An Investigation On Gasoline Engine Misfire Fault Using Multi Sensors And Analyzing With Vibration Signal Analysis

Awang, A’bdul Rahman (2018) An Investigation On Gasoline Engine Misfire Fault Using Multi Sensors And Analyzing With Vibration Signal Analysis. Project Report. UTeM, Melaka, Malaysia. (Submitted)

Text (24 Pages) An Investigation On Gasoline Engine Misfire Fault Using Multi Sensors And Analyzing With Vibration Signal Analysis.pdf - Submitted Version Download (376kB)

Abstract

A condition monitoring applied to gasoline engines, improves safety, productivity, reduces maintenance costs and increases serviceability. There are many fault diagnosis at the rotary machine which the vehicle engine, heavy duty machine and need to investigated through the different kinds of signals. Base on the literature, all literature says that vibration signal analysis (VSA) is the most accurately to analyses effective approach. This research was investigate and analyses the BMW D1 N43B20 gasoline engine fault which is misfire fault using the two different sensor accelerometer and piezo film was mounted at the engine wall near the internal combustion engine. The application of the Fast Fourier Transform (FFT), MatLAb is proposed as a main extraction methodology to find the accurate data. The vibration signal analysis was propose root mean square, standard deviation, skewness and kurtosis to select which one the best features to find the misfire fault in the internal combustion engine. It also to predict if the engine or ICE works healthily based on the selected features and, if not, what kind of faults is in the engine. By comparing the different result with the similar efforts in the literature proves the validity of the proposed. A review of the VSA sources in gasoline engines and how to represent the VSA signals generated is presented. There are four analysis methods were used time-domain analysis using parameters such as Root Mean Square (RMS), Standard Deviation, Skewness and Kurtosis. The frequency-domain analysis which relied on the amplitudes of the frequency components. In this researches, data has been obtained from tests on a BMW D1 N43B20 gasoline engine, where the engine speed, temperature and the type of fault which is the misfire at every cylinder were changed. It can be monitored signal and its difference from that obtained for normal engine conditions was well-known as a fault signature that could be used for fault detection and diagnosis/investigate.

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