| 基于数据融合技术的发动机磨损模式识别方法 |
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| 引用本文： | 张培林,李兵,任国全. 基于数据融合技术的发动机磨损模式识别方法[J]. 润滑与密封, 2007, 32(6): 60-63 |
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| 作者姓名： | 张培林 李兵 任国全 |
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| 作者单位： | 南京理工大学,江苏南京,210094;军械工程学院,河北石家庄,050003 |
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| 摘 要： | 针对单一的智能模型在发动机磨损模式识别中的局限性,提出了一种基于数据融合技术的多模型磨损模式识别方法。它利用模糊优选模型、神经网络模型和灰色关联度模型等3种单一智能模型的识别结果作为信息源,经D-S证据理论对其进行融合得到最终识别结果。实际计算表明,该模型具有良好的通用性、适应性和容错性,比单一的智能模型具有更好的识别效果。
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| 关 键 词： | 数据融合技术 D-S证据理论 内燃机 磨损模式识别 |
| 文章编号： | 0254-0150（2007）6-060-4 |
| 修稿时间： | 2007-01-05 |
A Multi-intelligent Model Based on Data Fusion in the Application of Wear Pattern Recognition |
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| Zhang Peilin,Li Bing,Ren Guoquan. A Multi-intelligent Model Based on Data Fusion in the Application of Wear Pattern Recognition[J]. Lubrication Engineering, 2007, 32(6): 60-63 |
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| Authors: | Zhang Peilin Li Bing Ren Guoquan |
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| Affiliation: | 1. Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China; 2. Ordnance Engineering College, Shijiazhuang Hebei 050003, China |
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| Abstract: | In order to overcome the disadvantages of single model for wear pattern recognition of engine, a multi-intelligent model based on the data fusion technology was proposed. The results of three single model ,fuzzy optimum model, neural network model and grey correlation degree model were used as the different data sources, an improved result was obtained by combination them used the effective data fusion technique D-S evidence theory. According to the application in the wear pattern recognition, the new method can get a more precise result in comparison with the single method. |
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| Keywords: | data fusion technology D-S evidence theory internal combustion engines wear pattern recognition |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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