Maintenance planning of two-component systems has been extensively studied in recent decades. In the literature, most studies assume that the failure cause of a two-component system is self-announcing. In some real applications, the failure cause is masked, and a diagnosis with professional equipment is needed to reveal the failed component. This study investigates a preventive replacement policy of a two-component series system considering masked causes of failure. When an unexpected failure occurs, we can carry out a diagnosis to reveal the failed component and replace it subsequently, or we can directly replace the whole system without diagnosis. Meanwhile, when we carry out a preventive replacement on a component, the other component can be replaced opportunistically. We formulate the problem as a semi-Markov decision process, and prove the existence of the stationary optimal policy. The optimal preventive replacement age thresholds for each component and the corresponding optimal maintenance actions upon each failure are jointly obtained to minimize the long-term average maintenance cost per time unit. A comprehensive numerical study is provided to illustrate the effectiveness of our proposed model.