Application on Generating Data Pattern of Car's Engine Combustion with Exhaust Gas Base

The exhaust of motor vehicle contain elements and compounds that indicate combustion conditions in the engine combustion chamber including the condition of internal combustion engine and external combustion engine. The concentration of elements and compounds that are dominant in determining the engine combustion conditions on exhaust emissions are Hydrocarbon (HC), Carbon Monoxide (CO), Carbon Dioxide (CO2) and Oxygen (O2). Elements and compounds contained in exhaust emissions can be detected by a sensors that sensitive to several levels of these elements and compounds. The result of analog data obtained on the sensor at time domain is converted to frequency domain through Fast Fourier Transform (FFT) method. Furthermore, normalization of the spectrum and unique data collection obtained to form data patterns that characterizes the combustion conditions of the machine. This study aims to make the system to be able to display the form of data pattern category of combustion engine car fuel gasoline with carburetor system through the detection of exhaust emissions. This system consists of a multisensor gas as an input component, and a signal processing system using Field Programable Gate Array logic (FPGA) MyRIO module production National Instrument. Trials were conducted on a number of car-fueled carburetor system cars with different brands, manufacturers and years of manufacture. Test results in the form of sensor response to the levels and elements of the exhaust gas and detection patterns of data displayed in the form of graphs of data categories burning machine. The results of the data pattern detection indicate a perfect burning category of 83.33%, and indication of incomplete combustion category pattern of 90%