FAULT DIAGNOSIS BASED ON IMPROVED LOCALITY PRESERVING PROJECTIONS ALOGRITHM
Aiming at the problem that accuracy of orthogonal locality preserving projections（ LPP） for fault diagnosis is not high enough,a fault diagnosis method based on none parameter supervised kernel locality preserving projections（ NPSKLPP） for dimension reduction is proposed. In NPSKLPP,firstly,by chang...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2019-01-01
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| Series: | Jixie qiangdu |
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| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.06.005 |
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| _version_ | 1841535701052555264 |
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| author | LU Li CHEN Ying |
| author_facet | LU Li CHEN Ying |
| author_sort | LU Li |
| collection | DOAJ |
| description | Aiming at the problem that accuracy of orthogonal locality preserving projections（ LPP） for fault diagnosis is not high enough,a fault diagnosis method based on none parameter supervised kernel locality preserving projections（ NPSKLPP） for dimension reduction is proposed. In NPSKLPP,firstly,by changing the Euclidean distance to the Cosine distance which is more robust to outline,and constructing a none parameter nearest-neighbor graph which combined sample label information. And then use the nonlinear mapping to map the high dimension fault feature into an implicit feature space to dimension reduction. Thus a linear transformation is performed to preserve locality geometric structures of the fault feature,which solves the difficulty of parameter selection in computing affinity matrix,as a result,better fault diagnosis accuracy can achieved. The experiment results of gear fault diagnosis verified the effectiveness of the method. |
| format | Article |
| id | doaj-art-77321ef8cd8b43678ca53ec296f14c29 |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2019-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-77321ef8cd8b43678ca53ec296f14c292025-01-15T02:28:48ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692019-01-01411298130330606261FAULT DIAGNOSIS BASED ON IMPROVED LOCALITY PRESERVING PROJECTIONS ALOGRITHMLU LiCHEN YingAiming at the problem that accuracy of orthogonal locality preserving projections（ LPP） for fault diagnosis is not high enough,a fault diagnosis method based on none parameter supervised kernel locality preserving projections（ NPSKLPP） for dimension reduction is proposed. In NPSKLPP,firstly,by changing the Euclidean distance to the Cosine distance which is more robust to outline,and constructing a none parameter nearest-neighbor graph which combined sample label information. And then use the nonlinear mapping to map the high dimension fault feature into an implicit feature space to dimension reduction. Thus a linear transformation is performed to preserve locality geometric structures of the fault feature,which solves the difficulty of parameter selection in computing affinity matrix,as a result,better fault diagnosis accuracy can achieved. The experiment results of gear fault diagnosis verified the effectiveness of the method.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.06.005Fault diagnosisLocality preserving projectionsNone parameterSupervisedGear |
| spellingShingle | LU Li CHEN Ying FAULT DIAGNOSIS BASED ON IMPROVED LOCALITY PRESERVING PROJECTIONS ALOGRITHM Jixie qiangdu Fault diagnosis Locality preserving projections None parameter Supervised Gear |
| title | FAULT DIAGNOSIS BASED ON IMPROVED LOCALITY PRESERVING PROJECTIONS ALOGRITHM |
| title_full | FAULT DIAGNOSIS BASED ON IMPROVED LOCALITY PRESERVING PROJECTIONS ALOGRITHM |
| title_fullStr | FAULT DIAGNOSIS BASED ON IMPROVED LOCALITY PRESERVING PROJECTIONS ALOGRITHM |
| title_full_unstemmed | FAULT DIAGNOSIS BASED ON IMPROVED LOCALITY PRESERVING PROJECTIONS ALOGRITHM |
| title_short | FAULT DIAGNOSIS BASED ON IMPROVED LOCALITY PRESERVING PROJECTIONS ALOGRITHM |
| title_sort | fault diagnosis based on improved locality preserving projections alogrithm |
| topic | Fault diagnosis Locality preserving projections None parameter Supervised Gear |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.06.005 |
| work_keys_str_mv | AT luli faultdiagnosisbasedonimprovedlocalitypreservingprojectionsalogrithm AT chenying faultdiagnosisbasedonimprovedlocalitypreservingprojectionsalogrithm |