Gears are one of the most significant machine components, and they are found all over the place in transmission systems and other rotating machinery. In the industry, the failure of such critical components results in significant losses. Vibration analysis is the most common method for determining the nature and severity of problems in machines and components. Early defect identification and diagnosis enables correctly timed shutdowns to avoid catastrophic failure, resulting in safer operation. Many studies have recently been conducted to construct faulty gear box dynamic models in order to better understand the mechanism of gear fault formation and then design effective fault detection and diagnosis methods. The focus of this study is on dynamic gearbox fault modeling, detection, and diagnosis. The vibration analysis of the gear box was obtained from various fault circumstances, speed and loads in the study of this study. For all conditions, vibration time domain and frequency domain signals are obtained, and the resulting signals for faults are compared to the signals of healthy gear. Examination tests on an experimental test rig were used to accomplish experimental validation of the suggested system. In addition, the model shows that changing the load and speed causes the same results as the trails. Finally, multiple signal processing algorithms were used to analyze the vibration data collected from an accelerometer mounted on the gearbox shell.

Vibration Analysis, fault detection, helical gear