ICA-Feature-Extraction-Based Fault Identification of Vehicular Starter Motor

IEEE SENSORS LETTERS(2023)

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Abstract
The starter motor is responsible for providing the mechanical rotating energy for automotive operation through electromechanical conversion via the battery. In case of a fault on the starter motor, the vehicle will fail to operate posing problems for the driver, especially for an emergency service vehicle like an ambulance. The starter motor and its corresponding components are prone to mechanical as well as electrical faults due to high starting torque and friction with the flywheel and gear teeth of the starter. In this letter, the focus has been given to the electrical fault of a starter motor and its effect on the operational characteristics of an automobile. The response characteristics thus obtained have been evaluated by the independent-component-analysis-based feature extraction analysis to obtain a continuous dataset for automobile fault diagnosis. The feature analysis of the response characteristics helps in easier calculation while being effective in designing a system that can help with vehicle diagnosis and quality control.
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Key words
Sensor applications,automobile,feature extraction algorithm (FEA),fast Fourier transform (FFT),independent component analysis (ICA),starter motor
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