In order to minimize the cost of maintenance and to avoid sudden failures of components in vertical axis wind turbines (VAWT), the employment of a condition monitoring system is necessary. Especially monitoring the source of vibration and controlling is a significant process in the structural reliability of any components. The gearbox in the VAWT is such type of a source to be monitored to avoid substantial downtime. The sudden rise in the need for alternate energy sources, the installation of wind turbines was gradually increased with increased data in condition monitoring. So interpreting and analyzing such vast resources of data required an efficient system. In this article, an automated adapted framework has been employed to analyze the gearbox failure. The adapted framework is anticipated to analyze the vibration signals, monitor the health, and isolate the faults by processing the signals with the support of artificial intelligence and machine learning techniques. It is anticipated to produce an efficient solution for the reduction of downtime in VAWT operations due to failures.