A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines
Remaining useful life (RUL) estimation is considered as one of the most central points in the prognostics and health management (PHM). The present paper describes a nonlinear hybrid ABC–MARS-based model for the prediction of the remaining useful life of aircraft engines. Indeed, it is well-known tha...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2016-05-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/9/6/409 |
| _version_ | 1828153325703397376 |
|---|---|
| author | Paulino José García Nieto Esperanza García-Gonzalo Antonio Bernardo Sánchez Marta Menéndez Fernández |
| author_facet | Paulino José García Nieto Esperanza García-Gonzalo Antonio Bernardo Sánchez Marta Menéndez Fernández |
| author_sort | Paulino José García Nieto |
| collection | DOAJ |
| description | Remaining useful life (RUL) estimation is considered as one of the most central points in the prognostics and health management (PHM). The present paper describes a nonlinear hybrid ABC–MARS-based model for the prediction of the remaining useful life of aircraft engines. Indeed, it is well-known that an accurate RUL estimation allows failure prevention in a more controllable way so that the effective maintenance can be carried out in appropriate time to correct impending faults. The proposed hybrid model combines multivariate adaptive regression splines (MARS), which have been successfully adopted for regression problems, with the artificial bee colony (ABC) technique. This optimization technique involves parameter setting in the MARS training procedure, which significantly influences the regression accuracy. However, its use in reliability applications has not yet been widely explored. Bearing this in mind, remaining useful life values have been predicted here by using the hybrid ABC–MARS-based model from the remaining measured parameters (input variables) for aircraft engines with success. A correlation coefficient equal to 0.92 was obtained when this hybrid ABC–MARS-based model was applied to experimental data. The agreement of this model with experimental data confirmed its good performance. The main advantage of this predictive model is that it does not require information about the previous operation states of the aircraft engine. |
| first_indexed | 2024-04-11T22:23:34Z |
| format | Article |
| id | doaj.art-3a3338916bfe4447b3d896ac571d3a2a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T22:23:34Z |
| publishDate | 2016-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-3a3338916bfe4447b3d896ac571d3a2a2022-12-22T03:59:55ZengMDPI AGEnergies1996-10732016-05-019640910.3390/en9060409en9060409A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft EnginesPaulino José García Nieto0Esperanza García-Gonzalo1Antonio Bernardo Sánchez2Marta Menéndez Fernández3Department of Mathematics, Faculty of Sciences, University of Oviedo, C/Calvo Sotelo s/n, 33007 Oviedo, SpainDepartment of Mathematics, Faculty of Sciences, University of Oviedo, C/Calvo Sotelo s/n, 33007 Oviedo, SpainDepartment of Mining Technology, Topography and Structures, University of León, 24071 León, SpainDepartment of Mining Technology, Topography and Structures, University of León, 24071 León, SpainRemaining useful life (RUL) estimation is considered as one of the most central points in the prognostics and health management (PHM). The present paper describes a nonlinear hybrid ABC–MARS-based model for the prediction of the remaining useful life of aircraft engines. Indeed, it is well-known that an accurate RUL estimation allows failure prevention in a more controllable way so that the effective maintenance can be carried out in appropriate time to correct impending faults. The proposed hybrid model combines multivariate adaptive regression splines (MARS), which have been successfully adopted for regression problems, with the artificial bee colony (ABC) technique. This optimization technique involves parameter setting in the MARS training procedure, which significantly influences the regression accuracy. However, its use in reliability applications has not yet been widely explored. Bearing this in mind, remaining useful life values have been predicted here by using the hybrid ABC–MARS-based model from the remaining measured parameters (input variables) for aircraft engines with success. A correlation coefficient equal to 0.92 was obtained when this hybrid ABC–MARS-based model was applied to experimental data. The agreement of this model with experimental data confirmed its good performance. The main advantage of this predictive model is that it does not require information about the previous operation states of the aircraft engine.http://www.mdpi.com/1996-1073/9/6/409multivariate adaptive regression splines (MARS)artificial bee colony (ABC)aircraft engineremaining useful life (RUL)prognosticsreliability |
| spellingShingle | Paulino José García Nieto Esperanza García-Gonzalo Antonio Bernardo Sánchez Marta Menéndez Fernández A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines Energies multivariate adaptive regression splines (MARS) artificial bee colony (ABC) aircraft engine remaining useful life (RUL) prognostics reliability |
| title | A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines |
| title_full | A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines |
| title_fullStr | A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines |
| title_full_unstemmed | A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines |
| title_short | A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines |
| title_sort | new predictive model based on the abc optimized multivariate adaptive regression splines approach for predicting the remaining useful life in aircraft engines |
| topic | multivariate adaptive regression splines (MARS) artificial bee colony (ABC) aircraft engine remaining useful life (RUL) prognostics reliability |
| url | http://www.mdpi.com/1996-1073/9/6/409 |
| work_keys_str_mv | AT paulinojosegarcianieto anewpredictivemodelbasedontheabcoptimizedmultivariateadaptiveregressionsplinesapproachforpredictingtheremainingusefullifeinaircraftengines AT esperanzagarciagonzalo anewpredictivemodelbasedontheabcoptimizedmultivariateadaptiveregressionsplinesapproachforpredictingtheremainingusefullifeinaircraftengines AT antoniobernardosanchez anewpredictivemodelbasedontheabcoptimizedmultivariateadaptiveregressionsplinesapproachforpredictingtheremainingusefullifeinaircraftengines AT martamenendezfernandez anewpredictivemodelbasedontheabcoptimizedmultivariateadaptiveregressionsplinesapproachforpredictingtheremainingusefullifeinaircraftengines AT paulinojosegarcianieto newpredictivemodelbasedontheabcoptimizedmultivariateadaptiveregressionsplinesapproachforpredictingtheremainingusefullifeinaircraftengines AT esperanzagarciagonzalo newpredictivemodelbasedontheabcoptimizedmultivariateadaptiveregressionsplinesapproachforpredictingtheremainingusefullifeinaircraftengines AT antoniobernardosanchez newpredictivemodelbasedontheabcoptimizedmultivariateadaptiveregressionsplinesapproachforpredictingtheremainingusefullifeinaircraftengines AT martamenendezfernandez newpredictivemodelbasedontheabcoptimizedmultivariateadaptiveregressionsplinesapproachforpredictingtheremainingusefullifeinaircraftengines |