Investigations on the Effect of Injection Pressure and Timing on Noise and Vibration Characteristics of a Biodiesel Fueled Genset Engine and Artificial Neural Network Architecture

In this present investigation, combustion, noise and vibration characteristics were studied in a direct injection compression ignition engine by blending of 20% Pongamia biodiesel with neat diesel. Experiments were conducted with different fuel injection pressures and injection timings. The brake thermal efficiency of the biodiesel blend found increased to 1.75% when the fuel was injected at 200 bar and 23° before top dead center. Higher engine vibration of 5.5% was observed in Y-axis at the fuel injection pressure of 250 bar with the injection timing of 25° bTDC when comparing to the standard operating condition of the engine. The combustion noise level found decreased to 4% when the fuel injection time increased from 21 to 23° bTDC. From Artificial Neural Network analysis, two metrics, such as Coefficient of correlation (R) and Mean Square Error (MSE), were found as 0.99 and 12.6, respectively. The developed artificial neural network model predicts and optimizes the parameters used in this experiment. The overall regression coefficient of developed model R is found as 0.94; hence the result showed that the developed model can predict the noise and vibrations of Genset engines more accurately.