Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component Analysis
This study proposes a fault diagnosis method (FD) for multistage centrifugal pumps (MCP) using informative ratio principal component analysis (Ir-PCA). To overcome the interference and background noise in the vibration signatures (VS) of the centrifugal pump, the fault diagnosis method selects the f...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/1/179 |
| _version_ | 1797497660363505664 |
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| author | Zahoor Ahmad Tuan-Khai Nguyen Sajjad Ahmad Cong Dai Nguyen Jong-Myon Kim |
| author_facet | Zahoor Ahmad Tuan-Khai Nguyen Sajjad Ahmad Cong Dai Nguyen Jong-Myon Kim |
| author_sort | Zahoor Ahmad |
| collection | DOAJ |
| description | This study proposes a fault diagnosis method (FD) for multistage centrifugal pumps (MCP) using informative ratio principal component analysis (Ir-PCA). To overcome the interference and background noise in the vibration signatures (VS) of the centrifugal pump, the fault diagnosis method selects the fault-specific frequency band (FSFB) in the first step. Statistical features in time, frequency, and wavelet domains were extracted from the fault-specific frequency band. In the second step, all of the extracted features were combined into a single feature vector called a multi-domain feature pool (MDFP). The multi-domain feature pool results in a larger dimension; furthermore, not all of the features are best for representing the centrifugal pump condition and can affect the condition classification accuracy of the classifier. To obtain discriminant features with low dimensions, this paper introduces a novel informative ratio principal component analysis in the third step. The technique first assesses the feature informativeness towards the fault by calculating the informative ratio between the feature within the class scatteredness and between-class distance. To obtain a discriminant set of features with reduced dimensions, principal component analysis was applied to the features with a high informative ratio. The combination of informative ratio-based feature assessment and principal component analysis forms the novel informative ratio principal component analysis. The new set of discriminant features obtained from the novel technique are then provided to the K-nearest neighbor (K-NN) condition classifier for multistage centrifugal pump condition classification. The proposed method outperformed existing state-of-the-art methods in terms of fault classification accuracy. |
| first_indexed | 2024-03-10T03:22:24Z |
| format | Article |
| id | doaj.art-bc67775f1c664768a5a5fe0a7391b7b1 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T03:22:24Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-bc67775f1c664768a5a5fe0a7391b7b12023-11-23T12:18:06ZengMDPI AGSensors1424-82202021-12-0122117910.3390/s22010179Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component AnalysisZahoor Ahmad0Tuan-Khai Nguyen1Sajjad Ahmad2Cong Dai Nguyen3Jong-Myon Kim4Department of Electrical, Electronics and Computer Engineering, University of Ulsan, Ulsan 44610, KoreaDepartment of Electrical, Electronics and Computer Engineering, University of Ulsan, Ulsan 44610, KoreaDepartment of Electrical, Electronics and Computer Engineering, University of Ulsan, Ulsan 44610, KoreaDepartment of Electrical, Electronics and Computer Engineering, University of Ulsan, Ulsan 44610, KoreaDepartment of Electrical, Electronics and Computer Engineering, University of Ulsan, Ulsan 44610, KoreaThis study proposes a fault diagnosis method (FD) for multistage centrifugal pumps (MCP) using informative ratio principal component analysis (Ir-PCA). To overcome the interference and background noise in the vibration signatures (VS) of the centrifugal pump, the fault diagnosis method selects the fault-specific frequency band (FSFB) in the first step. Statistical features in time, frequency, and wavelet domains were extracted from the fault-specific frequency band. In the second step, all of the extracted features were combined into a single feature vector called a multi-domain feature pool (MDFP). The multi-domain feature pool results in a larger dimension; furthermore, not all of the features are best for representing the centrifugal pump condition and can affect the condition classification accuracy of the classifier. To obtain discriminant features with low dimensions, this paper introduces a novel informative ratio principal component analysis in the third step. The technique first assesses the feature informativeness towards the fault by calculating the informative ratio between the feature within the class scatteredness and between-class distance. To obtain a discriminant set of features with reduced dimensions, principal component analysis was applied to the features with a high informative ratio. The combination of informative ratio-based feature assessment and principal component analysis forms the novel informative ratio principal component analysis. The new set of discriminant features obtained from the novel technique are then provided to the K-nearest neighbor (K-NN) condition classifier for multistage centrifugal pump condition classification. The proposed method outperformed existing state-of-the-art methods in terms of fault classification accuracy.https://www.mdpi.com/1424-8220/22/1/179fault diagnosismultistage centrifugal pumpprincipal component analysis |
| spellingShingle | Zahoor Ahmad Tuan-Khai Nguyen Sajjad Ahmad Cong Dai Nguyen Jong-Myon Kim Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component Analysis Sensors fault diagnosis multistage centrifugal pump principal component analysis |
| title | Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component Analysis |
| title_full | Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component Analysis |
| title_fullStr | Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component Analysis |
| title_full_unstemmed | Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component Analysis |
| title_short | Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component Analysis |
| title_sort | multistage centrifugal pump fault diagnosis using informative ratio principal component analysis |
| topic | fault diagnosis multistage centrifugal pump principal component analysis |
| url | https://www.mdpi.com/1424-8220/22/1/179 |
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