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| 基于矢谱和D-S理论的旋转机械故障诊断方法研究 | |
| 引用本文： | 董辛旻,韩捷,石来德.基于矢谱和D-S理论的旋转机械故障诊断方法研究[J].煤矿机械,2007,28(5):179-180. |
| 作者姓名： | 董辛旻 韩捷 石来德 |
| 作者单位： | 1. 郑州大学,振动工程研究所,郑州,450002;同济大学,机械工程学院,上海,200092 2. 郑州大学,振动工程研究所,郑州,450002 3. 同济大学,机械工程学院,上海,200092 |
| 摘 要： | 旋转机械结构复杂,不同方面的特征信号只从不同侧面反映设备的故障,都有一定的局限性。在对旋转机械进行故障诊断时,需要对设备的多种特征信号进行融合处理和综合诊断。运用多神经网络与证据理论融合的设备故障综合诊断方法,有效提高诊断结果的准确性和可靠性。 |
| 关 键 词： | 旋转机械 神经网络 D-S证据理论 综合诊断 |
| 文章编号： | 1003-0794（2007）05-0179-02 |
| 修稿时间： | 2007-01-23 |
Diagnostic Way Study of Rotating Machine Fault Based on Vector Frequency and D-S Theory |
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| DONG Xin-min,HAN Jie,SHI Lai-de.Diagnostic Way Study of Rotating Machine Fault Based on Vector Frequency and D-S Theory[J].Coal Mine Machinery,2007,28(5):179-180. | |
| Authors: | DONG Xin-min HAN Jie SHI Lai-de |
| Affiliation: | 1. Vibration Engineering Research Institute, Zhengzhou University, Zhengzhou 450002, China; 2. College of Mechanical Engineering, Tongii University, Shanghai 200092, China |
| Abstract: | Due to complexity of the structure of rotating machine, phenomenon of rotating machine, and any kinds of signature has its localization. Thus the synthetic disposal and cooperative analysis for multi - characteristic signal of rotating machine are needed. A synthetic diagnosis method used multi - neural network and evidence theory for rotating machine fault diagnosis is adopted, The diagnostic results show accuracy and reliability are improved effectively. |
| Keywords: | rotating machine neural networks D- S evidential reasoning integrated diagnosis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |