Fault Detection of Bearing Systems through EEMD and Optimization Algorithm
This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/17/11/2477 |
| _version_ | 1811264249549291520 |
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| author | Dong-Han Lee Jong-Hyo Ahn Bong-Hwan Koh |
| author_facet | Dong-Han Lee Jong-Hyo Ahn Bong-Hwan Koh |
| author_sort | Dong-Han Lee |
| collection | DOAJ |
| description | This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space. |
| first_indexed | 2024-04-12T20:00:45Z |
| format | Article |
| id | doaj.art-25dbb23b0b4a4bcfbc2ad738a6b706e6 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-12T20:00:45Z |
| publishDate | 2017-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-25dbb23b0b4a4bcfbc2ad738a6b706e62022-12-22T03:18:32ZengMDPI AGSensors1424-82202017-10-011711247710.3390/s17112477s17112477Fault Detection of Bearing Systems through EEMD and Optimization AlgorithmDong-Han Lee0Jong-Hyo Ahn1Bong-Hwan Koh2Department of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro 1 gil, Jung-gu, Seoul 100-715, KoreaDepartment of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro 1 gil, Jung-gu, Seoul 100-715, KoreaDepartment of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro 1 gil, Jung-gu, Seoul 100-715, KoreaThis study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space.https://www.mdpi.com/1424-8220/17/11/2477EEMDIsomapPSOfault detectionfeature extraction |
| spellingShingle | Dong-Han Lee Jong-Hyo Ahn Bong-Hwan Koh Fault Detection of Bearing Systems through EEMD and Optimization Algorithm Sensors EEMD Isomap PSO fault detection feature extraction |
| title | Fault Detection of Bearing Systems through EEMD and Optimization Algorithm |
| title_full | Fault Detection of Bearing Systems through EEMD and Optimization Algorithm |
| title_fullStr | Fault Detection of Bearing Systems through EEMD and Optimization Algorithm |
| title_full_unstemmed | Fault Detection of Bearing Systems through EEMD and Optimization Algorithm |
| title_short | Fault Detection of Bearing Systems through EEMD and Optimization Algorithm |
| title_sort | fault detection of bearing systems through eemd and optimization algorithm |
| topic | EEMD Isomap PSO fault detection feature extraction |
| url | https://www.mdpi.com/1424-8220/17/11/2477 |
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