| 基于BP神经网络的钛-铝双丝超音速电弧喷涂涂层质量的预测 |
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| 引用本文： | 王汉功,胡重庆,李平,苏勋家,侯根良.基于BP神经网络的钛-铝双丝超音速电弧喷涂涂层质量的预测[J].机械工程材料,2003,27(7):22-24,34. |
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| 作者姓名： | 王汉功 胡重庆 李平 苏勋家 侯根良 |
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| 作者单位： | 第二炮兵工程学院使用维修工程教研室,陕西,西安,710025 |
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| 摘 要： | 用神经网络的分析方法，对超音速电弧喷涂钛-铝合金涂层制备的工艺过程进行分析，建立了喷涂电压、距离与涂层孔隙率、硬度和耐磨性之间的非线性映射关系，对不同的工艺参数，网络可以给出较为准确的预测值，证实了将人工神经网络模型应用于电弧喷涂钛-铝合金涂层质量预测和工艺优化是可行的和有效的。
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| 关 键 词： | BP神经网络 电弧喷涂 钛-铝合金涂层 孔隙率 硬度 质量预测 工艺优化 |
| 文章编号： | 1000-3738(2003)07-0022-03 |
Quality Prediction of Ultrasonic Arc Sprayed Ti-Al Alloy Coatings Based on Neural Network |
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| WANG Han-gong,HU Chong-qing,LI Ping,SU Xun-jia,HOU Gen-liang.Quality Prediction of Ultrasonic Arc Sprayed Ti-Al Alloy Coatings Based on Neural Network[J].Materials For Mechanical Engineering,2003,27(7):22-24,34. |
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| Authors: | WANG Han-gong HU Chong-qing LI Ping SU Xun-jia HOU Gen-liang |
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| Abstract: | Artificial neural network (ANN) technology for the processing of ultrasonic arc sprayed coatings is proposed. A metabolism model for predicting the qualities such as porosity, micro-hardness and slide-wear resistance of Ti-Al alloy coating with ANN is presented, which only needs the spray parameters. It is proved that the ANN technology is applicable for evaluating the coating qualities of ultrasonic arc sprayed Ti-Al alloy coating. |
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| Keywords: | artificial neural network arc spraying Ti-Al alloy coating porosity micro-hardness |
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