An Enhanced Factor Analysis of Performance Degradation Assessment on Slurry Pump Impellers
Slurry pumps, such as oil sand pumps, are widely used in industry to convert electrical energy to slurry potential and kinetic energy. Because of adverse working conditions, slurry pump impellers are prone to suffer wear, which may result in slurry pump breakdowns. To prevent any unexpected breakdow...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2017/1524840 |
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| _version_ | 1832550035177340928 |
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| author | Shilong Sun Peter W. Tse Y. L. Tse |
| author_facet | Shilong Sun Peter W. Tse Y. L. Tse |
| author_sort | Shilong Sun |
| collection | DOAJ |
| description | Slurry pumps, such as oil sand pumps, are widely used in industry to convert electrical energy to slurry potential and kinetic energy. Because of adverse working conditions, slurry pump impellers are prone to suffer wear, which may result in slurry pump breakdowns. To prevent any unexpected breakdowns, slurry pump impeller performance degradation assessment should be immediately conducted to monitor the current health condition and to ensure the safety and reliability of slurry pumps. In this paper, to provide an alternative to the impeller health indicator, an enhanced factor analysis based impeller indicator (EFABII) is proposed. Firstly, a low-pass filter is employed to improve the signal to noise ratios of slurry pump vibration signals. Secondly, redundant statistical features are extracted from the filtered vibration signals. To reduce the redundancy of the statistic features, the enhanced factor analysis is performed to generate new statistical features. Moreover, the statistic features can be automatically grouped and developed a new indicator called EFABII. Data collected from industrial oil sand pumps are used to validate the effectiveness of the proposed method. The results show that the proposed method is able to track the current health condition of slurry pump impellers. |
| format | Article |
| id | doaj-art-e09907cf982c4e17ab861c798255a713 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-e09907cf982c4e17ab861c798255a7132025-02-03T06:07:53ZengWileyShock and Vibration1070-96221875-92032017-01-01201710.1155/2017/15248401524840An Enhanced Factor Analysis of Performance Degradation Assessment on Slurry Pump ImpellersShilong Sun0Peter W. Tse1Y. L. Tse2Smart Engineering Asset Management Laboratory (SEAM), Department of Systems Engineering & Engineering Management, City University of Hong Kong, Kowloon Tong, Hong KongSmart Engineering Asset Management Laboratory (SEAM), Department of Systems Engineering & Engineering Management, City University of Hong Kong, Kowloon Tong, Hong KongSmart Engineering Asset Management Laboratory (SEAM), Department of Systems Engineering & Engineering Management, City University of Hong Kong, Kowloon Tong, Hong KongSlurry pumps, such as oil sand pumps, are widely used in industry to convert electrical energy to slurry potential and kinetic energy. Because of adverse working conditions, slurry pump impellers are prone to suffer wear, which may result in slurry pump breakdowns. To prevent any unexpected breakdowns, slurry pump impeller performance degradation assessment should be immediately conducted to monitor the current health condition and to ensure the safety and reliability of slurry pumps. In this paper, to provide an alternative to the impeller health indicator, an enhanced factor analysis based impeller indicator (EFABII) is proposed. Firstly, a low-pass filter is employed to improve the signal to noise ratios of slurry pump vibration signals. Secondly, redundant statistical features are extracted from the filtered vibration signals. To reduce the redundancy of the statistic features, the enhanced factor analysis is performed to generate new statistical features. Moreover, the statistic features can be automatically grouped and developed a new indicator called EFABII. Data collected from industrial oil sand pumps are used to validate the effectiveness of the proposed method. The results show that the proposed method is able to track the current health condition of slurry pump impellers.http://dx.doi.org/10.1155/2017/1524840 |
| spellingShingle | Shilong Sun Peter W. Tse Y. L. Tse An Enhanced Factor Analysis of Performance Degradation Assessment on Slurry Pump Impellers Shock and Vibration |
| title | An Enhanced Factor Analysis of Performance Degradation Assessment on Slurry Pump Impellers |
| title_full | An Enhanced Factor Analysis of Performance Degradation Assessment on Slurry Pump Impellers |
| title_fullStr | An Enhanced Factor Analysis of Performance Degradation Assessment on Slurry Pump Impellers |
| title_full_unstemmed | An Enhanced Factor Analysis of Performance Degradation Assessment on Slurry Pump Impellers |
| title_short | An Enhanced Factor Analysis of Performance Degradation Assessment on Slurry Pump Impellers |
| title_sort | enhanced factor analysis of performance degradation assessment on slurry pump impellers |
| url | http://dx.doi.org/10.1155/2017/1524840 |
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