Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator
Remaining useful life (RUL) prediction can provide early warnings of failure and has become a key component in the prognostics and health management of systems. Among the existing methods for RUL prediction, the Wiener-process-based method has attracted great attention owing to its favorable propert...
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| Main Authors: | , , , , , |
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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/10.1155/2017/6754968 |
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| _version_ | 1832560329063661568 |
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| author | Aisong Qin Qinghua Zhang Qin Hu Guoxi Sun Jun He Shuiquan Lin |
| author_facet | Aisong Qin Qinghua Zhang Qin Hu Guoxi Sun Jun He Shuiquan Lin |
| author_sort | Aisong Qin |
| collection | DOAJ |
| description | Remaining useful life (RUL) prediction can provide early warnings of failure and has become a key component in the prognostics and health management of systems. Among the existing methods for RUL prediction, the Wiener-process-based method has attracted great attention owing to its favorable properties and flexibility in degradation modeling. However, shortcomings exist in methods of this type; for example, the degradation indicator and the first predicting time (FPT) are selected subjectively, which reduces the prediction accuracy. Toward this end, this paper proposes a new approach for predicting the RUL of rotating machinery based on an optimal degradation indictor. First, a genetic programming algorithm is proposed to construct an optimal degradation indicator using the concept of FPT. Then, a Wiener model based on the obtained optimal degradation indicator is proposed, in which the sensitivities of the dimensionless parameters are utilized to determine the FPT. Finally, the expectation of the predicted RUL is calculated based on the proposed model, and the estimated mean degradation path is explicitly derived. To demonstrate the validity of this model, several experiments on RUL prediction are conducted on rotating machinery. The experimental results indicate that the method can effectively improve the accuracy of RUL prediction. |
| format | Article |
| id | doaj-art-9523a053383e44df9b1870c9ecea2a66 |
| 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-9523a053383e44df9b1870c9ecea2a662025-02-03T01:27:50ZengWileyShock and Vibration1070-96221875-92032017-01-01201710.1155/2017/67549686754968Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation IndicatorAisong Qin0Qinghua Zhang1Qin Hu2Guoxi Sun3Jun He4Shuiquan Lin5Guangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis, Guangdong University of Petrochemical Technology, Maoming 525000, ChinaGuangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis, Guangdong University of Petrochemical Technology, Maoming 525000, ChinaGuangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis, Guangdong University of Petrochemical Technology, Maoming 525000, ChinaGuangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis, Guangdong University of Petrochemical Technology, Maoming 525000, ChinaGuangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis, Guangdong University of Petrochemical Technology, Maoming 525000, ChinaGuangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis, Guangdong University of Petrochemical Technology, Maoming 525000, ChinaRemaining useful life (RUL) prediction can provide early warnings of failure and has become a key component in the prognostics and health management of systems. Among the existing methods for RUL prediction, the Wiener-process-based method has attracted great attention owing to its favorable properties and flexibility in degradation modeling. However, shortcomings exist in methods of this type; for example, the degradation indicator and the first predicting time (FPT) are selected subjectively, which reduces the prediction accuracy. Toward this end, this paper proposes a new approach for predicting the RUL of rotating machinery based on an optimal degradation indictor. First, a genetic programming algorithm is proposed to construct an optimal degradation indicator using the concept of FPT. Then, a Wiener model based on the obtained optimal degradation indicator is proposed, in which the sensitivities of the dimensionless parameters are utilized to determine the FPT. Finally, the expectation of the predicted RUL is calculated based on the proposed model, and the estimated mean degradation path is explicitly derived. To demonstrate the validity of this model, several experiments on RUL prediction are conducted on rotating machinery. The experimental results indicate that the method can effectively improve the accuracy of RUL prediction.http://dx.doi.org/10.1155/2017/6754968 |
| spellingShingle | Aisong Qin Qinghua Zhang Qin Hu Guoxi Sun Jun He Shuiquan Lin Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator Shock and Vibration |
| title | Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator |
| title_full | Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator |
| title_fullStr | Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator |
| title_full_unstemmed | Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator |
| title_short | Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator |
| title_sort | remaining useful life prediction for rotating machinery based on optimal degradation indicator |
| url | http://dx.doi.org/10.1155/2017/6754968 |
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