| 基于数据挖掘的齿轮副磨损状态评估方法 |
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| 引用本文： | 张怀亮,刘森,邹佰文.基于数据挖掘的齿轮副磨损状态评估方法[J].西南交通大学学报,2015,28(4):710-716. |
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| 作者姓名： | 张怀亮 刘森 邹佰文 |
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| 基金项目： | 国家863计划资助项目(2014AA041602) |
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| 摘 要： | 为了提高齿轮副磨损状态评估的准确率,基于数据挖掘技术提出了一种新的齿轮副磨损状态评估方法.该方法通过设计直齿圆柱齿轮副磨损实验,提取实验齿轮副全寿命周期内的油液参数和振动参数,对齿轮副磨损状态进行聚类划分,建立了监测参数与齿轮副磨损状态之间的关联规则集及齿轮副磨损状态关联规则匹配算法,用于识别齿轮副的磨损状态.研究结果表明:基于数据挖掘的齿轮副磨损状态评估方法对齿轮副磨损状态的识别率达90%,能有效地评估齿轮副磨损状态.
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| 关 键 词： | 齿轮磨损 数据挖掘 状态评估 磨粒群 分形维数 关联规则 |
| 收稿时间： | 2014-09-06 |
Assessment Method of Gear Wear Condition Based on Data Mining |
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| ZHANG Huailiang,LIU Sen,ZOU Baiwen.Assessment Method of Gear Wear Condition Based on Data Mining[J].Journal of Southwest Jiaotong University,2015,28(4):710-716. |
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| Authors: | ZHANG Huailiang LIU Sen ZOU Baiwen |
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| Abstract: | To improve the accuracy of gear wear condition assessment, a novel gear wear condition assessment method based on data mining technology was proposed. In this method, a spur gear pair wear test was designed to extract oil parameters and vibration parameters within the whole life cycle of the gear pair first. Then, a clustering division of gear pair wear conditions was made, based on which, the association rules set between the monitoring parameters and gear pair wear conditions was obtained. Finally, a matching algorithm of association rules was developed to recognize the gear pair wear condition, and verified using the test data extracted from the wear test. The results show that the proposed gear wear assessment method based on data mining can effectively assess the wear condition of gear pairs, and the recognition rate is about 90%. |
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