| 基于RBF神经网络模型的司太立合金磨损量预测 |
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| 引用本文： | 宋江腾,曾攀,赵加清,李聪聪. 基于RBF神经网络模型的司太立合金磨损量预测[J]. 润滑与密封, 2011, 36(3). DOI: 10.3969/j.issn.0254-0150.2011.03.008 |
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| 作者姓名： | 宋江腾 曾攀 赵加清 李聪聪 |
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| 作者单位： | 清华大学机械系,北京,100084 |
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| 摘 要： | 司太立(Stellite)合金是一种能耐各种类型磨损、腐蚀以及高温氧化的硬质合金.为研究其磨损性能,以Stellite6为例,在自行设计的摩擦磨损机上进行室温干摩擦和润滑条件下的磨损实验.以实验数据为基础,建立该合金磨损量的RBF神经网络预测模型.结果表明:RBF神经网络预测模型具有较好的收敛效果和预测精度,具有良好的应用前景.
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| 关 键 词： | 司太立合金 RBF神经网络 磨损预测 |
Analysis of Stellite Alloys Wearing Prediction Based on Radial Basis Function Neural Network |
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| Song Jiangteng,Zeng Pan,Zhao Jiaqing,Li Congcong. Analysis of Stellite Alloys Wearing Prediction Based on Radial Basis Function Neural Network[J]. Lubrication Engineering, 2011, 36(3). DOI: 10.3969/j.issn.0254-0150.2011.03.008 |
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| Authors: | Song Jiangteng Zeng Pan Zhao Jiaqing Li Congcong |
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| Affiliation: | Song Jiangteng Zeng Pan Zhao Jiaqing Li Congcong (Mechanical Engineering Department,Tsinghua University,Beijing100084,China) |
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| Abstract: | The stellite alloys are hard alloys which can resist various wear,corrosion and oxidation at high temperature.In order to study the wearing behaviors of the stellite alloys,wear tests were carried out in the condition of dry friction and lubrication under room temperature by using a self-designed tribometer.According to the experimental results,a RBF neural network model was proposed to predict the wear loss of stellite alloys.The results show that the RBF neural network has good application prospects for g... |
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| Keywords: | stellite alloys RBF neural network wearing prediction |
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