| 张 云,吕景伟.磨机减速机滚动轴承特征提取和故障诊断研究[J].水泥工程,2016,29(4):16-18 |
| 磨机减速机滚动轴承特征提取和故障诊断研究 |
| Research on fault diagnosis and feature extraction for rolling bearings of mill gearbox |
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| DOI： |
| 中文关键词: 磨机 滚动轴承 故障诊断 独立分量 特征提取 支持向量机 |
| 英文关键词: mill rolling bearing fault diagnose independent components feature extraction support vector machine |
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| 中文摘要: |
| 滚动轴承是水泥磨机减速机的核心组件，同时也是故障频发的部件之一，为保证其健康、安全、高效的运行，本文将独立分量分析（ICA）与支持向量机（SVM）方法结合，为磨机减速机滚动轴承的故障诊断提供一个新的思路。首先提取轴承不同故障状态下观测信号的独立分量，再对独立分量（ICA）进行奇异值分解从而得到特征信息，最后联合支持向量机（SVM）将特征信息进行故障识别。数据处理结果表明这种特征提取的方法是有效的。 |
| 英文摘要: |
| Rolling bearing is not only one of the mill reducer’s core components, but also one of components which tend to fail. In order to make it work in health, safety, efficience. This paper presents an intelligent method combined Independent Component Analysis(ICA) and Support Vector Machine(SVM) for rolling bearing’s fault diagnosis. Firstly, the independent components are extracted from observed signals in different faults state.Secondly, singular value decomposition to the extracted independent components is treated as eigenvalues.Finally, the eigenvalues can be classified based on Support Vector Machine(SVM).The data processing shows the method introduced in this paper is effective. |
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