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In the present study, in order to detect the fault of the gearmeshs, two engaged gears based on research department of a major automotive company have been modeled. First off, by using the CATIA software the fault was induced to the output gear. Then, the faulty gearmesh and non-faulty gearmesh is modeled to find the fault pattern to predict and estimate the failure of the gearmesh. The induced defect is according to the frequently practical fault that takes place to the teeth of gears. In order to record the acceleration signals to calculate the decomposition algorithm, mount the accelerometer on accessible place of the output shaft to recognize the pattern. Then, for more realistic simulation, noise is added to the output signal. At the first step by means of Butterworth low pass digital, the noise has to be removed from signals after that by using the Empirical Mode Decomposition (EMD), signals have decomposed into the Instinct Mode Function (IMF) and every IMF were tested by using the Instantaneous Frequency (IF) in way of Hillbert Transform (HT). For this purpose a code was developed in MATLAB software. Then, in order to detect the presence of the fault the frequency spectrum of IMF's are created and defect is detected in gearmesh frequency of the spectrum. [ABSTRACT FROM AUTHOR]