<![CDATA[This study has created a system capable of identifying the condition of the piston ring and cylinder block of a 4-stroke motorcycle engine using petrol or similar through exhaust emissions. Multisensory gas, sensitive to changes in CO, CO2, NOx, and HC gas elements and compounds, is installed as an input to the exhaust channel and integrated using LabVIEW programming on the NI myRIO module. Multisensory data is processed using the FFT and the backpropagation method to classify whether the piston rings and engine cylinder block are in good or damaged condition. Tests have been carried out on motorbikes with piston rings and engine cylinder blocks that are in good, damaged, or unknown condition. During the test, the target error value for motorcycles with piston rings and engine cylinder blocks in good or damaged condition is less than 1%. The system can distinguish the condition of the piston ring and cylinder block of a motorcycle engine that is 100% optimal and 100% damaged with an error of 0% compared to the compression test method, and the maximum error is 20% Compared to the technician's manual method. Ten motorcycles were randomly tested in unknown conditions; 50% were in good condition, and 50% were damaged. For further development, an electronic nose system can detect engine combustion conditions and damage to cylinder rings and 4-stroke motorbike engine blocks based on exhaust emissions.]]>
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