A Model-Free Diagnosis Approach for Intake Leakage Detection and Characterization in Diesel Engines
Feature selection is an essential step for data classification used in fault detection and diagnosis processes. In this work, a new approach is proposed, which combines a feature selection algorithm and a neural network tool for leak detection and characterization tasks in diesel engine air paths. T...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-07-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2075-1702/3/3/157 |
| _version_ | 1818199545378504704 |
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| author | Ghaleb Hoblos Mourad Benkaci |
| author_facet | Ghaleb Hoblos Mourad Benkaci |
| author_sort | Ghaleb Hoblos |
| collection | DOAJ |
| description | Feature selection is an essential step for data classification used in fault detection and diagnosis processes. In this work, a new approach is proposed, which combines a feature selection algorithm and a neural network tool for leak detection and characterization tasks in diesel engine air paths. The Chi square classifier is used as the feature selection algorithm and the neural network based on Levenberg-Marquardt is used in system behavior modeling. The obtained neural network is used for leak detection and characterization. The model is learned and validated using data generated by xMOD. This tool is used again for testing. The effectiveness of the proposed approach is illustrated in simulation when the system operates on a low speed/load and the considered leak affecting the air path is very small. |
| first_indexed | 2024-12-12T02:23:28Z |
| format | Article |
| id | doaj.art-1c66166ff4e7497b97ea818e8de3c0bc |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-12-12T02:23:28Z |
| publishDate | 2015-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-1c66166ff4e7497b97ea818e8de3c0bc2022-12-22T00:41:37ZengMDPI AGMachines2075-17022015-07-013315717210.3390/machines3030157machines3030157A Model-Free Diagnosis Approach for Intake Leakage Detection and Characterization in Diesel EnginesGhaleb Hoblos0Mourad Benkaci1ESIGELEC-IRSEEM, Avenue Galilée, 76801 Saint Etienne du Rouvray, FranceESIGELEC-IRSEEM, Avenue Galilée, 76801 Saint Etienne du Rouvray, FranceFeature selection is an essential step for data classification used in fault detection and diagnosis processes. In this work, a new approach is proposed, which combines a feature selection algorithm and a neural network tool for leak detection and characterization tasks in diesel engine air paths. The Chi square classifier is used as the feature selection algorithm and the neural network based on Levenberg-Marquardt is used in system behavior modeling. The obtained neural network is used for leak detection and characterization. The model is learned and validated using data generated by xMOD. This tool is used again for testing. The effectiveness of the proposed approach is illustrated in simulation when the system operates on a low speed/load and the considered leak affecting the air path is very small.http://www.mdpi.com/2075-1702/3/3/157leak detectionautomotive diagnosisfeature selectionneural data classificationdiesel air path |
| spellingShingle | Ghaleb Hoblos Mourad Benkaci A Model-Free Diagnosis Approach for Intake Leakage Detection and Characterization in Diesel Engines Machines leak detection automotive diagnosis feature selection neural data classification diesel air path |
| title | A Model-Free Diagnosis Approach for Intake Leakage Detection and Characterization in Diesel Engines |
| title_full | A Model-Free Diagnosis Approach for Intake Leakage Detection and Characterization in Diesel Engines |
| title_fullStr | A Model-Free Diagnosis Approach for Intake Leakage Detection and Characterization in Diesel Engines |
| title_full_unstemmed | A Model-Free Diagnosis Approach for Intake Leakage Detection and Characterization in Diesel Engines |
| title_short | A Model-Free Diagnosis Approach for Intake Leakage Detection and Characterization in Diesel Engines |
| title_sort | model free diagnosis approach for intake leakage detection and characterization in diesel engines |
| topic | leak detection automotive diagnosis feature selection neural data classification diesel air path |
| url | http://www.mdpi.com/2075-1702/3/3/157 |
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