This paper presents the prognosis of automobile engine using artificial neural network (ANN). The prognosis of automobile engine has been performed by real-time data acquisition for implementation of ANN. The three major parameters for the automobile engine which are Coolant temperature, RPM, and Throttle value are monitored in real time. Using the real-time datasets, ANN model is trained and tested to accurately monitor the variation in the Throttle value output due to input, i.e., Coolant temperature and RPM variations. The considerable variation in Throttle value output from a threshold value that is quantitatively obtained using proposed ANN gives the faulty condition of the engine.
Implementation of ANN for Prognosis of Automobile Engine
Lect.Notes Mechanical Engineering
Biennial International Conference on Future Learning Aspects of Mechanical Engineering ; 2022 ; Noida, India August 03, 2022 - August 05, 2022
2023-06-19
8 pages
Article/Chapter (Book)
Electronic Resource
English
Implementation of ANN for Prognosis of Automobile Engine
TIBKAT | 2023
|SAE Technical Papers | 1985
|Automotive engineering | 1985
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