Condition Monitoring in Marine Oil Separation Systems Using Wavelet Packet Transform and Genetic Technique
Condition Monitoring is key to predictive maintenance and especially in the operational efficiency of the Marine Oil Separation System. These systems are crucial for environmental protection and compliance with international maritime regulations. Therefore, it is necessary to design a technique capa...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/12/11/2073 |
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| author | Ángela Hernández Cristina Castejón Deivis Ávila María Jesús Gómez-García Graciliano Nicolás Marichal |
| author_facet | Ángela Hernández Cristina Castejón Deivis Ávila María Jesús Gómez-García Graciliano Nicolás Marichal |
| author_sort | Ángela Hernández |
| collection | DOAJ |
| description | Condition Monitoring is key to predictive maintenance and especially in the operational efficiency of the Marine Oil Separation System. These systems are crucial for environmental protection and compliance with international maritime regulations. Therefore, it is necessary to design a technique capable of analyzing the signals from sensors and estimating the remaining useful life in order to avoid breakage or unnecessary replacement. This work presents an intelligent method with signal processing based on Wavelet Packets Transform that provides energy data from vibration measurements as characteristic parameters. These values can be related to its RUL, and they are used as inputs for the training process. In particular, a Genetic Neuro-Fuzzy system is proposed as an intelligent classification technique. Once the training process is completed, it can be concluded that a good classifier has been built, since it relates the energy state of the oil separation system with its remaining useful life, and therefore, the necessary information for efficient predictive maintenance is achieved. Furthermore, a mechanism to obtain the final set of fuzzy rules has been developed, showing the correspondence between these fuzzy rules and the neural network structure. |
| format | Article |
| id | doaj-art-c1bf3c32f3ae46f6bb6a159ab5332fcf |
| institution | OA Journals |
| issn | 2077-1312 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-c1bf3c32f3ae46f6bb6a159ab5332fcf2025-08-20T01:54:02ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-11-011211207310.3390/jmse12112073Condition Monitoring in Marine Oil Separation Systems Using Wavelet Packet Transform and Genetic TechniqueÁngela Hernández0Cristina Castejón1Deivis Ávila2María Jesús Gómez-García3Graciliano Nicolás Marichal4Escuela Superior de Ingeniería y Tecnología, Universidad de La Laguna, 38203 La Laguna, SpainDepartamento de Ingeniería Mecánica, Universidad Carlos III de Madrid, 28911 Leganés, SpainEscuela Superior de Ingeniería y Tecnología, Universidad de La Laguna, 38203 La Laguna, SpainDepartamento de Ingeniería Mecánica, Universidad Carlos III de Madrid, 28911 Leganés, SpainEscuela Superior de Ingeniería y Tecnología, Universidad de La Laguna, 38203 La Laguna, SpainCondition Monitoring is key to predictive maintenance and especially in the operational efficiency of the Marine Oil Separation System. These systems are crucial for environmental protection and compliance with international maritime regulations. Therefore, it is necessary to design a technique capable of analyzing the signals from sensors and estimating the remaining useful life in order to avoid breakage or unnecessary replacement. This work presents an intelligent method with signal processing based on Wavelet Packets Transform that provides energy data from vibration measurements as characteristic parameters. These values can be related to its RUL, and they are used as inputs for the training process. In particular, a Genetic Neuro-Fuzzy system is proposed as an intelligent classification technique. Once the training process is completed, it can be concluded that a good classifier has been built, since it relates the energy state of the oil separation system with its remaining useful life, and therefore, the necessary information for efficient predictive maintenance is achieved. Furthermore, a mechanism to obtain the final set of fuzzy rules has been developed, showing the correspondence between these fuzzy rules and the neural network structure.https://www.mdpi.com/2077-1312/12/11/2073wavelet packet transformgenetic neuro-fuzzycondition monitoring |
| spellingShingle | Ángela Hernández Cristina Castejón Deivis Ávila María Jesús Gómez-García Graciliano Nicolás Marichal Condition Monitoring in Marine Oil Separation Systems Using Wavelet Packet Transform and Genetic Technique Journal of Marine Science and Engineering wavelet packet transform genetic neuro-fuzzy condition monitoring |
| title | Condition Monitoring in Marine Oil Separation Systems Using Wavelet Packet Transform and Genetic Technique |
| title_full | Condition Monitoring in Marine Oil Separation Systems Using Wavelet Packet Transform and Genetic Technique |
| title_fullStr | Condition Monitoring in Marine Oil Separation Systems Using Wavelet Packet Transform and Genetic Technique |
| title_full_unstemmed | Condition Monitoring in Marine Oil Separation Systems Using Wavelet Packet Transform and Genetic Technique |
| title_short | Condition Monitoring in Marine Oil Separation Systems Using Wavelet Packet Transform and Genetic Technique |
| title_sort | condition monitoring in marine oil separation systems using wavelet packet transform and genetic technique |
| topic | wavelet packet transform genetic neuro-fuzzy condition monitoring |
| url | https://www.mdpi.com/2077-1312/12/11/2073 |
| work_keys_str_mv | AT angelahernandez conditionmonitoringinmarineoilseparationsystemsusingwaveletpackettransformandgenetictechnique AT cristinacastejon conditionmonitoringinmarineoilseparationsystemsusingwaveletpackettransformandgenetictechnique AT deivisavila conditionmonitoringinmarineoilseparationsystemsusingwaveletpackettransformandgenetictechnique AT mariajesusgomezgarcia conditionmonitoringinmarineoilseparationsystemsusingwaveletpackettransformandgenetictechnique AT gracilianonicolasmarichal conditionmonitoringinmarineoilseparationsystemsusingwaveletpackettransformandgenetictechnique |