The diagnosis of intermittent faults is crucial in the field of maintenance support. However, most existing studies focus on the analysis of intermittent faults of single components, ignoring the more complex intermittent failures of equipment functions due to the coupling of multivariate anomalous states in the fault propagation process. Existing diagnostic methods based on fault propagation models, which mainly focus on one-dimensional temporal or logical relationships, fall short in representing and reasoning about intermittent faults caused by temporal and state coupling. In this paper, we propose a Temporal Constrained Dynamic Uncertain Causality Graph (TC-DUCG) model to fill this gap and effectively model intermittent faults. The model not only considers the probability of fault propagation among variables, but also integrates temporal constraints. It also presents a diagnostic reasoning process to investigate potential causes of intermittent faults. We provide an illustrative example to demonstrate the effectiveness of the proposed method in diagnosing intermittent faults.