The aim of this thesis is to design a process for the automatic detection of engine faults by analysing sound spectrograms. The designed technique mimics the manual state-of-the-art analysis performed by domain experts. Each operation of our method is performed automatically, without requiring domain experts intervention. The manual process being replicated consists of analysing the spectrogram image obtained from the sound emitted by the engine under inspection. This visualized spectrogram allows highlighting engine faults, which occur with peculiar characteristics that are well known by the experts. In particular, we focused on the detection of a whistle called constant tone, which appears as a straight noisy line in the spectrogram.