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• W2911791808 abstract "The increasing use of biofuels in recent years has resulted in renewed consideration of compression ignition (CI) engines for power generation. However, the differences in chemical properties of these fuels have led to some variation in key engine performance parameters. Accordingly, researchers have begun to investigate the use of vibration-based approaches in assessing these behaviors. Despite some progress in assessing the use of diesel in CI engines, very little has been done on assessing the use of fuel blends. The current work, therefore, proposes a vibration-based approach to assessing engine performance in CI engines. It hypothesizes that the variation in cylinder pressure with combustion can be effectively monitored via engine vibration signals. It further proposes the use of a hybrid calculus-statistical method for the analysis of the vibration data. Accordingly, tests were conducted using a single-cylinder engine made to operate on different fuel blends. Conventional thermodynamic data were recorded during its operation. These data were used to calculate fundamental engine performance indicators. Simultaneously, vibration data were collected from the engine using an accelerometer mounted on the engine casing. The vibration data were analyzed using a matlab algorithm. The results showed that the proposed method is able to track the variations in combustion performance, for changes in the fuel used. More importantly, based on the approach, a parameter, which characterizes the nature of combustion taking place, is proposed. The approach proves to be a feasible method for assessing combustion performance of different fuels in CI engines, with minimal computational requirements." @default.
• W2911791808 created "2019-02-21" @default.
• W2911791808 creator A5048501916 @default.
• W2911791808 creator A5050676029 @default.
• W2911791808 date "2019-03-07" @default.
• W2911791808 modified "2023-09-27" @default.
• W2911791808 title "Assessing Combustion Performance of a Diesel Reciprocating Engine Under Various Fuel Blends Using a Calculus-Statistical Time-Series Vibration Based Approach" @default.
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• W2911791808 doi "https://doi.org/10.1115/1.4042832" @default.
• W2911791808 hasPublicationYear "2019" @default.
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