In the current research on the fatigue state of controllers using radiotelephony communication, most of them only consider the changes of voice in the time domain or frequency domain, while ignore that fatigue will affect the time domain and frequency domain at the same time. In this paper, the voice of radiotelephony communication in the three fatigue states is converted into speech spectrum images that can reflect the characteristics of both the time domain and frequency domain, and the grayscale co-existence matrix (GLCM) is used to extract the typical feature parameters in four dimensions, compare the changes of the characteristic parameters of the controllers in different states, and confirm that the selected features have a good discrimination. The selected features were detected as the input features of the controller fatigue detection model, and the detection accuracy of using the spectral pattern features combined with the traditional features as the input features was the highest, reaching 95.49%, which was 4% higher than that of the traditional features alone. The results show that the change of controllers fatigue state will be intuitively reflected on the spectrogram and will have an impact on its eigenvalues, and good results can be obtained by using this influence to detect the controllers fatigue state.