AI Based Automatic Fault Diagnosis and Rectification System

Abstract

AI Based Automatic Fault Diagnosis and Rectification System in Car is a paper aimed at improving vehicle safety, reliability, and performance by automatically detecting and correcting faults in automotive systems. Modern vehicles consist of multiple electrical, electronic, and mechanical subsystems, and faults within these subsystems may lead to unexpected failures, reduced efficiency, or hazardous situations if not identified at an early stage. Traditional fault diagnosis methods depend largely on manual inspection or periodic servicing, which are often time-consuming and may not provide real-time fault detection. To address these limitations, we have developed an intelligent fault diagnosis system using an Arduino Nano board as the controller board to interface all sensors and actuators. Various sensors installed in the vehicle continuously monitor critical parameters such as engine temperature, battery voltage, fuel level, and exhaust gas conditions. The controller analyzes the sensor data using trained neural network models to identify abnormal operating conditions and classify different types of faults. Once a fault is detected, the system automatically initiates appropriate rectification actions such as activating protective relays, controlling cooling mechanisms, or generating warning indications. Fault information is displayed on an LCD for the driver’s awareness and can also be transmitted wirelessly through a Bluetooth module to an external device. The proposed system provides real-time monitoring, early fault detection, and automatic rectification, thereby reducing human intervention and maintenance effort. This intelligent approach enhances overall vehicle safety, minimizes downtime, and contributes to the development of smart and reliable automotive systems. [3-4]