Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal
Piston engines fueled by kerosene have a strong application prospect in special vehicles and small aircrafts, but the low amount of octane in kerosene fuel causes its knock combustion phenomenon to be particularly serious. A knock will deteriorate the power and economy of the engine and will damage...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/6/2766 |
| _version_ | 1797612049031757824 |
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| author | Zhixin Xu Guangzhou Cao Minxiang Wei Zhuowen Zhao Zhiyu Xing Yuzhang Ding |
| author_facet | Zhixin Xu Guangzhou Cao Minxiang Wei Zhuowen Zhao Zhiyu Xing Yuzhang Ding |
| author_sort | Zhixin Xu |
| collection | DOAJ |
| description | Piston engines fueled by kerosene have a strong application prospect in special vehicles and small aircrafts, but the low amount of octane in kerosene fuel causes its knock combustion phenomenon to be particularly serious. A knock will deteriorate the power and economy of the engine and will damage the engine in serious cases. Therefore, knocking is the key problem with kerosene engines. We propose a knock-prediction system for kerosene engines based on in-cylinder pressure signals. Firstly, the intrinsic mode function (IMF) caused by knock resonance is extracted from the in-cylinder pressure signal via empirical mode decomposition (EMD) and a time–frequency domain analysis. A time-domain statistical analysis (TDSA) combined with a principal component analysis (PCA) is used to extract features from the IMF. Finally, the data collected from the test bench are trained by a support vector machine to obtain the knock-prediction model. Compared with other technical combinations for training, the proposed scheme achieved more accurate results in knock prediction. Considering the working characteristics of kerosene engines, a slight knock can increase the power of a kerosene engine. Therefore, some incorrectly predicted cycles (slight-knock cycles) do not affect the normal operation of the engine. |
| first_indexed | 2024-03-11T06:36:34Z |
| format | Article |
| id | doaj.art-28c8c8e69f9841bf92d9513a38d3f904 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T06:36:34Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-28c8c8e69f9841bf92d9513a38d3f9042023-11-17T10:50:42ZengMDPI AGEnergies1996-10732023-03-01166276610.3390/en16062766Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure SignalZhixin Xu0Guangzhou Cao1Minxiang Wei2Zhuowen Zhao3Zhiyu Xing4Yuzhang Ding5College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaResearch Institute of Unmanned Aircraft, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaCollege of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaCollege of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaCollege of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaCollege of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaPiston engines fueled by kerosene have a strong application prospect in special vehicles and small aircrafts, but the low amount of octane in kerosene fuel causes its knock combustion phenomenon to be particularly serious. A knock will deteriorate the power and economy of the engine and will damage the engine in serious cases. Therefore, knocking is the key problem with kerosene engines. We propose a knock-prediction system for kerosene engines based on in-cylinder pressure signals. Firstly, the intrinsic mode function (IMF) caused by knock resonance is extracted from the in-cylinder pressure signal via empirical mode decomposition (EMD) and a time–frequency domain analysis. A time-domain statistical analysis (TDSA) combined with a principal component analysis (PCA) is used to extract features from the IMF. Finally, the data collected from the test bench are trained by a support vector machine to obtain the knock-prediction model. Compared with other technical combinations for training, the proposed scheme achieved more accurate results in knock prediction. Considering the working characteristics of kerosene engines, a slight knock can increase the power of a kerosene engine. Therefore, some incorrectly predicted cycles (slight-knock cycles) do not affect the normal operation of the engine.https://www.mdpi.com/1996-1073/16/6/2766knock predictionkerosene engineempirical mode decompositionsupport vector machine |
| spellingShingle | Zhixin Xu Guangzhou Cao Minxiang Wei Zhuowen Zhao Zhiyu Xing Yuzhang Ding Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal Energies knock prediction kerosene engine empirical mode decomposition support vector machine |
| title | Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal |
| title_full | Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal |
| title_fullStr | Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal |
| title_full_unstemmed | Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal |
| title_short | Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal |
| title_sort | knock prediction system for kerosene engines using in cylinder pressure signal |
| topic | knock prediction kerosene engine empirical mode decomposition support vector machine |
| url | https://www.mdpi.com/1996-1073/16/6/2766 |
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