Prolonged viewing of 3D content may result in severe fatigue symptoms, giving negative user experience thus hindering the development of 3D industry. For 3D visual fatigue evaluation, previous studies focused on exploring the changes of frequency-domain features in EEG for various fatigue degrees. However, their time-domain features were scarcely investigated. In this study, a modified paradigm with a random disparities order is adopted to evoke the depth-related visual evoked potentials (DVEPs). Then the characteristics of the DVEPs components for various fatigue degrees are compared using one-way repeated-measurement ANOVA. Point-by-point permutation statistics revealed sample points from 100ms to 170ms - including P1 and N1 - in sensors Pz and P4 changed significantly with visual fatigue. More specifically, we find that the amplitudes of P1 and N1 change significantly when visual fatigue increases. Additionally, independent component analysis identify P1 and N1 which originate from posterior cingulate cortex are associated statistically with 3D visual fatigue. Our results indicate there is a significant correlation between 3D visual fatigue and P1 amplitude, as well as N1, of DVEPs on right parietal areas. We believe the characteristics (e.g., amplitude and latency) of identified components may be the indicators of 3D visual fatigue evaluation. Furthermore, we argue that 3D visual fatigue may be associated with the activities decrease of the attention and the processing capacity of disparity.