GA-BP算法构建涂层显微硬度与喷涂电压、喷涂电流的关系模型并进行工艺参数优化。研究结果表明:喷涂电压和喷涂电流对涂层显微硬度均有影响,呈现非线性规律,并且电压和电流之间存在交互作用;通过遗传算法优化,获得的最佳喷涂工艺参数为:喷涂电压29V,电流200A。此时JCW-S-AM涂层显微硬度最大。The microhardness of JCW-S-AM coatings prepared by high velocity electric arc spraying on conditions of different process parameters was tested by hardometer. According to the test results, the model on the relation between the JCW-S-AM coatings microhardness and the process parameters was established by means of GA-BP genetic neural network arithmetic. The optimum parameters were optimized with genetic algorithm. The results of analysis and calculation show that the spray voltage and spray current all affect the microhardness, and there exists certain interaction between spray voltage and spray current. By means of genetic algorithm, the optimum spray parameters theoretically are that spray voltage is 29 V, spray current is 200 A, the microhardness of JCW-S-AM coatings is biggest. Key words: high velocity electric arc spraying; microhardness; GA-BP genetic neural network arithmetic.

关 键 词：超音速电弧喷涂 显微硬度 GA-BP算法 

分 类 号：TG174.44[金属学及工艺—金属表面处理]