Frequency Analysis of Car Engine Sounds and Fault Detection with Machine Learning

This study aims to create a database to detect the healthy or faulty states of automotive engines using engine sound data. Sound signals collected through microphones are analyzed using deep learning algorithms to enable the quick and reliable diagnosis of engine faults. This article serves as a preliminary study for the project. In the next step, a comprehensive article will be added to the database, including technical details such as code, libraries, and circuit design.