[1]Qi Baolin,LI Lingjun,Li Zhinong.Research on failure mode recognition based on support vector machine[J].Journal of Zhengzhou University (Engineering Science),2007,28(01):9-11,15.[doi:10.3969/j.issn.1671-6833.2007.01.003]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
28卷
Number of periods:
2007年01期
Page number:
9-11,15
Column:
Public date:
1900-01-01
- Title:
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Research on failure mode recognition based on support vector machine
- Author(s):
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Qi Baolin; LI Lingjun; Li Zhinong
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- Keywords:
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- CLC:
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- DOI:
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10.3969/j.issn.1671-6833.2007.01.003
- Abstract:
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Support vector machines provide a new way for intelligent diagnosis that is constrained by the lack of a large number of fault samples. The feature vector is extracted from the vibration signal as the input of the support vector machine to identify the rolling bearing failure mode. Experiments show that the support vector machine still has excellent classification performance against rolling bearing failure modes under noisy conditions.