One of the most important machine parts, gears can be found in a wide variety of rotating machinery, including transmission systems. Significant losses occur in the industry when such crucial components fail. The most popular technique for figuring out the kind and extent of issues with machines and components is vibration analysis. A safer operation is the consequence of early problem detection and identification, which allows for properly timed shutdowns to prevent catastrophic failure. Recently, a great deal of research has been done to build dynamic models of faulty gearboxes in order to better understand the mechanism of gear fault creation and subsequently devise efficient fault detection and diagnosis techniques. 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.